Increasing homeowners’ insulation activity in Germany - A theoretically and empirically grounded agent-based model analysis

How is it possible to increase homeowners’ insulation activity? Answering this question is key to successful policies regarding energy-efficient buildings worldwide. In Germany, doubling today’s insulation rate of about 1% is an important element for reaching the government’s target of an 80% reduction in energy demand in the building sector by 2050. This thesis uses an agent-based model analysis to improve the understanding of homeowners’ insulation activity and to explore new approaches aiming at its increase in Germany. Two agent-based models were developed and utilized. The first model was developed mainly based on insights derived from a structured literature review. The second emerged from the previous one, incorporating the results of an online survey conducted among 275 homeowners. The results indicate that homeowners’ economic means have little influence on their decision to install insulation. Instead, their insulation decision-making is mostly affected by situational factors and their attitudes towards insulation. Situational factors, such as the condition of the building, are important because they initiate homeowners’ individual decision-making processes on insulation. The simulation results show that improving homeowners’ attitudes about insulation by providing information has a comparatively low potential for increasing their insulation activity. Out of the policy options this thesis explored, the introduction of an obligation to insulate the walls within one year after change of house ownership was found to have the greatest impact on homeowners’ insulation activity. The research has been published in the scope of three peer-reviewed articles: Friege, Jonas, and Emile J. L. Chappin. “Modelling decisions on energy-efficient renovations: a review.” Renewable and Sustainable Energy Reviews 39 (2014): 196-208. Friege, Jonas, Georg Holtz, and Emile J. L. Chappin. “Exploring Homeowners’ Insulation Activity.” Journal of Artificial Societies & Social Simulation 19.1 (2016). Friege, Jonas. “Increasing homeowners’ insulation activity in Germany: An empirically grounded agent-based model analysis.” Energy and Buildings 128 (2016): 756-771. 2 MODELING DECISIONS ON ENERGY-EFFICIENT RENOVATIONS Originally published as: Friege, J. and Chappin, E., 2014. Modelling decisions on energy-efficient renovations: a review. Renewable and Sustainable Energy Reviews, 39, pp.196-208. 3 EXPLORING HOMEOWNERS’ INSULATION ACTIVITY Originally published as: Friege, J., Holtz, G. and Chappin, E.J., 2016. Exploring Homeowners' Insulation Activity. Journal of Artificial Societies & Social Simulation, 19(1). 4 INCREASING HOMEOWNERS’ INSULATION ACTIVITY IN GERMANY Originally published as: Friege, J., 2016. Increasing homeowners’ insulation activity in Germany – An empirically grounded agent-based model analysis. Journal Energy and Buildings, 128, 756–771.</p

Semi-automated co-reference identification in digital humanities collections

Locating specific information within museum collections represents a significant challenge for collection users. Even when the collections and catalogues exist in a searchable digital format, formatting differences and the imprecise nature of the information to be searched mean that information can be recorded in a large number of different ways. This variation exists not just between different collections, but also within individual ones. This means that traditional information retrieval techniques are badly suited to the challenges of locating particular information in digital humanities collections and searching, therefore, takes an excessive amount of time and resources. This thesis focuses on a particular search problem, that of co-reference identification. This is the process of identifying when the same real world item is recorded in multiple digital locations. In this thesis, a real world example of a co-reference identification problem for digital humanities collections is identified and explored. In particular the time consuming nature of identifying co-referent records. In order to address the identified problem, this thesis presents a novel method for co-reference identification between digitised records in humanities collections. Whilst the specific focus of this thesis is co-reference identification, elements of the method described also have applications for general information retrieval. The new co-reference method uses elements from a broad range of areas including; query expansion, co-reference identification, short text semantic similarity and fuzzy logic. The new method was tested against real world collections information, the results of which suggest that, in terms of the quality of the co-referent matches found, the new co-reference identification method is at least as effective as a manual search. The number of co-referent matches found however, is higher using the new method. The approach presented here is capable of searching collections stored using differing metadata schemas. More significantly, the approach is capable of identifying potential co-reference matches despite the highly heterogeneous and syntax independent nature of the Gallery, Library Archive and Museum (GLAM) search space and the photo-history domain in particular. The most significant benefit of the new method is, however, that it requires comparatively little manual intervention. A co-reference search using it has, therefore, significantly lower person hour requirements than a manually conducted search. In addition to the overall co-reference identification method, this thesis also presents: • A novel and computationally lightweight short text semantic similarity metric. This new metric has a significantly higher throughput than the current prominent techniques but a negligible drop in accuracy. • A novel method for comparing photographic processes in the presence of variable terminology and inaccurate field information. This is the first computational approach to do so.AHR

Blockchain Technology and Operations Management: An Implementation Roadmap

Blockchain is a form of distributed ledger technology. While it has grown in prominence, its full potential and possible downsides are not fully understood yet, especially with respect to Operations Management (OM). This thesis aims to provide a bibliometric literature review through which the current literature is studied and analyzed. In this regard, four main clusters have been identified: (1) Blockchain and Supply Chain Management, (2) Blockchain Technology Adoption in Supply Chain Management, (3) Blockchain and Sustainability, and (4) Blockchain Application in Food Supply Chain (FSC). As a result of this bibliometric literature review, some consistent gaps in the literature have been identified. Specifically, we have found that most of these recent studies focus their attention only on the possible benefits and risks of Blockchain implementation in the specific area of Supply Chain Management. Additionally, it is not clear how an enterprise should practically approach and transform its operations to implement Blockchain Technology. Hence, to fill these gaps, a case study has been conducted with a specific focus on the road mapping of the main steps and initiatives an organization should undertake when starting a Blockchain transformation journey as well as on its impacts inside the general company’s operations.Blockchain is a form of distributed ledger technology. While it has grown in prominence, its full potential and possible downsides are not fully understood yet, especially with respect to Operations Management (OM). This thesis aims to provide a bibliometric literature review through which the current literature is studied and analyzed. In this regard, four main clusters have been identified: (1) Blockchain and Supply Chain Management, (2) Blockchain Technology Adoption in Supply Chain Management, (3) Blockchain and Sustainability, and (4) Blockchain Application in Food Supply Chain (FSC). As a result of this bibliometric literature review, some consistent gaps in the literature have been identified. Specifically, we have found that most of these recent studies focus their attention only on the possible benefits and risks of Blockchain implementation in the specific area of Supply Chain Management. Additionally, it is not clear how an enterprise should practically approach and transform its operations to implement Blockchain Technology. Hence, to fill these gaps, a case study has been conducted with a specific focus on the road mapping of the main steps and initiatives an organization should undertake when starting a Blockchain transformation journey as well as on its impacts inside the general company’s operations

A framework for technology-assisted sensitivity review: using sensitivity classification to prioritise documents for review

More than a hundred countries implement freedom of information laws. In the UK, the Freedom of Information Act 2000 (FOIA) states that the government's documents must be made freely available, or opened, to the public. Moreover, all central UK government departments' documents that have a historic value, for example the minutes from significant meetings, must be transferred to the The National Archives (TNA) within twenty years of the document's creation. However, government documents can contain sensitive information, such as personal information or information that would likely damage the international relations of the UK if it was opened to the public. Therefore, all government documents that are to be publicly archived must be sensitivity reviewed to identify and redact the sensitive information, or close the document until the information is no longer sensitive. Historically, government documents have been stored in a structured file-plan that can reliably inform a sensitivity reviewer about the subject-matter and the likely sensitivities in the documents. However, the lack of structure in digital document collections and the volume of digital documents that are to be sensitivity reviewed mean that the traditional manual sensitivity review process is not practical for digital sensitivity review. In this thesis, we argue that the automatic classification of documents that contain sensitive information, sensitivity classification, can be deployed to assist government departments and human reviewers to sensitivity review born-digital government documents. However, classifying sensitive information is a complex task, since sensitivity is context-dependent. For example, identifying if information is sensitive or not can require a human to judge on the likely effect of releasing the information into the public domain. Moreover, sensitivity is not necessarily topic-oriented, i.e., it is usually dependent on a combination of what is being said and about whom. Furthermore, the vocabulary and entities that are associated to particular types of sensitive information, e.g., confidential information, can vary greatly between different collections. We propose to address sensitivity classification as a text classification task. Moreover, through a thorough empirical evaluation, we show that text classification is effective for sensitivity classification and can be improved by identifying the vocabulary, syntactic and semantic document features that are reliable indicators of sensitive or non-sensitive text. Furthermore, we propose to reduce the number of documents that have to be reviewed to learn an effective sensitivity classifier through an active learning strategy in which a sensitivity reviewer redacts any sensitive text in a document as they review it, to construct a representation of the sensitivities in a collection. With this in mind, we propose a novel framework for technology-assisted sensitivity review that can prioritise the most appropriate documents to be reviewed at specific stages of the review process. Furthermore, our framework can provide the reviewers with useful information to assist them in making their reviewing decisions. Our framework consists of four components, namely the Document Representation, Document Prioritisation, Feedback Integration and Learned Predictions components, that can be instantiated to learn from the reviewers' feedback about the sensitivities in a collection or provide assistance to reviewers at different stages of the review. In particular, firstly, the Document Representation component encodes the document features that can be reliable indicators of the sensitivities in a collection. Secondly, the Document Prioritisation component identifies the documents that should be prioritised for review at a particular stage of the reviewing process, for example to provide the sensitivity classifier with information about the sensitivities in the collection or to focus the available reviewing resources on the documents that are the most likely to be released to the public. Thirdly, the Feedback Integration component integrates explicit feedback from a reviewer to construct a representation of the sensitivities in a collection and identify the features of a reviewer's interactions with the framework that indicate the amount of time that is required to sensitivity review a specific document. Finally, the Learned Predictions component combines the information that has been generated by the other three components and, as the final step in each iteration of the sensitivity review process, the Learned Predictions component is responsible for making accurate sensitivity classification and expected reviewing time predictions for the documents that have not yet been sensitivity reviewed. In this thesis, we identify two realistic digital sensitivity review scenarios as user models and conduct two user studies to evaluate the effectiveness of our proposed framework for assisting digital sensitivity review. Firstly, in the limited review user model, which addresses a scenario in which there are insufficient reviewing resources available to sensitivity review all of the documents in a collection, we show that our proposed framework can increase the number of documents that can be reviewed and released to the public with the available reviewing resources. Secondly, in the exhaustive review user model, which addresses a scenario in which all of the documents in a collection will be manually sensitivity reviewed, we show that providing the reviewers with useful information about the documents in the collection that contain sensitive information can increase the reviewers' accuracy, reviewing speed and agreement. This is the first thesis to investigate automatically classifying FOIA sensitive information to assist digital sensitivity review. The central contributions of this thesis are our proposed framework for technology-assisted sensitivity review and our sensitivity classification approaches. Our contributions are validated using a collection of government documents that are sensitivity reviewed by expert sensitivity reviewers to identify two FOIA sensitivities, namely international relations and personal information. The thesis draws insights from a thorough evaluation and analysis of our proposed framework and sensitivity classifier. Our results demonstrate that our proposed framework is a viable technology for assisting digital sensitivity review

Research and development in science and technology in GCC countries: role of information centres and libraries

This research study identifies the role of library and information centres at the major science and technology related universities and research institutes in the six GeC countries i.e. Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates, in relation to the institutes/organisations research and development activities. It also had a comparative aspect in that it examined information resources and information services available in the institutes/organisations under study with users perceptions on the effectiveness and efficiency of library and information services. A survey research design utilizing questionnaires was chosen as the most appropriate and effective method for gathering the data needed with intensive interviews with academe, Deans/Directors of Library Information Centres and R&D personnel to answer the study's research questions. The different populations were queried including the Chief Executives of institutes/organisations, Deans/Directors of Library and Information Centres and selected R&D personnel associated with them. It was found that in spite of large library collections and a number of de-centralised library systems in all the universities, information services available to the R&D personnel were inadequate. The fmdings of this investigation provided the means for the development of the proposed regional and national library/information network systems for successful library and information services model presented in this study. As an alternative a GeC infonnation subsystem GCC-SIST has been recommended along with emphasis on an electronic information system