6,901 research outputs found

    An empirical investigation of the relationship between integration, dynamic capabilities and performance in supply chains

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    This research aimed to develop an empirical understanding of the relationships between integration, dynamic capabilities and performance in the supply chain domain, based on which, two conceptual frameworks were constructed to advance the field. The core motivation for the research was that, at the stage of writing the thesis, the combined relationship between the three concepts had not yet been examined, although their interrelationships have been studied individually. To achieve this aim, deductive and inductive reasoning logics were utilised to guide the qualitative study, which was undertaken via multiple case studies to investigate lines of enquiry that would address the research questions formulated. This is consistent with the author’s philosophical adoption of the ontology of relativism and the epistemology of constructionism, which was considered appropriate to address the research questions. Empirical data and evidence were collected, and various triangulation techniques were employed to ensure their credibility. Some key features of grounded theory coding techniques were drawn upon for data coding and analysis, generating two levels of findings. These revealed that whilst integration and dynamic capabilities were crucial in improving performance, the performance also informed the former. This reflects a cyclical and iterative approach rather than one purely based on linearity. Adopting a holistic approach towards the relationship was key in producing complementary strategies that can deliver sustainable supply chain performance. The research makes theoretical, methodological and practical contributions to the field of supply chain management. The theoretical contribution includes the development of two emerging conceptual frameworks at the micro and macro levels. The former provides greater specificity, as it allows meta-analytic evaluation of the three concepts and their dimensions, providing a detailed insight into their correlations. The latter gives a holistic view of their relationships and how they are connected, reflecting a middle-range theory that bridges theory and practice. The methodological contribution lies in presenting models that address gaps associated with the inconsistent use of terminologies in philosophical assumptions, and lack of rigor in deploying case study research methods. In terms of its practical contribution, this research offers insights that practitioners could adopt to enhance their performance. They can do so without necessarily having to forgo certain desired outcomes using targeted integrative strategies and drawing on their dynamic capabilities

    Establishing genetic manipulation for novel strains of human gut bacteria

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    Acknowledgements We would like to thank Pat Bain for preparing the Figures. Financial support and sponsorship The Rowett Institute (University of Aberdeen) receives financial support from the Scottish Government Rural and Environmental Sciences and Analytical Services (RESAS).Peer reviewedPublisher PD

    Integration of MLOps with IoT edge

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    Abstract. Edge Computing and Machine Learning have become increasingly vital in today’s digital landscape. Edge computing brings computational power closer to the data source enabling reduced latency and bandwith, increased privacy, and real-time decision-making. Running Machine Learning models on edge devices further enhances these advantages by reducing the reliance on cloud. This empowers industries such as transport, healthcare, manufacturing, to harness the full potential of Machine Learning. MLOps, or Machine Learning Operations play a major role streamlining the deployment, monitoring, and management of Machine Learning models in production. With MLOps, organisations can achieve faster model iteration, reduced deployment time, improved collaboration with developers, optimised performance, and ultimately meaningful business outcomes. Integrating MLOps with edge devices poses unique challenges. Overcoming these challenges requires careful planning, customised deployment strategies, and efficient model optimization techniques. This thesis project introduces a set of tools that enable the integration of MLOps practices with edge devices. The solution consists of two sets of tools: one for setting up infrastructure within edge devices to be able to receive, monitor, and run inference on Machine Learning models, and another for MLOps pipelines to package models to be compatible with the inference and monitoring components of the respective edge devices. This platform was evaluated by obtaining a public dataset used for predicting the breakdown of Air Pressure Systems in trucks, which is an ideal use-case for running ML inference on the edge, and connecting MLOps pipelines with edge devices.. A simulation was created using the data in order to control the volume of data flow into edge devices. Thereafter, the performance of the platform was tested against the scenario created by the simulation script. Response time and CPU usage in different components were the metrics that were tested. Additionally, the platform was evaluated against a set of commercial and open source tools and services that serve similar purposes. The overall performance of this solution matches that of already existing tools and services, while allowing end users setting up Edge-MLOps infrastructure the complete freedom to set up their system without completely relying on third party licensed software.MLOps-integraatio reunalaskennan tarpeisiin. Tiivistelmä. Reunalaskennasta (Edge Computing) ja koneoppimisesta on tullut yhä tärkeämpiä nykypäivän digitaalisessa ympäristössä. Reunalaskenta tuo laskentatehon lähemmäs datalähdettä, mikä mahdollistaa reaaliaikaisen päätöksenteon ja pienemmän viiveen. Koneoppimismallien suorittaminen reunalaitteissa parantaa näitä etuja entisestään vähentämällä riippuvuutta pilvipalveluista. Näin esimerkiksi liikenne-, terveydenhuolto- ja valmistusteollisuus voivat hyödyntää koneoppimisen koko potentiaalin. MLOps eli Machine Learning Operations on merkittävässä asemassa tehostettaessa ML -mallien käyttöönottoa, seurantaa ja hallintaa tuotannossa. MLOpsin avulla organisaatiot voivat nopeuttaa mallien iterointia, lyhentää käyttöönottoaikaa, parantaa yhteistyötä kehittäjien kesken, optimoida laskennan suorituskykyä ja lopulta saavuttaa merkityksellisiä liiketoimintatuloksia. MLOpsin integroiminen reunalaitteisiin asettaa ainutlaatuisia haasteita. Näiden haasteiden voittaminen edellyttää huolellista suunnittelua, räätälöityjä käyttöönottostrategioita ja tehokkaita mallien optimointitekniikoita. Tässä opinnäytetyöhankkeessa esitellään joukko työkaluja, jotka mahdollistavat MLOps-käytäntöjen integroinnin reunalaitteisiin. Ratkaisu koostuu kahdesta työkalukokonaisuudesta: toinen infrastruktuurin perustamisesta reunalaitteisiin, jotta ne voivat vastaanottaa, valvoa ja suorittaa päätelmiä koneoppimismalleista, ja toinen MLOps “prosesseista”, joilla mallit paketoidaan yhteensopiviksi vastaavien reunalaitteiden komponenttien kanssa. Ratkaisun toimivuutta arvioitiin avoimeen dataan perustuvalla käyttötapauksella. Datan avulla luotiin simulaatio, jonka tarkoituksena oli mahdollistaa reunalaitteisiin suuntautuvan datatovirran kontrollonti. Tämän jälkeen suorituskykyä testattiin simuloinnin luoman skenaarion avulla. Testattaviin mittareihin kuuluivat muun muassa suorittimen käyttö. Lisäksi ratkaisua arvioitiin vertaamalla sitä olemassa oleviin kaupallisiin ja avoimen lähdekoodin alustoihin. Tämän ratkaisun kokonaissuorituskyky vastaa jo markkinoilla olevien työkalujen ja palvelujen suorituskykyä. Ratkaisu antaa samalla loppukäyttäjille mahdollisuuden perustaa Edge-MLOps-infrastruktuuri ilman riippuvuutta kolmannen osapuolen lisensoiduista ohjelmistoista

    The nexus between e-marketing, e-service quality, e-satisfaction and e-loyalty: a cross-sectional study within the context of online SMEs in Ghana

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    The spread of the Internet, the proliferation of mobile devices, and the onset of the COVID-19 pandemic have given impetus to online shopping in Ghana and the subregion. This situation has also created opportunities for SMEs to take advantage of online marketing technologies. However, there is a dearth of studies on the link between e-marketing and e-loyalty in terms of online shopping, thereby creating a policy gap on the prospects for business success for online SMEs in Ghana. Therefore, the purpose of the study was to examine the relationship between the main independent variable, e-marketing and the main dependent variable, e-loyalty, as well as the mediating roles of e-service quality and e-satisfaction in the link between e-marketing and e-loyalty. The study adopted a positivist stance with a quantitative method. The study was cross-sectional in nature with the adoption of a descriptive correlational design. A Structural Equation Modelling approach was employed to examine the nature of the associations between the independent, mediating and dependent variables. A sensitivity analysis was also conducted to control for the potential confounding effects of the demographic factors. A sample size of 1,293 residents in Accra, Ghana, who had previously shopped online, responded to structured questionnaire in an online survey via Google Docs. The IBM SPSS Amos 24 software was used to analyse the data collected. Positive associations were found between the key constructs in the study: e-marketing, e-service quality, e-satisfaction and e-Loyalty. The findings from the study gave further backing to the diffusion innovation theory, resource-based view theory, and technology acceptance model. In addition, e-service quality and e-satisfaction individually and jointly mediated the relationship between e-marketing and e-loyalty. However, these mediations were partial, instead of an originally anticipated full mediation. In terms of value and contribution, this is the first study in a developing economy context to undertake a holistic examination of the key marketing performance variables within an online shopping context. The study uniquely tested the mediation roles of both e-service quality and e-satisfaction in the link between e-marketing and e-loyalty. The findings of the study are novel in the e-marketing literature as they unearthed the key antecedents of e-loyalty for online SMEs in a developing economy context. The study suggested areas for further related studies and also highlighted the limitations

    An onto-epistemological (re)framing and (re)connecting of organisations as praxeological multi-capital value systems

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    Organisation stands as one of humankind’s greatest inventions, and reconceptualising organisations to meet the ever-diversifying needs of the modern stakeholder community one of its most significant challenges. Historically, scientific management principles simplified the challenge through a profitable operations practice imperative, which reinforced a creation and destruction value dualism, and causal and value dead ends. However, value is contingent upon meeting needs, demanding that organisations leverage a wider and connected set of capitals to meet the diverse needs of modernity. This research seeks to understand how praxeologically inert legacy organisations can generate value by (re)connecting capitals and (re)framing as multi-capital value systems. The study’s setting is the university-led Made Smarter Leadership Development programme which provided an insightful longitudinal case study over the two-year programme life-cycle. The research surfaced rich qualitative insights on participant sense-making journeys across a diverse set of participant-researcher touchpoints, and also collected associated quantitative survey data. Analysis was conducted in three streams, and iteratively built up a complementary organisational model ontology. Stream one, a qualitative ethnographic study utilised grounded theory analysis to surface the prâxis (re)framing priorities of organisations. Analysis of such priorities yielded an onto-epistemological perspective of an organisation, and novel insights were generated on prâxis (re)framing strategies, organisational maturity, and how prâxes and frames combine as a relational onto-epistemological duality. Stream two’s quantitative analysis of respondent data identified the 20 significant prâxis-elements that form six systemically correlated and causally related capital factors. Findings indicate how multiple capitals connect as an organisational structure which orchestrates value flows between capital factors. Stream three elaborated on the prior two streams’ empirically-grounded foundations through sensemaking systems dynamics theory. This modelling produced both empirical findings and a generalisable methodology to reconceptualise organisations as a connected praxeological multi-capital value system. Specifically, findings informed how means-ends dynamics orchestrate complex capital interactions, which form pan-organisational value journeys, and ultimately form generalisable value archetypes. In summary, the research confirmed an organisation is a connected multi-capital praxeological value system, this outcome enabled by the discovery of a novel onto-epistemological perspective of organisations
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