7,698 research outputs found
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Production networks in the cultural and creative sector: case studies from the publishing industry
The CICERONE project investigates cultural and creative industries through case study research, with a focus on production networks. This report, part of WP2, examines the publishing industry within this framework. It aims to understand the industry’s hidden aspects, address statistical issues in measurement, and explore the industry’s transformation and integration of cultural and economic values. The report provides an overview of the production network, explores statistical challenges, and presents qualitative analyses of two case studies. It concludes by highlighting the potential of the Global Production Network (GPN) approach for analyzing, researching, policymaking, and intervening in the European publishing network.
The CICERONE project’s case study research delves into the publishing industry, investigating its production networks and examining key aspects often unseen by the public. The report addresses statistical challenges in measuring the industry and sheds light on its ongoing transformations and integration of cultural and economic values. It presents an overview of the production network, explores statistical issues, and provides qualitative analyses of two case studies. The report emphasizes the potential of the GPN approach for analyzing and intervening in the European publishing network, ultimately contributing to research, policymaking, and understanding within the industry
An empirical investigation of the relationship between integration, dynamic capabilities and performance in supply chains
This research aimed to develop an empirical understanding of the relationships between integration,
dynamic capabilities and performance in the supply chain domain, based on which, two conceptual
frameworks were constructed to advance the field. The core motivation for the research was that, at
the stage of writing the thesis, the combined relationship between the three concepts had not yet
been examined, although their interrelationships have been studied individually.
To achieve this aim, deductive and inductive reasoning logics were utilised to guide the qualitative
study, which was undertaken via multiple case studies to investigate lines of enquiry that would
address the research questions formulated. This is consistent with the author’s philosophical
adoption of the ontology of relativism and the epistemology of constructionism, which was considered
appropriate to address the research questions. Empirical data and evidence were collected, and
various triangulation techniques were employed to ensure their credibility. Some key features of
grounded theory coding techniques were drawn upon for data coding and analysis, generating two
levels of findings. These revealed that whilst integration and dynamic capabilities were crucial in
improving performance, the performance also informed the former. This reflects a cyclical and
iterative approach rather than one purely based on linearity. Adopting a holistic approach towards
the relationship was key in producing complementary strategies that can deliver sustainable supply
chain performance.
The research makes theoretical, methodological and practical contributions to the field of supply
chain management. The theoretical contribution includes the development of two emerging
conceptual frameworks at the micro and macro levels. The former provides greater specificity, as it
allows meta-analytic evaluation of the three concepts and their dimensions, providing a detailed
insight into their correlations. The latter gives a holistic view of their relationships and how they are
connected, reflecting a middle-range theory that bridges theory and practice. The methodological
contribution lies in presenting models that address gaps associated with the inconsistent use of
terminologies in philosophical assumptions, and lack of rigor in deploying case study research
methods. In terms of its practical contribution, this research offers insights that practitioners could
adopt to enhance their performance. They can do so without necessarily having to forgo certain
desired outcomes using targeted integrative strategies and drawing on their dynamic capabilities
Integrating materials supply in strategic mine planning of underground coal mines
In July 2005 the Australian Coal Industry’s Research Program (ACARP) commissioned Gary Gibson to identify constraints that would prevent development production rates from achieving full capacity. A “TOP 5” constraint was “The logistics of supply transport distribution and handling of roof support consumables is an issue at older extensive mines immediately while the achievement of higher development rates will compound this issue at most mines.” Then in 2020, Walker, Harvey, Baafi, Kiridena, and Porter were commissioned by ACARP to investigate Australian best practice and progress made since Gibson’s 2005 report. This report was titled: - “Benchmarking study in underground coal mining logistics.” It found that even though logistics continue to be recognised as a critical constraint across many operations particularly at a tactical / day to day level, no strategic thought had been given to logistics in underground coal mines, rather it was always assumed that logistics could keep up with any future planned design and productivity. This subsequently meant that without estimating the impact of any logistical constraint in a life of mine plan, the risk of overvaluing a mining operation is high.
This thesis attempts to rectify this shortfall and has developed a system to strategically identify logistics bottlenecks and the impacts that mine planning parameters might have on these at any point in time throughout a life of mine plan. By identifying any logistics constraints as early as possible, the best opportunity to rectify the problem at the least expense is realised. At the very worst if a logistics constraint was unsolvable then it could be understood, planned for, and reflected in the mine’s ongoing financial valuations. The system developed in this thesis, using a suite of unique algorithms, is designed to “bolt onto” existing mine plans in the XPAC mine scheduling software package, and identify at a strategic level the number of material delivery loads required to maintain planned productivity for a mining operation. Once an event was identified the system then drills down using FlexSim discrete event simulation to a tactical level to confirm the predicted impact and understand if a solution can be transferred back as a long-term solution. Most importantly the system developed in this thesis was designed to communicate to multiple non-technical stakeholders through simple graphical outputs if there is a risk to planned production levels due to a logistics constraint
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
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
Model Diagnostics meets Forecast Evaluation: Goodness-of-Fit, Calibration, and Related Topics
Principled forecast evaluation and model diagnostics are vital in fitting probabilistic models and forecasting outcomes of interest. A common principle is that fitted or predicted distributions ought to be calibrated, ideally in the sense that the outcome is indistinguishable from a random draw from the posited distribution. Much of this thesis is centered on calibration properties of various types of forecasts.
In the first part of the thesis, a simple algorithm for exact multinomial goodness-of-fit tests is proposed. The algorithm computes exact -values based on various test statistics, such as the log-likelihood ratio and Pearson\u27s chi-square. A thorough analysis shows improvement on extant methods. However, the runtime of the algorithm grows exponentially in the number of categories and hence its use is limited.
In the second part, a framework rooted in probability theory is developed, which gives rise to hierarchies of calibration, and applies to both predictive distributions and stand-alone point forecasts. Based on a general notion of conditional T-calibration, the thesis introduces population versions of T-reliability diagrams and revisits a score decomposition into measures of miscalibration, discrimination, and uncertainty. Stable and efficient estimators of T-reliability diagrams and score components arise via nonparametric isotonic regression and the pool-adjacent-violators algorithm. For in-sample model diagnostics, a universal coefficient of determination is introduced that nests and reinterprets the classical in least squares regression.
In the third part, probabilistic top lists are proposed as a novel type of prediction in classification, which bridges the gap between single-class predictions and predictive distributions. The probabilistic top list functional is elicited by strictly consistent evaluation metrics, based on symmetric proper scoring rules, which admit comparison of various types of predictions
On the Mechanism of Building Core Competencies: a Study of Chinese Multinational Port Enterprises
This study aims to explore how Chinese multinational port enterprises (MNPEs) build
their core competencies. Core competencies are firms’special capabilities and sources
to gain sustainable competitive advantage (SCA) in marketplace, and the concept led
to extensive research and debates. However, few studies include inquiries about the
mechanisms of building core competencies in the context of Chinese MNPEs.
Accordingly, answers were sought to three research questions:
1. What are the core competencies of the Chinese MNPEs?
2. What are the mechanisms that the Chinese MNPEs use to build their core
competencies?
3. What are the paths that the Chinese MNPEs pursue to build their resources bases?
The study adopted a multiple-case study design, focusing on building mechanism of
core competencies with RBV. It selected purposively five Chinese leading MNPEs
and three industry associations as Case Companies.
The study revealed three main findings. First, it identified three generic core
competencies possessed by Case Companies, i.e., innovation in business models and
operations, utilisation of technologies, and acquisition of strategic resources. Second,
it developed the conceptual framework of the Mechanism of Building Core
Competencies (MBCC), which is a process of change of collective learning in
effective and efficient utilization of resources of a firm in response to critical events.
Third, it proposed three paths to build core competencies, i.e., enhancing collective
learning, selecting sustainable processes, and building resource base.
The study contributes to the knowledge of core competencies and RBV in three ways:
(1) presenting three generic core competencies of the Chinese MNPEs, (2) proposing
a new conceptual framework to explain how Chinese MNPEs build their core
competencies, (3) suggesting a solid anchor point (MBCC) to explain the links among
resources, core competencies, and SCA. The findings set benchmarks for Chinese
logistics industry and provide guidelines to build core competencies
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Antecedents of business intelligence system use
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.Organisational reliance on information has become vital for organisational competitiveness. With increasing data volumes, Business Intelligence (BI) becomes a cornerstone of the decision-support system. However, employee resistance to use Business Intelligence Systems (BIS) is evident. This creates a problem to organisations in realising the benefits of BIS. It is thus important to study the enablers of sustained use of BIS amongst employees.
This thesis identifies existing theories that can be used to study BI system use. It integrates and extends technology use theories through a framework focusing on Business Intelligence System Use (BISU). Empirical research is then conducted in Kuwait’s telecom and banking industries through a close-ended, self-administered questionnaire using a five-point Likert scale. Responses were received from 211 BI users. The data was analysed using SmartPLS to study the convergent and discriminant validity and reliability. Partial least squares structural equation modelling (PLS-SEM) was used to study the direct and indirect relationships between constructs and answer the hypotheses. In addition to SmartPLS, SPSS was used for descriptive analysis.
The results indicated that UTAUT factors consisting of performance expectancy, effort expectancy and social influence positively impact BI system use. Voluntariness of use was found to positively moderate the relationship between social influence and BI system use. Furthermore, BI system quality positively impacts both performance expectancy and effort expectancy. The BI user’s self-efficacy also positively impacts effort expectancy. In addition, social influence was found to be positively influenced by organisational factors, namely top management support and information culture.
The findings of this research contribute to literature by determining and quantifying the factors that influence BISU through the lens of employee perspectives. This thesis also explains how employees’ object-based beliefs about BI affect their behavioural beliefs, which in turn impact BISU. Limitations of this research include the omission of UTAUT’s facilitating conditions and the limited variance of respondent demographics
DIN Spec 91345 RAMI 4.0 compliant data pipelining: An approach to support data understanding and data acquisition in smart manufacturing environments
Today, data scientists in the manufacturing domain are confronted with a set of challenges associated to data acquisition as well as data processing including the extraction of valuable in-formation to support both, the work of the manufacturing equipment as well as the manufacturing processes behind it.
One essential aspect related to data acquisition is the pipelining, including various commu-nication standards, protocols and technologies to save and transfer heterogenous data. These circumstances make it hard to understand, find, access and extract data from the sources depend-ing on use cases and applications.
In order to support this data pipelining process, this thesis proposes the use of the semantic model. The selected semantic model should be able to describe smart manufacturing assets them-selves as well as to access their data along their life-cycle.
As a matter of fact, there are many research contributions in smart manufacturing, which already came out with reference architectures or standards for semantic-based meta data descrip-tion or asset classification. This research builds upon these outcomes and introduces a novel se-mantic model-based data pipelining approach using as a basis the Reference Architecture Model for Industry 4.0 (RAMI 4.0).Hoje em dia, os cientistas de dados no domĂnio da manufatura sĂŁo confrontados com várias normas, protocolos e tecnologias de comunicação para gravar, processar e transferir vários tipos de dados. Estas circunstâncias tornam difĂcil compreender, encontrar, aceder e extrair dados necessários para aplicações dependentes de casos de utilização, desde os equipamentos aos respectivos processos de manufatura.
Um aspecto essencial poderia ser um processo de canalisação de dados incluindo vários normas de comunicação, protocolos e tecnologias para gravar e transferir dados. Uma solução para suporte deste processo, proposto por esta tese, é a aplicação de um modelo semântico que descreva os próprios recursos de manufactura inteligente e o acesso aos seus dados ao longo do seu ciclo de vida.
Muitas das contribuições de investigação em manufatura inteligente já produziram arquitecturas de referĂŞncia como a RAMI 4.0 ou normas para a descrição semântica de meta dados ou classificação de recursos. Esta investigação baseia-se nestas fontes externas e introduz um novo modelo semântico baseado no Modelo de Arquitectura de ReferĂŞncia para IndĂşstria 4.0 (RAMI 4.0), em conformidade com a abordagem de canalisação de dados no domĂnio da produção inteligente como caso exemplar de utilização para permitir uma fácil exploração, compreensĂŁo, descoberta, selecção e extracção de dados
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