Entrepreneurship and business training programs have been created and administered throughout the world and particularly in developing economies to help entrepreneurs open new businesses and grow their current businesses. Evaluations of these programs have shown that most of them successfully help entrepreneurs expand their knowledge and understanding of business principles and practices, but few entrepreneurs will then apply or transfer what they learn into their businesses. Without many entrepreneurs making changes in how they run their businesses, it is no surprise that these training programs generally show little impact on sales or profits. This research explores how business training programs in developing economies can help entrepreneurs go beyond just learning about business principles to making changes in their businesses based on those principles. Put simply, this research explores how training programs can help entrepreneurs act on what they learn. The research for this dissertation is presented in three articles. Article 1 includes a review and analysis of findings from a decade of evaluations and research on entrepreneurship training programs in developing economies around the world. In this analysis, I identified factors that have been found to positively affect training transfer, and then based on these findings I developed a theoretical framework of how training transfer can be facilitated. Article 2 is a multiple case analysis of seven trainers from two different entrepreneurship training programs based in Lima, Peru. This article includes an analysis of six months of in-field observations and interviews conducted in Peru, revealing several challenges trainers face while helping entrepreneurs apply what they learn as well as strategies the trainers use in their efforts to overcome those challenges. Article 3 includes a field experiment to test if using learning contracts in a training program will help more entrepreneurs begin following new business practices. This article also includes a quasi-experimental impact evaluation of the training program as a whole on entrepreneurs' business knowledge, application of business principles, and sales and expenses. The learning contracts showed some impact but not on all business practices. The training program as a whole had a statistically significant impact on knowledge and application but the impact on sales was not statistically significant.

Understanding the motives behind Islamist terrorist attacks is not only relevant for the field of politics but preoccupies research within academia. One of the most debated is certainly the role of religion. This thesis addresses this gap by asking the question, what role does religion play in the radicalization processes of Islamist terrorists attacking western targets? It combines an emotional approach to religion, with religiosity as defined by religious practices in everyday life and by the self-perception of individuals themselves. It further argues that when religion is perceived as emotionally meaningful, this results in spiritual selective incentives, individuals perceive as worth engaging in terrorism. Using process tracing and structured focused comparison, it conducts an analysis of the radicalisation processes of three individuals, within a comparative case study design, using autobiographies, court documents, previous case studies and news articles. The results show that the individuals perceived their emotions in a religious context and support is found for the hypothesis that justification for violence emerges out of religious motives. The Thesis concludes that religion does have explanatory power as an independent variable, but causal relationships are complex. This leaves room for further research which focuses more on religion as an independent variable.

Purpose: To explore the influence of marketing AI on marketing managers' attention allocation to leverage customer relationships in different business-to-business contexts. Method: Abductive approach and multiple case study, data collection was made by qualitative semi-structured interviews and secondary data collection. Conclusion: The study identified both similarities and differences within three main categories across two industrial clusters where marketing AI effect marketing managers’ attention allocation in B2B relationships. Marketing AI is shown to affect B2B relationships through marketing managers’ attentional selection towards efficiencies and/or new opportunities. Marketing AI is shown to influence marketing managers’ attention allocation by distorting the focus of attention on relational dynamics by introducing automated or augmented marketing AI solutions into the relationship.

Partiellt bortfall är en vanligt förekommande felkälla vid statistiska undersökningar. Med partiellt bortfall avses avsaknad av vissa variabelvärden för ett observationsobjekt, något som riskerar leda till förlust av statistisk styrka och skeva parameterskattningar. Ett stort antal metoder har utvecklats för att hantera denna problematik, och syftet med denna uppsats är att undersöka vilken effekt några av dessa metoder har på parameterskattningarna i en logistisk regressionsmodell, och huruvida dessa metoder är lämpliga att tillämpa på aktuellt datamaterial. De metoder som inkluderats i denna studie är complete case analysis, MICE och missForest. För ändamålet simuleras partiellt bortfall av olika omfattningar och under olika bortfallsmekanismer i ett verkligt datamaterial som består av 2987 observationer och fem variabler. Metoderna utvärderas sedan med avseende på normalized root mean squared error (NRMSE), samt genom att undersöka hur de regressionskoefficienter som skattats med de imputerade datamaterialen avviker från de regressionskoefficienter som skattats med det kompletta, observerade datamaterialet. missForest resulterar i lägst NRMSE. I den efterföljande logistiska regressionsanalysen resulterar dock MICE i betydligt lägre bias än missForest. / Missing data is a common problem in research and can lead to loss of statistical power and bias in parameter estimates. Numerous methods have been developed for dealing with missing data, and the aim of this thesis is to evaluate how a number of these methods affect the parameter estimates in a logistic regression model, and whether these methods are suitable for the data in question. The methods included in this study are complete case analysis, MICE and missForest. For the purpose of evaluating the methods, missing values in varying proportions and under different missing mechanisms are generated in a real dataset consisting of 2987 observations and five variables. The performance of the methods is assessed by normalized root mean squared error (NRMSE), and by comparing the regression coefficients estimated using the original, true data set with the regression coefficients estimated using imputed data sets. missForest results in the lowest NRMSE. In the subsequent logistic regression analysis, however, MICE results in considerably lower bias than missForest.

På SSI-Schäfer System International i Norrköping pågår ständiga förbättringar och projektför att effektivisera produktionen hos kunden. Ett förbättringsområde som varit särskiltintressant under senare tid har varit produktionsflödet mellan lagerhanteringssystemet(shuttlesystemet) och packningsstationerna och på packningsstationerna. Den här rapportenpresenterar en fallstudie om förbättringspotential och åtgärder för förbättringspotential,baserat på befintlig företagsdokumentation och intervjuer på företaget, samt kartläggningarav produktionsflödet hos kunden. Genomförandet av studien är uppdelat i fyra huvudfaser, I.Kartläggning av produktionen, II. Presentation av identifierade förbättringspotential ochslöseri, III. Identifiering av rotorsaker till förbättringspotential och slöseri och IV.Framtagning av förbättringsförslag. De två första faserna är att förstå produktionen ochpresentera identifierade förbättringspotential och slöseri. I tredje fasen identifieras rotorsakertill förbättringspotential och slöseri, i fjärde fasen presenteras förbättringsförslag.Presentation av identifierade förbättringspotential och slöseri resulterade i att projektet kundefokusera på 5 viktiga förbättringspotentialer, 1. Deadlocks (dödläge), 2. Backar som fastnar,3. Dra stora kartongen, 4. Stopp sekvenserare 1, 5. Skrivare vid GTP-stationer(packningsstationer). Identifiering av rotorsaker till förbättringspotential och slöserigenomfördes med hjälp av Ishikawadiagram för varje förbättringspotential tillsammans medoperatörer på GTP-stationerna och RM-teamet. Detta resulterade i 1. Brist på vänteplatser, 2.Viktfördelning i backarna, 3. Operatörerna saknar åtkomst till transportbandet, 4. Backarloopas inte, 5. Placering av skrivare. För att ta itu med förbättringspotentialen föreslogsföljande förbättringar: 1. Bygg en till lift, 2. Montera bricka och plugg, 3. Justeraautobagmaskinen, 4. Cirkulera (loopa) backarna, 5. Placera skrivare på bordsförlängning ellerhylla närmare operatörer vid GTP-stationer. Det rekommenderas att företaget fortsätter sittarbete genom att ytterligare undersöka föreslagna förbättringsförslag för att implementeraförbättringsförslag för att reducera förbättringspotentialen och slöserier. / At SSI-Schäfer System International in Norrköping, continuous improvements and projectsare underway to streamline the customer's production. An area of improvement that has beenparticularly interesting in recent times has been the production flow between the warehousemanagement system (the shuttle system) and the packing stations and at the packing stations.This report presents a case study on improvement potential and measures for improvementpotential, based on existing company documentation and interviews at the company, as wellas surveys of the production flow at the customer. The implementation of the study is dividedinto four main phases, I. Mapping of production, II. Presentation of identified potential forimprovement and waste, III. Identification of rotor causes for improvement potential andwaste and IV. Development of improvement proposals. The first two phases are to understandthe production and present identified potential for improvement and waste. In the third phase,rotor causes for improvement potential and waste are identified, in the fourth phase,improvement proposals are presented.Presentation of identified improvement potential and waste resulted in the project being ableto focus on 5 important improvement potentials, 1. Deadlocks, 2. Tote boxes that get stuck, 3.Pull the large box, 4. Stop sequencer 1, 5. Printers at GTP-stations (packing stations).Identification of rotor causes for improvement potential and waste was carried out usingIshikawa diagrams for each improvement potential together with operators at theGTP-stations and the RM-team. This resulted in 1. Lack of transferpoints, 2. Weightdistribution in the tote boxes, 3. The operators do not have access to the conveyor belt, 4.Tote boxes are not looped, 5. Placement of printers. To address the potential forimprovement, the following improvements were proposed: 1. Build another lift, 2. Mountwasher and plug, 3. Adjust the autobag machine, 4. Loop the tote boxes, 5. Place printers ontable extensions or shelf closer to operators at GTP-stations. It is recommended that thecompany continue its work by further examining proposed improvement proposals toimplement improvement proposals to reduce the potential for improvement and waste.

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The vehicle routing problem (VRP) determines preferred vehicle routes to visit multiple customer locations from a depot location based on a defined objective function. The VRP is an NP-hard network optimization problem that is challenging to solve to optimality. Over the past 60 years, multitudes of heuristics and metaheuristics have been developed in order to minimize the computational burden of solving the VRP. In order to compare the performance of VRP heuristics, researchers have developed bench-marking datasets. These datasets, however, lack properties found in industry datasets. In this dissertation, we explore how properties of industry datasets influence VRP heuristics and objective functions. In Chapter 2, we quantify and compare features of bench-marking and industry datasets. In order to determine if these features influence heuristic performance, we conduct extensive computational runs on three heuristics, Tabu Search, Genetic Algorithm, and Clarke-Wright Savings Procedure, on standard and industry datasets. In Chapter 3, we derive worst-case analysis on how VRP objective functions and metrics relate to one another. These bounds depend on properties of customer locations. These bounds illustrate how customer locations can influence how different routes behave for different routing metrics. Finally, in Chapter 4, we improve two VRP heuristics, Clarke-Wright Saving Procedure and Hybrid Genetic Search Algorithm, by developing new enhancements to the algorithms. These enhancements rely on certain properties of the datasets in order to perform well. Thus, these heuristics perform better on specific VRP dataset types. / Doctor of Philosophy / The vehicle routing problem (VRP) creates vehicle routes that have the shortest travel distance. The routes determine how vehicles should visit multipl customer locations, to deliver or pickup goods, and return to a depot location. While explaining what the VRP entails is simple, the VRP is actually very difficult for even the most sophisticated algorithms on the best computers to solve. Over the past 60 years, many algorithms have been developed in order to more easily and quickly solve the VRP. In order to compare the performance of VRP algorithms, researchers have developed bench-marking datasets. However, these datasets lack properties of datasets found in industry. In this dissertation, we look to connect the disconnect between industry and bench-marking datasets by 1) comparing feature differences between these two types of datasets, 2) determining if differences in datasets imply differences in algorithm performance, 3) proving how problem differences influence VRP routes, and 4) enhancing existing VRP algorithms to perform better on specific VRP dataset types.

The main contributions of this work are applications of robust control and analysis methods to complex engineering systems, namely, small fixed-wing unmanned aircraft systems (UAS). Multiple path-following controllers for a small fixed-wing Telemaster UAS are presented, including a linear parameter-varying (LPV) controller scheduled over path curvature. The controllers are synthesized based on a lumped path-following and UAS dynamic system, effectively combining the six degree-of-freedom aircraft dynamics with established parallel transport frame virtual vehicle dynamics. The robustness and performance of these controllers are tested in a rigorous MATLAB simulation environment that includes steady winds, turbulence, measurement noise, and delays. After being synthesized off-line, the controllers allow the aircraft to follow prescribed geometrically defined paths bounded by a maximum curvature. The controllers presented within are found to be robust to the disturbances and uncertainties in the simulation environment. A robust analysis framework for mathematical validation of flight control systems is also presented. The framework is specifically developed for the complete uncertainty characterization, quantification, and analysis of small fixed-wing UAS. The analytical approach presented within is based on integral quadratic constraint (IQC) analysis methods and uses linear fractional transformations (LFTs) on uncertainties to represent system models. The IQC approach can handle a wide range of uncertainties, including static and dynamic, linear time-invariant and linear time-varying perturbations. While IQC-based uncertainty analysis has a sound theoretical foundation, it has thus far mostly been applied to academic examples, and there are major challenges when it comes to applying this approach to complex engineering systems, such as UAS. The difficulty mainly lies in appropriately characterizing and quantifying the uncertainties such that the resulting uncertain model is representative of the physical system without being overly conservative, and the associated computational problem is tractable. These challenges are addressed by applying IQC-based analysis tools to analyze the robustness of the Telemaster UAS flight control system. Specifically, uncertainties are characterized and quantified based on mathematical models and flight test data obtained in house for the Telemaster platform and custom autopilot. IQC-based analysis is performed on several time-invariant H∞ controllers along with various sets of uncertainties aimed at providing valuable information for use in controller analysis, controller synthesis, and comparison of multiple controllers. The proposed framework is also transferable to other fixed-wing UAS platforms, effectively taking IQC-based analysis beyond academic examples to practical application in UAS control design and airworthiness certification. IQC-based analysis problems are traditionally solved using convex optimization techniques, which can be slow and memory intensive for large problems. An oracle for discrete-time IQC analysis problems is presented to facilitate the use of a cutting plane algorithm in lieu of convex optimization in order to solve large uncertainty analysis problems relatively quickly, and with reasonable computational effort. The oracle is reformulated to a skew-Hamiltonian/Hamiltonian eigenvalue problem in order to improve the robustness of eigenvalue calculations by eliminating unnecessary matrix multiplications and inverses. Furthermore, fast, structure exploiting eigensolvers can be employed with the skew-Hamiltonian/Hamiltonian oracle to accurately determine critical frequencies when solving IQC problems. Applicable solution algorithms utilizing the IQC oracle are briefly presented, and an example shows that these algorithms can solve large problems significantly faster than convex optimization techniques. Finally, a large complex engineering system is analyzed using the oracle and a cutting-plane algorithm. Analysis of the same system using the same computer hardware failed when employing convex optimization techniques. / Ph. D.

Ziel: Einzellfallanalyse der Totgeburten hinsichtlich ihrer Vermeidbarkeit und Vermeidungsfaktoren als ein wesentlicher Anteil der internen Qualitätssicherung. Methode: Im Zeitraum von 1996 bis 2000 wurden nach dem Ausschluss der Abbrüche bei Fehlbildungen 100 Totgeburten bei 99 Entbindungen mit einem Geburtsgewicht von mindestens 500 g in die Analyse miteinbezogen. Ergebnisse: Die korrigierte Totgeburtenrate lag bei 5,23 Totgeburten/1000 Geburten. Der Anteil von totgeborenen Mehrlingen (11%) war 4fach so hoch dem Normalkollektiv (2,8%) gegenüber. Die relativ große Zahl der zwischen 20-23 vollendeten SSW (22%) und vor 28 vollendeten SSW (36%) auftretenden intrauterinen Fruchttode in unserer Untersuchung weist auf eine Population mit einem großen Anteil an früher Frühgeburtlichkeit hin. Die meisten Totgeburten (38%) befanden sich in der Gewichtsgruppe 500-999 g. Zwei Drittel (14/21) der Kinder mit SGA wurden ab 32 SSW und knapp die Hälfte (10/21) am Entbindungstermin mit 37 bis 41 SSW geboren. Die Todesursachen waren Plazentainsuffizienz (31%), AIS (21%), vorzeitige Plazentalösung (20%), Nabelschnurkomplikationen (7%), FFTS (2%) und Hydrops fetalis (2%). Das Amnioninfektionssyndrom (AIS) als Todesursache trat häufiger in frühen Schwangerschaftswochen (20-24 SSW: n= 17 von 21 Fällen mit AIS als Todesursache) auf. Nabelschnurkomplikationen fanden sich dagegen in späteren Schwangerschaftswochen (34-40 SSW: n=7). Unabhängig von den Todesursachen waren 51% der Totgeburten nach unserer Analyse nicht vermeidbar, 12% waren intern vermeidbar und 37% möglicherweise vermeidbar durch die Frauenärzte/Innen bzw. die Patientinnen selber. Eine gute Schwangerschaftsvorsorge, eine ausreichende fetale Überwachung und ein gutes Geburtsmanagement hätten viele Totgeburten vermeiden können. Die Beteiligung der Schwangeren ist dabei die Grundvoraussetzung. Schlussfolgerung: Die Betrachtung der Todesursache allein ist zur Beurteilung der Vermeidbarkeit nicht ausreichend. Das Verständnis der Ereignisse, die zu den Totgeburten führten, ist der Ausgangspunkt für eine kritische Auswertung. / Objective: The avoidability and the preventive factors relating to stillbirths were evaluated as an important part of internal quality control. Methods: After exclusion of interruptions because of fetal malformations, the case records of 100 stillbirths with a minimal birth weight of 500 g from 99 deliveries in our clinic in the years 1996 till 2000 were retrospectively as single cases analysed. Results: The corrected rate of stillbirth was 5,23 per 1000 births. The proportion of the stillborn multiplets (11%) was 4 times higher then the proportion in the normal population (2,8%). That the stillbirths occurred preferentially between 20-23 menstrual weeks of pregnancy (22%) and before 28 menstrual weeks in our collection points out a population with a large proportion of earlier prematurity. Most of the stillbirths (38%) were born with a birth weight between 500-999 g. Two third (14/21) of the stillbirths from 32 menstrual weeks and almost the half of the stillbirths (10/21) between 37 till 41 menstrual weeks were born with small for gestational age (SGA). The principal causes of the stillbirths were placental insufficiency (31%), chorioamnionitis (21%), placental abruption (20%), cord complications (7%), twin-to-twin transfusion syndrom (2%) and hydrops (2%). The chorioamnionitis appeared more frequently in the early menstrual weeks (20-24 menstrual weeks: n=17 of 21 cases with chorioamnionitis). The cord complications on the contrary occurred in the late menstrual weeks (34-40 menstrual weeks: n=7). Independent of the causes of deaths, 51% of the stillbirths according to our analysis were not avoidable, 12% were internally preventable and 37% could be prevented by the external gynecologists or the patients themselves. A qualified and compliance to prenatal care, a sufficient fetal surveillance and a good management of delivery could avoid many stillbirths. The corporation of the pregnant patients is nevertheless prerequisite. Conclusion: The only consideration of the cause of death is not sufficient to evaluate the preventability of stilllbirths. The insight of the events that lead to stillbirths is the starting point for a critical interpretation.

In the United States, microenterprises, critical segment of the small business population, accounts for 110 million small businesses that source new jobs. Despite the increase in the number of created businesses in the U.S., more than 70% of microenterprise business owners are unsuccessful after 2 years. The multiple case study included 6 participants living in Houston, Texas, and intended to explore business strategies microenterprise event management owners used to succeed in business beyond 2 years. The conceptual framework that grounded the study was the 5-stage small business growth model and the 5-stage of the evolution of entrepreneurship theory. The data collection process consisted of interviews resulting in transcripts, review of company documents, and interview observations notes. The data analysis process while triangulating the data consisted of creating thematic codes, and clustering keywords, and ideas from the data. Development of visual aids assisted with organizing information, synthesizing, and generating new ideas. Text, word, and matrix coding queries were conducted and summarized for a cross-case analysis as relating to the interview questions. Thematic analysis and cross-case analysis revealed 3 major themes: customer relationship management, education/work experience, and promotional activities. Implications for social change include encouraging entrepreneurial and small business development programs to develop innovative curriculums that microenterprise business owners may benefit from to increase more business opportunities. An increase in microenterprises may help provide more employment opportunities that meet the needs of local communities, and improve socioeconomic conditions.