Usability Evaluation of an Open Data Platform

Despite the rapid proliferation of open data platforms, the accessibility and ease of use of data portals is low. This factor prevents citizens and civil society organizations from exploiting open data for their goals. The poor usability of current generation of open data platforms could be attributed to the fact that these platforms were not designed for non-technical users. They are typically software products developed “by programmers for programmers or technical users”. Consequently, while reports about innovative use of open data by software developers and start-ups are common, there are very few reports about successful public use of open data to tackle concrete societal challenges. This paper provides the results and lessons learnt from the usability evaluation of the second alpha release of a next generation open data platform designed explicitly to support non-technical users. A scenario involving a transportation challenge in Dublin City was employed as the context for the evaluation of the platform. Findings provide some empirical basis for identifying important user interface design considerations, patterns for highly usable open data platforms and considerations for open data policy

Towards a circular maritime industry : identifying strategy and technology solutions

Shipping is considered one of the most energy-efficient modes, considering the amount of cargo that can be carried. On the other hand, the circular economy approach is not well-established in the maritime industry, which currently lags behind different transport modes. The maritime industry needs scientific support to “close the loop”, minimise waste and increase the revenue stream. Therefore, this study aims to address a critical gap in the maritime industry by first showing the understanding of the stakeholders and identifying suitable strategy and technology solutions that can fit the characteristics of the maritime industry. Moreover, the potential benefits of these solutions have been demonstrated through high-speed marine engine remanufacturing. A cost-benefit analysis has shown that remanufactured engine acquisition cost is nearly half of the cost of a new engine with similar operating performance and operating cost. This study is a novel contribution to maritime industry stakeholders to demonstrate the advantages of circular end-of-life applications

Application of reinforcement learning in robotic disassembly operations

Disassembly is a key step in remanufacturing. To increase the level of automation in disassembly, it is necessary to use robots that can learn to perform new tasks by themselves rather than having to be manually reprogrammed every time there is a different job. Reinforcement Learning (RL) is a machine learning technique that enables the robots to learn by trial and error rather than being explicitly programmed. In this thesis, the application of RL to robotic disassembly operations has been studied. Firstly, a literature review on robotic disassembly and the application of RL in contact-rich tasks has been conducted in Chapter 2. To physically implement RL in robotic disassembly, the task of removing a bolt from a door chain lock has been selected as a case study, and a robotic training platform has been built for this implementation in Chapter 3. This task is chosen because it can demonstrate the capabilities of RL to pathfinding and dealing with reaction forces without explicitly specifying the target coordinates or building a force feedback controller. The robustness of the learned policies against the imprecision of the robot is studied by a proposed method to actively lower the precision of the robots. It has been found that the robot can learn successfully even when the precision is lowered to as low as ±0.5mm. This work also investigates whether learned policies can be transferred among robots with different precisions. Experiments have been performed by training a robot with a certain precision on a task and replaying the learned skills on a robot with different precision. It has been found that skills learned by a low-precision robot can perform better on a robot with higher precision, and skills learned by a high-precision robot have worse performance on robots with lower precision, as it is suspected that the policies trained on high-precision robots have been overfitted to the precise robots. In Chapter 4, the approach of using a digital-twin-assisted simulation-to-reality transfer to accelerate the learning performance of the RL has been investigated. To address the issue of identifying the system parameters, such as the stiffness and damping of the contact models, that are difficult to measure directly but are critical for building the digital twins of the environments, system identification method is used to minimise the discrepancy between the response generated from the physical and digital environments by using the Bees Algorithm. It is found that the proposed method effectively increases RL's learning performance. It is also found that it is possible to have worse performance with the sim-to-real transfer if the reality gap is not effectively addressed. However, increasing the size of the dataset and optimisation cycles have been demonstrated to reduce the reality gap and lead to successful sim-to-real transfers. Based on the training task described in Chapters 4 and 5, a full factorial study has been conducted to identify patterns when selecting the appropriate hyper-parameters when applying the Deep Deterministic Policy Gradient (DDPG) algorithm to the robotic disassembly task. Four hyper-parameters that directly influence the decision-making Artificial Neural Network (ANN) update have been chosen for the study, with three levels assigned to each hyper-parameter. After running 241 simulations, it is found that for this particular task, the learning rates of the actor and critic networks are the most influential hyper-parameters, while the batch size and soft update rate have relatively limited influence. Finally, the thesis is concluded in Chapter 6 with a summary of findings and suggested future research directions

Evolutionary Service Composition and Personalization Ecosystem for Elderly Care

Current demographic trends suggest that people are living longer, while the ageing process entails many necessities, calling for care services tailored to the individual senior’s needs and life style. Personalized provision of care services usually involves a number of stakeholders, including relatives, friends, caregivers, professional assistance organizations, enterprises, and other support entities. Traditional Information and Communication Technology based care and assistance services for the elderly have been mainly focused on the development of isolated and generic services, considering a single service provider, and excessively featuring a techno-centric approach. In contrast, advances on collaborative networks for elderly care suggest the integration of services from multiple providers, encouraging collaboration as a way to provide better personalized services. This approach requires a support system to manage the personalization process and allow ranking the {service, provider} pairs. An additional issue is the problem of service evolution, as individual’s care needs are not static over time. Consequently, the care services need to evolve accordingly to keep the elderly’s requirements satisfied. In accordance with these requirements, an Elderly Care Ecosystem (ECE) framework, a Service Composition and Personalization Environment (SCoPE), and a Service Evolution Environment (SEvol) are proposed. The ECE framework provides the context for the personalization and evolution methods. The SCoPE method is based on the match between the customer´s profile and the available {service, provider} pairs to identify suitable services and corresponding providers to attend the needs. SEvol is a method to build an adaptive and evolutionary system based on the MAPE-K methodology supporting the solution evolution to cope with the elderly's new life stages. To demonstrate the feasibility, utility and applicability of SCoPE and SEvol, a number of methods and algorithms are presented, and illustrative scenarios are introduced in which {service, provider} pairs are ranked based on a multidimensional assessment method. Composition strategies are based on customer’s profile and requirements, and the evolutionary solution is determined considering customer’s inputs and evolution plans. For the ECE evaluation process the following steps are adopted: (i) feature selection and software prototype development; (ii) detailing the ECE framework validation based on applicability and utility parameters; (iii) development of a case study illustrating a typical scenario involving an elderly and her care needs; and (iv) performing a survey based on a modified version of the technology acceptance model (TAM), considering three contexts: Technological, Organizational and Collaborative environment

Aligning business processes and IT of multiple collaborating organisations

When multiple organisations want to collaborate with one another they have to integrate their business processes. This requires aligning the collaborative business processes and the underlying IT (Information Technology). Realizing the required alignment is, however, not trivial and is the subject of this thesis. We approached the issue of alignment in three steps. First, we explored business-IT alignment problems in detail in a real-life business case. This is done in order to clarify what alignment of business processes and IT systems across a collaboration network entails. Second, we provided a business-IT alignment framework called BITA* (pronounce bita-star). The framework provides modelling abstractions for alignment. Third, we applied the framework in two real-life case studies, including the real-life business case used in step one. By applying the framework in practice we showed that the framework can, in fact, help to address the business-IT alignment problems that we identified in the first step. The work presented in this thesis is conducted over a number of years in the context of four large EU sponsored research projects. The projects focused on alignment problems in two very distinct application areas. Two projects were about realizing transparency systems for meat supply chains and constitute the first case study. The other two projects were about realizing multidisciplinary modelling collaboration systems and constitute the second case study. Although the projects were conducted sequentially the research questions were addressed iteratively over the years. The research methodology that shows how the framework is designed and how the case studies are applied is discussed in detail in chapter 2. In chapter 3 we present BITA*, a Business-IT Alignment framework for multiple collaborating organisations. The main challenges in designing BITA* have been what models to consider for alignment and how to compare them in order to make explicit statements about alignment. We addressed this problem by introducing allocation and alignment modelling constructs to help the alignment process, and the concept of business collaboration model to represent the models that have to be aligned. We identified three groups of stakeholders for whom we designed explicit design viewpoints and associated allocation and alignment models. The Business Process to Business Process (BP2BP) alignment viewpoint is designed for business analysts who have to align diverse business collaboration process models. The IT to IT (IT2IT) alignment viewpoint is designed for software architects to align the distribution of data and IT systems across a collaboration network. The Business Process to IT (BP2IT) alignment viewpoint is designed for an interdisciplinary team of business analysts and software architects who have to align the different ways of supporting business collaboration processes with distributed IT system. An essential element of this thesis has been elaborating how business-IT alignment problems occur in the context of multi-organisational collaboration. The case studies were used to demonstrate business-IT alignment concerns. Particularly, the details of the first case study presented in chapters 4 and 5 were used in chapter 3 to help derive the alignment framework. The case study presented an ideal problem scenario since realizing transparency across supply chains is intrinsically a collaborative effort. The second case study was used to enhance the validity of our approach. The results of the second case study are presented in chapter 6. The alignment framework was designed during the iterative process we followed when realizing a generic transparency system for meat supply chains. To realize the required generic transparency system we needed a reference architecture. To derive the reference architecture we adapted an already existing and broadly-accepted generic reference architecture. We have to adapt the generic reference architecture in order to address specific requirements of the meat sector that were not considered in the generic reference architecture. The adaptation process made it clear that we needed models for representing business collaborations. We, therefore, introduced the notion of business collaboration model, which we used both to model reference architectures and to adapt them. Adaptation required aligning the generic reference architecture with the diverse business collaboration models adopted by the organisations that have to collaborate. The alignment framework is thus used for adapting a generic reference architecture in order to create a reference architecture that the collaborating organisations can, and are willing to, adopt. We identified three types of business collaboration models: business collaboration process model, business collaboration IT model, and a model for representing the relationship between these two. A business collaboration process model is a business process model that spans a collaboration network. A business collaboration IT model is a model of the distribution of the IT across the collaboration network. A business collaboration process-IT model is a model of the relationships between the elements of the business collaboration processes and the elements of the distributed IT. Each organisation is considered to adopt its own business collaboration models. For instance, different actors in meat supply chains have different views on how chain-wide transparency should be realized. Which business processes and IT systems each organisation has to deploy and use depends on the business collaboration models each food operator adopts. If two different food operators adopt the same set of business collaboration models, they are aligned; otherwise they are misaligned. Hence, alignment entails comparing the different business collaboration models adopted by the participating organisations. The results of the alignment process are explicit statements about how convergent or divergent the organisations are from the chosen generic reference architecture. The explicit statements of alignment guide how best the generic and the corresponding organisational business collaboration models can be adapted to create a better state of alignment. To further enhance the validity of the overall approach the second case study was conducted. The second case study was a retrospective investigation of two past research projects focusing on aligning environmental modelling processes and IT systems. A retrospective case study was chosen because launching a new business-IT alignment project involving multiple collaborating organisations was not feasible. The projects were undertaken to support the European Water Framework Directive, which mandated, among other things, participatory, multidisciplinary, river-basin wide and model-based studies to manage the water resources of Europe. The directive particularly required a collaborative approach to building environmental decision support systems and to deriving methodologies for applying existing decision support systems. We applied BITA* to aligning environmental modelling processes and IT systems in order to evaluate the suitability of the framework to addressing alignment problems in other application areas. The contributions of the thesis are summarized in chapter 7. The contributions include a number of design artefacts, which can be grouped into four categories: constructs, models, methods, and instantiations. The contribution in the first category includes the conceptualization of allocation and alignment. The contributions in the second category include allocation and alignment models, and reference architectures. Allocation models are representations of business collaboration models in a form that can be compared and are the basis for alignment modelling. The main contribution in the third category is the BITA* systematic approach to alignment modelling. The contributions in the fourth category are the software systems developed with the help of the reference architectures.</p

Strategic Assortment Decisions in Omnichannel Retailing: The Design and Evaluation of an Omnichannel Assortment Ontology for Consumer Confusion.

Consumer confusion is a phenomenon observed in retail settings where consumers feel irritation or frustration during the shopping journey. Consumers can be overwhelmed by assortment size, complex product variety, brand similarities, information inconsistencies or by intense stimuli from store atmospherics inducing information overload, leading to adverse reactions. Oftentimes, these experiences result in various negative short- and long-term consequences such as helplessness, purchase abandonment, dissatisfaction, or loss of trust or loyalty, thus representing a crucial challenge for retailers to prevent or mitigate. Consumer confusion has been studied extensively in a single-channel context, for instance, by investigating information overload phenomena in online shopping situations or examining increased choice sets resulting from large assortment sizes in physical stores. However, although omnichannel retailing has become the current state-of-the-art in the retail industry today, consumer confusion research from an omnichannel perspective is still very scarce. With the increased adoption of the omnichannel strategy by retailers that allow free switching behaviour for their customers during their shopping journeys, a new dimension to the consumer confusion phenomenon is observed. Customers are not only exposed to potential confusion at a specific retail situation in a single channel but are now confronted with potential new negative experiences while comparing products, prices, or information across channels. Particularly, when confronted with assortment inconsistencies across channels while switching channels, customers can experience irritation, frustration, or annoyance if the desired item is not to be found on the other channel, leading to adverse reactions that can potentially impact the retailer's financial performance. Prior literature has considered consumer confusion induced by assortment size, variety, or layout, but neglected its occurrence from assortment inconsistencies across channels from a channel switching perspective so far. This thesis focuses on the consumer confusion phenomenon resulting from assortment inconsistencies across channels from a channel-switching perspective in omnichannel retailing. Strategic assortment decisions in omnichannel retailing involve the coordination of the assortment between channels. Retailers can decide to realise a “Full”, “Asymmetric”, or “No Integration” approach for their assortment across channels. These strategic assortment decisions are taken at the Marketing-Operations-Interface (MOI), an interface harmonizing oftentimes conflicting relationships between objectives of the marketing and operations functions of the retailer. Although identical assortment across channels seems to be the desired solution to prevent consumer confusion (representing an objective from the marketing function), retailers oftentimes apply partial integration to benefit from channel-specific advantages such as the Long Tail effect (representing an objective from the operations function) which is detrimental to consumer confusion prevention. Retailers seem to neglect the significance of consumer confusion while making strategic assortment decisions at the MOI indicating that the phenomenon is not sufficiently explored or captured in an omnichannel context. Retailers appear to lack knowledge of the relevant concepts, dimensions, and consequences of the consumer confusion phenomenon. As a result, retailers are likely to fail in addressing and preventing the occurrence of the consumer confusion phenomenon in an omnichannel context. Current studies on strategic assortment decisions and consumer confusion in omnichannel retailing are very scarce and primarily based on experimental studies with a strong lack of empirical contributions. More importantly, none of the studies considers channel switching behaviour in the context of consumer confusion although representing the primary condition for the phenomenon to occur. There is a need for the integration and alignment of knowledge capturing the domains for strategic assortment decisions, the consumer confusion concept, and its short- and long-term consequences from a channel switching behaviour perspective in order to inform strategic assortment decisions at the MOI. Ontologies are explicit and formal specifications of shared conceptualisations that can structure and link information of specific domains and thus are a suitable technique for knowledge representation. Grounded on a Design Science project, this research designs and develops an ontology-based knowledge representation that captures and aligns domain knowledge on strategic assortment decisions, the consumer confusion concept and its consequences from a channel switching behaviour perspective in an omnichannel retailing context. The literature- and practitioner-informed Omnichannel Assortment Ontology for Consumer Confusion is able to integrate and represent relevant concepts and their relationships at the MOI in order to inform omnichannel retailers on the link between strategic assortment decisions and the consumer confusion phenomenon. The ontology is instantiated and evaluated through a System Dynamics model based on a case study that demonstrates successfully its ability to inform omnichannel retailers on strategic assortment decisions and the consumer confusion concept at the MOI. This study contributes to theory and practice in various ways. From a theoretical perspective, this is the first study to link strategic assortment decisions with the consumer confusion concept from a channel switching behaviour perspective. The solution design embodies novel design knowledge on the construction of an ontology-based knowledge representation. Moreover, the study enhances the fields of omnichannel assortment, consumer confusion, and channel switching behaviour research by introducing novel concepts, tools, and an improved understanding of the domains and their interplay with each other. From a managerial perspective, the ontology effectively serves as a knowledge reference that is able to guide strategic decision-making in assortment integration for omnichannel retailers at the MOI. This allows omnichannel retailers to identify and mitigate potential adverse consumer reactions induced by consumer confusion, thus eventually preventing financial impact on their retail performance