Motivation is a universal psychological phenomenon that determines all that we do. Self- determination Theory (SDT) and Achievement Goal Theory (AGT) each explain the academic motivation of university students and its relation to important academic outcomes (achievement, dedication, and well-being). Recently, an integration of these theories has been proposed (Drylund, 2009) which theorizes that achievement goals affect academic outcomes through their relationship with SDT constructs. The current study uses this integrative theory as a starting point but applies the critical realist perspective which posits that all empirical behaviours are produced by real generative mechanisms (Bhaskar, 1978). Although critical realism is considered vital to the advancement of psychology, its methodology and actual application has yet to be elaborated. Thus, the goals of the current study are: 1. to increase the current understanding of academic motivation; and, 2. to provide a method capable of facilitating research conducted from the critical realist perspective. Study 1 uses a variable-based approach and statistical analysis of questionnaire data from 385 undergraduate students; Study 2 uses a case-based approach through causal mapping of interview data from a purposeful sample of 12 Study 1 participants. Results support an academic motivational mechanism primarily influenced by autonomy satisfaction and controlling motivation that functions through the complex reciprocal relationships between achievement goals, competence satisfaction, and autonomous motivation. Comparison of Study 1 and 2 results supports the argument for case-based research from a critical realist perspective to aid in the further advancement of psychology.

Information Technology Technical Competency is critical for the optimal functioning of any organization. IT personnel need to be competent in their technical skills. Studying how IT personnel build their technical competencies is a critical but under-studied area of research. To date, very little research has been done on how to build IT Technical Competencies, and virtually none of this research begins with qualitative data or uses IT personnel as key respondents. Initially, we evoke a revealed causal map that shows four concepts in the IT Environment construct: the Technical Environment, the People Environment, the Business Environment, and the Job Environment. Our model first proposes a relationship between the IT Environment and IT Technical Competency. An original survey based on the qualitative data was developed for this study. Data was collected at four research sites: a manufacturing organization, a healthcare organization, a government organization, and an education organization. All together 101 respondent's survey answers were analyzed. We tested the proposed model of IT Technical Competency using the method of path analysis with linear regression. Our results indicated that the Technical and Business Environments are viewed as one, so we end up with a three environment concept model of IT Technical Competency. Our model achieved a R-squared value of above 0.5, meaning that the environment surrounding IT personnel, the IT Environment, is 50% related to IT Technical Competency. This is the first model to this author's knowledge that holistically looks at environment in relation to technical competency. Future research will continue look more in-depth at each of the concepts in this environment individually.

The elicitation and processing of relevant information is the core of any policy decision-making process. Modelling is about making sense of the available information. Models are able to incorporate the contextual influences on policy making (e.g. political and economic environments, community sentiment…etc). Systems analysis allows quantitative, empirical testing of models that exist in the study of public policy. Simulation and visualisation techniques can help policy makers to reduce uncertainties on the possible impacts of policies. In an effort to enable adoption of the systems thinking approach to address the central problem of empirical political study, this thesis presents a framework for prescriptive policy analysis that provides decision support to: the problem definition, ex-ante impact assessment and evaluation activities carried out at the policy formulation stage of the policymaking process. We contribute a new tool for systemic modelling and simulation of public policy decision situations. It aims to facilitate the cognitive activity of representing complex mental models using system dynamics simulation modelling. Using the ’labelled causal mapping’ method, a policy-oriented problem structuring method introduced in this research, the tool bridges the gap between the user’s mental model and the explicit graphical representation in order to enable knowledge representation and system analysis. The method provides a basis for further computational decision analysis using a common policy appraisal format, a multi-criteria model with main evaluation criteria (effectiveness, efficiency, relevance, coherence and added value), linked to a set of measurable, context dependent attributes (targeted impact variables from the policy model). A web-based tool prototype has been implemented in a Node.js environment and is accessible both from a web-based graphical user interface as well as a hosted API.  Multiple demonstration and test cases, from various policy areas and different EU policymaking levels, were used in several iterations of the build-evaluate cycle. This approach lead to the different studies that make up this research. / Sense4us - Data insights for policymakers and Citizens

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Food loss and waste (FLW) occurring early in the food supply chain (FSC) leads to increased resource wastage, including land, water, fertilisers, pesticides, fuel, packaging, energy, and labour. Targeting FLW prevention benefits various aspects such as food security, productivity, economic growth, climate change mitigation, resource conservation, and food waste management. Understanding the causes of FLW and their environmental impact is crucial for the design of effective solutions and their prioritisation. The purpose of this study was to investigate the risk factors and underlying causes of FLW in leafy vegetables (LV), mainly lettuce, throughout the Brazilian FSC, spanning from harvest to retail. Additionally, the study evaluated the environmental impact of waste management strategies applicable in the context of the case study. To achieve this, the research methodology encompassed a case study conducted among small-scale producers and retailers in the city of Tupã, Brazil. A comprehensive approach was adopted by integrating a systematic literature review of global FLW causes and those specific to the Latin American context. This approach was complemented by exploratory research, involving interviews with various stakeholders along the FSC, coupled with rigorous root-cause analysis. Moreover, the study employed a Life Cycle Assessment (LCA) methodology to offer an immersive perspective, determining the environmental implications associated with different approaches to treating lettuce waste in the case study. Findings revealed that the root causes of FLW in the case study encompassed normalised unfair trading practices, notably take-back agreement (TBA) conditions, and the absence of supportive policies and incentives for FLW reduction. These root causes manifested in the absence of formal agreements between retailers and local producers, leading to the return of unsold or substandard items without compensation. Furthermore, supermarkets exert power over product quality but evade responsibility for proper storage or encouraging the utilisation of unsold products. Another category of significant causes, designated by the author as "major causes," encompassed causes such as unpreparedness for adverse weather conditions, lack of skilled labour, and stringent visual quality standards. These factors were pivotal risk contributors that potentially motivate various other causes of FLW. To tackle root and major causes of FLW of LV, this study proposed specific measures encompassing fair trade agreements, policy enhancements, protective measures for producers, skill development, and flexible standards. Moreover, by implementing an attributional LCA methodology, the study underscored the importance of source reduction in preventing the environmental impact of food waste for the specific context of the case study. According to the results obtained, for each kg of lettuce that is not produced, 0.065 kg CO2eq are avoided. These findings also highlighted the environmental efficacy of animal feed production, which is a cost-efficient strategy, widely prevalent in the city studied, presents a carbon footprint of -0.013 kg CO2eq/kg of waste. Other common solutions implemented at the case study, such as anaerobic digestion and composting exhibit less favourable carbon footprints, measuring 0.019 and 0.006 kg CO2eq/kg of lettuce, respectively. Landfilling emerges, as expected, as the least desirable option with a considerably higher carbon footprint of 0.423 kg CO2eq/kg. To summarise, this study highlights the environmental advantages of prioritising prevention and higher waste hierarchy levels. It underscores the need for context-specific evaluations when dealing with the intricacies of waste management systems. Moreover, the research emphasises the potential for innovative strategies, multi-stakeholder collaboration, and a holistic approach to address the complex issue of FLW, considering both the environmental impact and practical challenges in a real-world implementation.

With advancement in information and communication technologies (ICT), Smart Cities are becoming a popular urban development strategy amongst policymakers and city managers to respond to various threats posed by rapid urbanization such as environmental degradation and increasing inequality (Hartemink, 2016). Therefore, globally, regions ranging from small towns to megacities are proposing and investing in smart city (SC) initiatives. Unfortunately, the prolific use of this term by city managers and technology vendors is clouding the view on what it really takes to become a SC (Van den Bergh and Viaene, 2015). Consequently, cities are experiencing multiple implementation risks when trying to turn a smart city ambition into reality. These implementation risks reflect the gaps or missing pieces in the current organizational structure and policies designed for implementing SC projects at the city level. They can be understood better if the process of SC transformation is explored using diverse cases of cities undergoing such a transformation. However, the current studies on SC initiatives at the local, regional, national, and international level have focused on: 1) strengthening the SC concept rather than understanding the practical implementation of the concept – i.e., discussing SC characteristics and outcomes rather than focusing on the challenges faced in implementing SC projects; 2) cases that have already been developed as a SC or are soon to become a SC, leaving out the opportunity to study cities undergoing SC transformation and the identification of implementation risks; and 3) cases from more advanced economies. Taken together, these observations reveal the need for research that focuses on SC initiatives in a developing nation context. More specifically, there is a need for researchers, city managers, and policymakers in these regions to focus on the process of SC transformation to identify implementation risks early on in the process. Understanding these risks may help the development of better risk mitigation strategies and result in more successful SC projects. This research explores SC implementation risks in two cities currently undergoing a SC transformation in India – Kakinada and Kanpur. While examining the risks landscape in these two cities, the research also explores what city officials are focused on when implementing SC projects. This research finds that: 1) implementation risks such as Institutional, Resource and Partnership, and Social are crucial for implementing SC projects; 2) in the cities of Kakinada and Kanpur, Institutional risks that relate to gaps and deficiencies in local urban governance such as overlapping functions of multiple local urban development agencies, have causal linkages with other risks such as Resource and Partnership risks and Financial risks, which further delay project implementation; and 3) city officials and industry professionals implementing SC projects in Kakinada and Kanpur have a slightly different perspective on smartness, however both the groups focus on External smartness of the city – i.e., projects related to physical infrastructure such as mobility and sanitation – rather than Internal smartness of the city – i.e., strengthening local urban governance, increasing citizen engagement, etc. Overall, this research proposes that there is a need to frame the concept of a SC around both Internal and External Smartness of the city. This research will be of special interest to: 1) cities (in both developed and developing nations) currently implementing SC projects by providing a framework to systematically examine the risk landscape for successful project implementation; and 2) communities/institutions (especially in developing nations) proposing SC initiatives by helping them focus on components, goals, and enablers of a SC. / Doctor of Philosophy / The concept of a Smart City (SC) revolves around "using Information and Communication Technologies (ICT) to increase workability, liveability, and sustainability" of a city (Smart Cities Council, 2014). SCs are becoming a popular urban development strategy amongst policymakers and city managers to respond to various threats posed by rapid urbanization such as environmental degradation and increasing inequality (Hartemink, 2016). Unfortunately, city managers see SCs as a readymade solution to urban challenges. As a consequence, cities are experiencing multiple implementation risks when trying to turn a smart city ambition into reality. These implementation risks reflect the gaps or missing pieces in the current organizational structure and policies designed for implementing SC projects at the city level. They can be understood better if the process of SC transformation is explored. However, the current studies on SC initiatives at the local, regional, national, and international level have focused on: 1) strengthening the SC concept rather than understanding the practical implementation of the concept; 2) cases that have already been developed as a SC or are soon to become a SC, leaving out the opportunity to study cities undergoing SC transformation and the identification of implementation risks; and 3) cases from more advanced economies. Taken together, these observations reveal the need for research that focuses on SC initiatives in a developing nation context. More specifically, there is a need for researchers, city managers, and policymakers in these regions to focus on the process of SC transformation to identify implementation risks early in the project development process. Understanding these risks may help the development of better risk mitigation strategies and result in more successful SC projects. This research explores SC implementation risks in two cities currently undergoing a SC transformation in India – Kakinada and Kanpur. This research finds that: 1) implementation risks such as Institutional, Resource and Partnership, and Social are crucial for implementing SC projects; 2) in the cities of Kakinada and Kanpur, Institutional risks that relate to gaps and deficiencies in local urban governance such as overlapping functions of multiple local urban development agencies, have causal linkages with other risks such as Resource and Partnership risks and Financial risks, which further delay project implementation; and 3) city officials and industry professionals implementing SC projects in Kakinada and Kanpur have a slightly different perspective on smartness, however both the groups focus on the External smartness of the city – i.e., projects related to physical infrastructure such as mobility and sanitation – rather than the Internal smartness of the city – i.e., strengthening local urban governance, increasing citizen engagement, etc.

[pt] A compreensão dos atuais processos produtivos é essencial neste momento em que o conhecimento tornou-se um importante gerador de valor. Uma visão holística dos conhecimentos que estão disseminados, de forma dispersa, entre profissionais, consultores e acadêmicos é necessária para a síntese de novas teorias da produção. Pesquisadores de gerência de operações freqüentemente usam mapeamento causal como um mecanismo para construir e comunicar teorias, particularmente em suporte à pesquisa empírica. As abordagens mais usuais para capturar dados cognitivos para um mapa causal são brainstorming e entrevistas, os quais exigem muito tempo e apresentam um significativo custo em sua implementação. Esta tese visa gerar uma metodologia (Metodologia Evocativa para Mapeamento Causal - ECMM) voltada para aplicação em pesquisa sobre gerência de operações para coletar e estruturar dados disseminados de forma desagregada, como conhecimento e experiência profissional e acadêmica, contidos nas opiniões de um grande número de especialistas dispersos demograficamente e geograficamente. Isto é alcançado evocando opiniões, codificando-as em variáveis e reduzindo o grupo em conceitos e relações. Tem-se uma especial preocupação em conseguir este objetivo em tempo factível e com baixo custo. A coleta de dados é assíncrona, via Internet, possui dois ou três turnos (à semelhança do método Delfos). A análise de dados usa codificação, técnica de grupamento hierárquica e escalamento multidimensional para identificar conceitos na forma de mapas cognitivos. A ECMM foi ilustrada com aplicações que demonstram sua viabilidade. Aplicou-se nas áreas de gestão da cadeia de suprimento (SCM) e administração de serviços (SM) com a participação de aproximadamente 1.300 respondentes de empresas e universidades de quase 100 países. Dentre os desdobramentos para pesquisas futuras propõe-se aplicar nas áreas de ECMM em SCM e SM visando a uni-las em um tema: gestão da cadeia de suprimento de serviços. / [en] The understanding of the present productive processes is essential at this moment when knowledge became an important value creator. A holistic vision of the pieces of knowledge that are spread out and dispersed among practitioners, consultants and academics is necessary for the synthesis of new theories of production. Operations management researchers often use causal mapping as a key tool for building and communicating theory, particularly in support of empirical research. The widely accepted approaches for capturing cognitive data for a causal map are informal brainstorming and interviews, which require a time- consuming and significant cost of implementation. This dissertation aims at creating a methodology (Evocative Causal Mapping Methodology - ECMM) intended for use in operations management research for collecting and structuring dispersed data spread out as practical and research knowledge, and experience contained in the opinions of a large number of specialists demographically and geographically scattered. This is accomplished by evoking opinions, encoding them into variables and reducing the resulting set to concepts and relationships. A special concern is to achieve this goal in a feasible time and cost- efficient way. ECMM consists of two or three round, Delphi- like, Internet-based asynchronous data collection, and a data analysis that uses a coding panel of experts, hierarchical cluster analysis and multidimensional scaling for identifying concepts on cognitive map formats. Applications illustrate ECMM and demonstrate its feasibility. They were developed on supply chain management (SCM) and service management (SM) involving about 1,300 respondents of companies and universities of about 100 countries. Among possible unfolding future studies, this dissertation proposes to apply ECMM in SCM and SM aiming at unifying them into a single topic: service supply chain management.