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The impact of employees' working relations in creating and retaining trust: the case of the Bahrain Olympic Committee
Introduction: This thesis investigates the impact of employeesâ working relations in creating, maintaining and retaining trust in the Bahrain Olympic Committee (BOC).
Aim: The main aim of this thesis is to determine how the three groups of Organisational Trust variables, namely Social System Elements (SSE), Factors of Trustworthiness (FoT) and Third-Party Gossip (TPG), affect employeesâ Organisational Trust (OTR) in the BOC and promote Organisational Citizenship Behaviour (OCB). To answer this main aim, a conceptual framework was created that focused on exploring the following research aims: (1) the interrelationship between SSE and FoT, (2) the effect of SSE on OTR, (3) the impact of TPG on OTR and (4) the effect of OTR on overall OCB.
Methodology: The study uses a mixed-method case study research style that included in-depth semi-structured interviews with 17 managers, an online questionnaire survey with 320 employees of the BOC and an analysis of the BOCâs Annual Reports from 2015 to 2018.
Results: The qualitative and quantitative findings indicate, firstly, that there is a significant interrelationship between SSE and FoT, establishing that SSEâs perception of organisational justice (OJ), including that FoTs benevolence and integrity as the most important factors in yielding employeesâ trust in the BOC. Secondly, it has been established that SSEs have significant direct and indirect effects on OTR. Thirdly, negative and positive TPG concurrently occurred in the BOC and the prevalence of negative TPG poses more impact on OTR. Finally, this studyâs findings demonstrated OTRâs effect in generating OCB, including that Civic Virtue was rated as the most preferred of the five OCB themes; this indicates the managersâ and the employeesâ strong emotional attachment and support of the activities taking place at the BOC.
Contributions: Overall, this thesis substantially contributes to OTR literature, particularly in the context of the Middle East. It also proposes several insightful recommendations for future research and practical implications for practitioners in the field of Organisational Trust
Comparative Multiple Case Study into the Teaching of Problem-Solving Competence in Lebanese Middle Schools
This multiple case study investigates how problem-solving competence is integrated into teaching practices in private schools in Lebanon. Its purpose is to compare instructional approaches to problem-solving across three different programs: the American (Common Core State Standards and New Generation Science Standards), French (Socle Commun de Connaissances, de Compétences et de Culture), and Lebanese with a focus on middle school (grades 7, 8, and 9). The project was conducted in nine schools equally distributed among three categories based on the programs they offered: category 1 schools offered the Lebanese program, category 2 the French and Lebanese programs, and category 3 the American and Lebanese programs. Each school was treated as a separate case.
Structured observation data were collected using observation logs that focused on lesson objectives and specific cognitive problem-solving processes. The two logs were created based on a document review of the requirements for the three programs. Structured observations were followed by semi-structured interviews that were conducted to explore teachers' beliefs and understandings of problem-solving competence. The comparative analysis of within-category structured observations revealed an instruction ranging from teacher-led practices, particularly in category 1 schools, to more student-centered approaches in categories 2 and 3. The cross-category analysis showed a reliance on cognitive processes primarily promoting exploration, understanding, and demonstrating understanding, with less emphasis on planning and executing, monitoring and reflecting, thus uncovering a weakness in addressing these processes. The findings of the post-observation semi-structured interviews disclosed a range of definitions of problem-solving competence prevalent amongst teachers with clear divergences across the three school categories.
This research is unique in that it compares problem-solving teaching approaches across three different programs and explores underlying teachers' beliefs and understandings of problem-solving competence in the Lebanese context. It is hoped that this project will inform curriculum developers about future directions and much-anticipated reforms of the Lebanese program and practitioners about areas that need to be addressed to further improve the teaching of problem-solving competence
Facilitating prosociality through technology: Design to promote digital volunteerism
Volunteerism covers many activities involving no financial rewards for volunteers but which contribute
to the common good. There is existing work in designing technology for volunteerism in HumanComputer Interaction (HCI) and related disciplines that focuses on motivation to improve
performance, but it does not account for volunteer wellbeing. Here, I investigate digital volunteerism
in three case studies with a focus on volunteer motivation, engagement, and wellbeing. My research
involved volunteers and others in the volunteering context to generate recommendations for a
volunteer-centric design for digital volunteerism. The thesis has three aims:
1. To investigate motivational aspects critical for enhancing digital volunteersâ experiences
2. To identify digital platform attributes linked to volunteer wellbeing
3. To create guidelines for effectively supporting volunteer engagement in digital volunteering
platforms
In the first case study I investigate the design of a chat widget for volunteers working in an
organisation with a view to develop a design that improves their workflow and wellbeing. The second
case study investigates the needs, motivations, and wellbeing of volunteers who help medical
students improve their medical communication skills. An initial mixed-methods study was followed by
an experiment comparing two design strategies to improve volunteer relatedness; an important
indicator of wellbeing. The third case study looks into volunteer needs, experiences, motivations, and
wellbeing with a focus on volunteer identity and meaning-making on a science-based research
platform. I then analyse my findings from these case studies using the lens of care ethics to derive
critical insights for design.
The key contributions of this thesis are design strategies and critical insights, and a volunteer-centric
design framework to enhance the motivation, wellbeing and engagement of digital volunteers
Knowledge Graph Building Blocks: An easy-to-use Framework for developing FAIREr Knowledge Graphs
Knowledge graphs and ontologies provide promising technical solutions for
implementing the FAIR Principles for Findable, Accessible, Interoperable, and
Reusable data and metadata. However, they also come with their own challenges.
Nine such challenges are discussed and associated with the criterion of
cognitive interoperability and specific FAIREr principles (FAIR + Explorability
raised) that they fail to meet. We introduce an easy-to-use, open source
knowledge graph framework that is based on knowledge graph building blocks
(KGBBs). KGBBs are small information modules for knowledge-processing, each
based on a specific type of semantic unit. By interrelating several KGBBs, one
can specify a KGBB-driven FAIREr knowledge graph. Besides implementing semantic
units, the KGBB Framework clearly distinguishes and decouples an internal
in-memory data model from data storage, data display, and data access/export
models. We argue that this decoupling is essential for solving many problems of
knowledge management systems. We discuss the architecture of the KGBB Framework
as we envision it, comprising (i) an openly accessible KGBB-Repository for
different types of KGBBs, (ii) a KGBB-Engine for managing and operating FAIREr
knowledge graphs (including automatic provenance tracking, editing changelog,
and versioning of semantic units); (iii) a repository for KGBB-Functions; (iv)
a low-code KGBB-Editor with which domain experts can create new KGBBs and
specify their own FAIREr knowledge graph without having to think about semantic
modelling. We conclude with discussing the nine challenges and how the KGBB
Framework provides solutions for the issues they raise. While most of what we
discuss here is entirely conceptual, we can point to two prototypes that
demonstrate the principle feasibility of using semantic units and KGBBs to
manage and structure knowledge graphs
Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse
This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses.
This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups.
In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in usersâ speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018â6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena
One-sided differentiability: a challenge for computer algebra systems
Computer Algebra Systems (CASs) are extremely powerful and widely used digital tools. Focusing on differentiation, CASs include a command that computes the derivative of functions in one variable (and also the partial derivative of functions in several variables). We will focus in this article on real-valued functions of one real variable. Since CASs usually compute the derivative of real-valued functions as a whole, the value of the computed derivative at points where the left derivative and the right derivative are different (that we will call conflicting points) should be something like "undefined", although this isn't always the case: the output could strongly differ depending on the chosen CAS. We have analysed and compared in this article how some well-known CASs behave when addressing differentiation at the conflicting points of five different functions chosen by the authors. Finally, the ability for calculating one-sided limits of CASs allows to directly compute the result in these cumbersome cases using the formal definition of one-sided derivative, which we have also analysed and compared for the selected CASs. Regarding teaching, this is an important issue, as it is a topic of Secondary Education and nowadays the use of CASs as an auxiliary digital tool for teaching mathematics is very common
Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective
This paper introduces a comprehensive, multi-stage machine learning
methodology that effectively integrates information systems and artificial
intelligence to enhance decision-making processes within the domain of
operations research. The proposed framework adeptly addresses common
limitations of existing solutions, such as the neglect of data-driven
estimation for vital production parameters, exclusive generation of point
forecasts without considering model uncertainty, and lacking explanations
regarding the sources of such uncertainty. Our approach employs Quantile
Regression Forests for generating interval predictions, alongside both local
and global variants of SHapley Additive Explanations for the examined
predictive process monitoring problem. The practical applicability of the
proposed methodology is substantiated through a real-world production planning
case study, emphasizing the potential of prescriptive analytics in refining
decision-making procedures. This paper accentuates the imperative of addressing
these challenges to fully harness the extensive and rich data resources
accessible for well-informed decision-making
Beyond invisibility: The position and role of the literary translator in the digital paratextual space
This thesis presents a new theoretical framework through which to analyse the visibility of literary translators in the digital materials that present translations to readers, referred to throughout as paratextual spaces. Central to this model is the argument that paratextual âvisibilityâ must be understood as including both the way translators and their labour are presented to readers, defined here as their position, and also their role in the establishment of that position. Going beyond Lawrence Venutiâs concept of invisibility as an inevitably negative position to be fought against, this thesis instead establishes paratextual visibility as a complex negotiation between the agency of individual translators, the needs of a publishing house and the interests of readers.
The value of this approach is demonstrated through a case study examining the visibility of translator Jamie Bulloch in the digital spaces surrounding his English-language translations of two novels by German author Timur Vermes: Look Whoâs Back and The Hungry and the Fat. This analysis finds that even though Bulloch played an early role in creating the publisherâs paratextual materials, publisher MacLehose Press prioritised making the novelsâ German origins and the foreignness of the texts visible over Bullochâs status as the translator, or his translatorship. Bullochâs limited visibility in the publisher-created materials was then reproduced in digital paratexts created by readers and third parties such as retailer Amazon, despite his attempts to interact with readers and perform his translatorship in digital spaces such as Twitter. Rather than challenging Bullochâs limited visibility, then, digital spaces served to amplify it. This thesis therefore finds that the translatorâs active participation in the promotion of their work does not always equate to increased visibility, thus demonstrating the need to go beyond Venutiâs invisibility and towards understanding the multifaceted roles played by translators in presenting literary texts to new audiences
Technologies and Applications for Big Data Value
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part âTechnologies and Methodsâ contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part âProcesses and Applicationsâ details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems
Methodological document on statistical use of economic administrative records
This methodological document is intended to furnish the countries of the region with a set of guidelines and recommendations for producing innovative and timely economic statistics, and to provide greater benefits by making statistical use of administrative records on economic issues
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