Den industriella digitaliseringen utvecklas med hög fart. Många verksamheter tar steget mot ett mer digitaliserat arbetssätt. Digitala förbättringstavlor är ett av flera nya digitaliseringsverktyg som verksamheter och organisationer kan använda sig av för att skapa högre delaktighet och engagemang hos medarbetarna. Det finns många fördelar att gå ifrån den analoga förbättringstavlan till den digitala. Några av dessa är att digitala förbättringstavlor ger bättre styrning, vilket leder till att det går snabbt att ta fram information och dela med medarbetarna. Tavlan visualiserar dagordningen samt skapar en informationsplats för att samla viktig information som kan vara användbar för medarbetarna. Digitala förbättringstavlor kan presentera information beroende på vad verksamheten vill förmedla, till exempel information om nyckeltal till medarbetarna.  Syftet med denna fallstudie är att bredda kunskapen om digitala förbättringstavlor samt ta fram beslutsunderlag för en kommande implementering. Med hjälp av intervjuer samt mailkonversationer med fallföretaget och leverantörer har det empiriska materialet samlats in. Studien besvarar följande frågeställningar: -       Vad ska en digital förbättringstavla innehålla? -       Vilka beslutsunderlag behövs för införandet av digitala förbättringstavlor? -       Varför behöver medarbetare information om nyckeltal? Målet med fallstudien är att jämföra leverantörer med hjälp av en kravspecifikation för att kunna skapa ett beslutsunderlag. Författarna vill även att andra verksamheter skall kunna använda de beslutsunderlag som skapats. Författarna kontaktade fyra leverantörer som kunde leverera en digital förbättringstavla, dessa leverantörer jämfördes med hjälp av kravspecifikation samt ett egenutvecklat verktyg för beslutsstöd. Utifrån dessa jämförelser kom författarna fram till en rekommendation för val av leverantör. / Industrial digitalisation is developing rapidly, more companies are willing to take the step towards a more digitised way of working. Digital improvement boards is one of several new digital tools that companies and organisations can make use of. Therefore, they would create a higher commitment and motivation for the co- workers. There are several benefits to change from analog boards to digital boards, some of these benefits are following, improved management, visualisation of today's schedule and the board creates a information center where important information can be presented. The digital improvement board can be customized to present what the company wants, for example informing their co-workers about how their KPI’s are performing. The purpose of this case study is to acquire more knowledge about digital improvement boards and also create a decision basis for an implementation. Interviews and mail conversations with the case company and suppliers have helped the authors gather the empirical data needed. This study answers the following questions:    -       What should a digital improvement board contain? -       Which decision basis is needed for the implementation of a digital improvement board? -       Why are KPI’s important for the co-workers? The goal with this study is to compare several suppliers, with the help of a requirement specification. The authors also want other businesses to be able to use the decision basis as a template. The authors contacted four suppliers who were able to deliver a digital improvement board, these suppliers were then compared with each other with help of a requirement specification and a Multi Criteria Decision Making tool. Based on the result of the MCDM tool, the authors came to a conclusion of which supplier they would recommend.

New Zealand faces a range of food safety hazards. Microbial hazards alone were estimated to cause over 2,000 years of lost healthy life in 2011 (Cressey, 2012) and $62m in medical costs and lost productivity in 2009 (Gadiel & Abelson, 2010). Chemical hazards are thought to be well managed through existing controls (Vannoort & Thomson, 2009) whereas microbial hazards are considered harder to control, primarily due to their ability to reproduce along the food production chain. Microbial hazards are thought to cause the majority of acute foodborne gastroenteritis. This research reviewed food safety literature and official documentation, and conducted 55 interviews, mostly with food safety experts from different stakeholder groups, to examine the food safety decision-making environment in New Zealand. This research explores the concept of the ‘stakeholder’ in the context of food safety decision-making and proposes an inclusive ‘stakeholder’ definition as any group which is able to affect, or be affected by, the decision-making process. Utilising this definition, and guided by interviews, New Zealand stakeholders in food safety decision-making were identified and classified as follows: •Regulators •Public health authorities •Food safety scientists/academics •Consumers •Māori •Food Businesses (further classified as): o Farmers o Processors o Food retailers o Exporters Interviews with stakeholders from these groups highlighted twelve criteria as being relevant to multiple groups during food safety intervention evaluation: •Effectiveness •Financial cost •Market Access •Consumer Perceptions •Ease of Implementation •Quality or Suitability •Quality of Science •Equity of Costs •Equity of Benefits •Workplace Safety •Cultural Impact •Animal Welfare There are a number of different ways to measure or assess performance on these criteria. Some are able to be quantitatively measured, while others may require the use of value judgements. This thesis used the Disability-Adjusted Life Year (DALY) metric for quantifying effectiveness during the testing of different MCDA models. This thesis reviews the MCDA process and the food safety specific MCDA literature. There are different ways of conducting MCDA. In particular, there are a large number of models available for the aggregation phase; the process of converting model inputs, in the form of criteria scores and weights, into model recommendations. This thesis has described and reviewed the main classes of model. The literature review and interview process guided the construction and testing of three classes of MCDA model; the Weighted Sum, Analytic Hierarchy Process (AHP) and PROMETHEE models. These models were selected due to their having different characteristics and degrees of complexity, as well as their popularity in the food safety and Health Technology Assessment (HTA) literature. Models were tested on the problem of selecting the most appropriate intervention to address the historic Campylobacter in poultry problem in New Zealand during the mid-2000s. Experimentation was conducted on these models to explore how different configurations utilise data and produce model outputs. This experimentation included: •Varying the format of input data •Exploring the effects of including/excluding criteria •Methods for sensitivity analysis •Exploring how data inputs and outputs can be elicited and presented using visual tools • Creating and using hybrid MCDA models The results of this testing are a key output of this thesis and provide insight into how such models might be used in food safety decision-making. The conclusions reached throughout this research phase can be classified into one of two broad groups: •Those relating to MCDA as a holistic process/methodology for decision-making •Those relating to the specific models and mathematical procedures for generating numerical inputs and outputs This thesis demonstrates that food-safety decision-making is a true multi-criteria, multi-stakeholder problem. The different stakeholders in food-safety decision-making do not always agree on the value and importance of the attributes used to evaluate competing intervention schemes. MCDA is well suited to cope with such complexity as it provides a structured methodology for the systematic and explicit identification, recording and aggregation of qualitative and quantitative information, gathered from a number of different sources, with the output able to serve as a basis for decision-making. The MCDA models studied in this thesis range from models that are simple and quick to construct and use, to more time consuming models with sophisticated algorithms. The type of model used for MCDA, the way these models are configured and the way inputs are generated or elicited can have a significant impact on the results of an analysis. This thesis has identified a number of key methodological considerations for those looking to employ one of the many available MCDA models. These considerations include: •Whether a model can accommodate the type and format of input data •The desired degree of compensation between criteria (i.e. full, partial or no compensation) •Whether the goal of an analysis is the identification of a ‘best’ option(s), or the facilitation of discussion, and communication of data •The degree of transparency required from a model and whether an easily understood audit trail is desired/required •The desired output of a model (e.g. complete or partial ranking). This thesis has also identified a number of practical considerations when selecting which model to use in food safety decision-making. These include: •The amount of time and energy required of stakeholders in the generation of data inputs (elicitation burden) •The degree of training required for participants •How data inputs are to be elicited and aggregated in different group decision-making environments •The availability of MCDA software for assisting an analysis Considering the above points will assist users in selecting a suitable MCDA model that meets their requirements and constraints. This thesis provides original and practical knowledge to assist groups or individuals looking to employ MCDA in the context of food-safety intervention decision-making. This research could also serve as a guide for those looking to evaluate a different selection of MCDA models.

The Internet of Things (IoT) has seen a huge growth spurt in the last few years which has resulted in the need for more standardised IoT technology. Because of this, numerous IoT platforms have sprung up that offer a variety of features and use different technologies which may not necessarily be compliant with each other or with other technologies. Companies that wish to enter theIoT market are in constant need to find the most suitable IoT platform for their business and have a certain set of requirements that need to be fulfilled by the IoT platforms in order for the application to be fully functional. The problem that this thesis project is trying to address is a standardised procedure for selecting the IoT platforms. The project aims to suggest a list of requirements derived from the available IoT architecture models, that must be followed by IoT applications in general, and a subset of these requirements may be specified by the companies as essentials for their application. This thesis project also aims at development of a Web platform to automate this process, by listing the requirements on this website and allowing companies to input their choices,and accordingly show them the list of IoT platforms that comply with their input requirements. A simple Weighted Sum Model is used to rank the search result in order to prioritise the IoT platforms in order of the features that they provide. This thesis project also infers the best IoT architectural model available based on a comparative study of three major IoT architectures with respect to the requirements proposed. Hence the project concludes that this Web platform will ease the process of searching for the right IoT platform andthe companies can therefore make an informed decision about the kind of IoT platform that they should use, thereby reducing their time spent on market research and hence their time-to-market.

There are many possible tools to develop mobile applications with. Choosing a development tool is done by considering many different factors, and the choice is currently done, in many cases, arbitrarily. For this project, a decision model is designed to ease the process of choosing a development tool. A survey was conducted to examine how people using different smartphone platforms discover and download applications. 94 responses were collected, showing that approximately 50% of Android-users found mobile applications by using search engines or browsers. The corresponding number was approximately 30% for iOS-users. A usability test was conducted to discover the differences in user experience between Progressive Web Applications and native applications. 18 usability tests were conducted comparing the same product developed as a Progressive Web Application and a native application. A majority of the participants had a technical background. Both Android and iOS devices were included in the tests. The results indicated that end-users notice when an application is not natively developed. The effect on the user experience is combined with other technical differences and applied to the decision model. This model was designed to predict if a native application, a Progressive Web Application or a React Native application is the most favourable to develop for a specific scenario. The final model could, according to consultants at the stakeholder Slagkryssaren AB, with good accuracy predict when the different development tools should be used. The model could be used as a discussion tool in the first stages of the development process of an application. / Det finns många möjliga verktyg för att utveckla mobila applikationer. Valet av utvecklingsverktyg görs genom att överväga många olika faktorer, och görs idag i många fall högst godtyckligt. För det här projektet designades en beslutsmodell som förenklar processen av att välja ett utecklingsverktyg. En undersökning gjordes för att undersöka hur användare av olika smartphone- plattformar upptäcker och laddar ner applikationer. 94 svar samlades, svaren visade att ungefär 50% av Android-användare hittade mobila applikationer genom internetsökningar eller webbläsare. Denna siffran var ungefär 30% för iOS-användare. Ett användarbarhetstest utfördes för att finna skillnader i användarupplevelse mellan progressiva webbapplikationer och native-applikationer. En majoritet av deltagarna hade en teknisk bakgrund. Både Android- och iOS-enheter testades. Resultatet tydde på att slutanvändare la märke till när en applikation inte utvecklades som en native-applikation. Effekten på användarvänligheten, kombinerat med tekniska skillnader mellan verktygen, tillämpades på beslutsmodellen. Modellen designades för att förutse om en native-applikation, en progressiva webbapplikation eller en React Native- applikation är mest fördelaktig att utveckla i ett specifikt scenario. Den slutgiltiga modellen kunde, enligt konsulter på uppdragsgivaren Slagkryssaren AB, med god precision avgöra när de olika utvecklingsverktygen bör nyttjas. Modellens användning blev som ett diskussionsverktyg i de första stadierna av processen med att välja utvecklingsvektyg.