4,701 research outputs found

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    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

    From wallet to mobile: exploring how mobile payments create customer value in the service experience

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    This study explores how mobile proximity payments (MPP) (e.g., Apple Pay) create customer value in the service experience compared to traditional payment methods (e.g. cash and card). The main objectives were firstly to understand how customer value manifests as an outcome in the MPP service experience, and secondly to understand how the customer activities in the process of using MPP create customer value. To achieve these objectives a conceptual framework is built upon the Grönroos-Voima Value Model (Grönroos and Voima, 2013), and uses the Theory of Consumption Value (Sheth et al., 1991) to determine the customer value constructs for MPP, which is complimented with Script theory (Abelson, 1981) to determine the value creating activities the consumer does in the process of paying with MPP. The study uses a sequential exploratory mixed methods design, wherein the first qualitative stage uses two methods, self-observations (n=200) and semi-structured interviews (n=18). The subsequent second quantitative stage uses an online survey (n=441) and Structural Equation Modelling analysis to further examine the relationships and effect between the value creating activities and customer value constructs identified in stage one. The academic contributions include the development of a model of mobile payment services value creation in the service experience, introducing the concept of in-use barriers which occur after adoption and constrains the consumers existing use of MPP, and revealing the importance of the mobile in-hand momentary condition as an antecedent state. Additionally, the customer value perspective of this thesis demonstrates an alternative to the dominant Information Technology approaches to researching mobile payments and broadens the view of technology from purely an object a user interacts with to an object that is immersed in consumers’ daily life

    Genetic and cardiometabolic contributions to cognitive, structural brain and biomarker phenotypes

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    The number of individuals experiencing abnormal cognitive ageing is rapidly increasing, which can only in part be explained by an ageing population. Prevention of considerable cognitive decline is complicated by its heterogeneity and numerous risk factors. The most significant contributions to brain health and cognitive decline outside of age are higher genetic risk and poor cardiometabolic health. There are gaps in the literature and understanding regarding the extent to which common genetic or cardiometabolic conditions contribute to and interact with one another to influence brain health. Therefore, the overall aim of this PhD project is to explore genetic and cardiometabolic risks in relation to structural brain MRI measures, cognitive assessments, and blood biomarkers. This thesis used large-scale secondary data from the UK Biobank in which several analyses investigating associations between cardiometabolic conditions, genetic risks, cognition, and brain MRI data are the largest to date. The use of the UK Biobank cohort also allowed for controlling of confounders that have not been considered or accounted for in previous studies. The primary focus of this thesis was on genetic and cardiometabolic contributions to cognition and brain MRI. The main objectives were: (1) Contribute to the understanding of cardiovascular to brain health and (2) Determine the role of genetic risk factors on the brain and physical health in healthy adults. When examining multimorbidity, there were no clear trends between cardiometabolic groups and brain MRI metrics. However, this may have been due to a healthy selection bias in which those with multimorbidity were healthy enough for MRI assessments. When examining genetically elevated risk of cardiovascular disease (CVD) indexed by lipoprotein A (), we found associations with mean diffusivity and fractional anisotropy, suggesting a potential role of LpA in brain ageing. However, we found discrepancies between genetically elevated LpA and blood LpA, which should be further investigated. When calculating genetic risk scores for Alzheimer’s disease (AD) in healthy midlife adults, we found evidence for potential early ageing pathology within subfields of the hippocampus prior to significant cognitive impairments. We also found that this elevated genetic risk for AD was associated with elevated cystatin c. Elevated genetic risk of AD also showed significant sex differences in biomarker analyses. Creatinine and oestradiol were significantly associated with an elevated risk of Alzheimer’s in women but not men. These findings support routine stratification in exploratory research. This thesis emphasises the importance of epidemiological research that considers cardiometabolic, lifestyle and genetic risk factors together in the context of cognitive health. There is scope to build on this work in omics and cohort studies

    A Theory Kit for World History

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    This report presents a “kit” of theories regarding major processes in human history formed into a whole, a “theory kit”, with the aim to understand how these processes unfold over thousands of years. The theory kit has an underlying fundamental theoretical approach concerning dialectical, contradictory, processes as a core of the complex matrix that shapes human history. In the kit, history is presented in three spheres that are given equal importance: material culture, social structure and societal mentality. An enigma in world history is the common rhythm: different parts of the world tend to move at the same time and in the same direction. The claim here is that the enormous interacting complexity is one explanation of this relative unity in change. In the theory kit a number of issues are discussed, such as: Axial Ages, class struggle, empires, expansion-stagnation-crisis, agricultural world systems, technological complex(es), mentality world systems, invention-innovation

    Exploring how Interactions and Responses within the Servicescape combine to form Customer Experience – A Text Mining Approach

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    The core research objective in this thesis is to address the ways in which Customer Experience (CX) emerges through the combinational effects of multiple customer interactions at touchpoints and their resulting CX responses. The empirical study designed in this work is positioned to build upon existing literature within the Service Management field. According to extant work, CX can be viewed from both the provider’s perspective (e.g. ‘intended’ or designed), and the customer’s perspective (e.g. ‘realised’ or subjective). The thesis integrates both accounts through the presentation of a new conceptual model which forms the basis for the design of the empirical study. Several limitations are addressed in this work. First, building on the notion that CX emerges across multiple touchpoint interactions (Lemon and Verhoef, 2016) the study explores the impact multiple interaction types, and their associated responses, have on overall CX. Extant studies have tended to view CX at single touchpoint interactions (Becker and Jaakkola, 2020). CX emerges across multiple touchpoint interactions, which each induce responses in the customer. As it stands, little is known about how this process occurs, or the relationships which exist between customer interaction, customer response, and overall CX. Second, the study widens the field and its understanding of the servicescape from an ‘unbounded’ perspective (Rosenbaum and Massiah, 2011). Traditionally, studies have explored CX through the impact of provider-owned touchpoints, predominantly within bounded service sites. The study addresses requests to explore the impact of wider, non-provider-controlled touchpoints on overall CX (Kandampully et al., 2018). Relating to this aim, very little existing work deals with the impact of natural servicescape touchpoints on CX. The case studies in this work have been chosen for their suitability to address this gap. The study employs a comparative case study approach from the cultural heritage sector. Text mining (TM) and text analytics (TA) techniques are employed to capture and assess CX elements found within customer feedback data from an online review depository. Contrary to existing work in this field, the study employs a three-step annotation process to concept classification which can ensure rigour in the results. The purpose of the analysis process is to capture patterns of CX responses and customer interactions within the data and assess their relationship to overall CX ratings. Both quantitative measures (e.g. statistical analysis) and qualitative measures (e.g. verbatim text analysis) are used to explore a number of key questions relating to the core research objective. The empirical study performed in this work results in several key findings. The study finds that CX arises as a combination of customer interactions and CX responses, with each pattern impacting the overall experience in different ways. Results suggest that pattern prevalence and prominence are not core drivers of customer rating, but rather that significance measures need to be employed. From a customer perspective, negative CX responses have a stronger effect on overall CX rating than positive responses. These can be induced through touchpoint interactions beyond the control of the provider. The emotional content of the experience is key, with customer surprise, anger, and sadness significantly impacting CX to a greater degree than other discrete emotions. The findings suggest that customer expectations play an important role in the delivery of CX. Customer expectations can be used to make sense of the differences in terms of patterns and the statistical significance of their relationship to CX rating. Several potential avenues for future work to further develop these themes are put forward in the final stages of the thesis.EPSRC and University of Exeter Business Schoo
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