Business intelligence viewpoint on managerial decision-making : Ill-structured problems and decision support systems

Vaikka liiketoimintatiedon hallintaa sekä johdon päätöksentekoa on tutkittu laajasti, näiden kahden käsitteen yhteisvaikutuksesta on olemassa hyvin rajallinen määrä tutkimustietoa. Tulevaisuudessa aiheen tärkeys korostuu, sillä olemassa olevan datan määrä kasvaa jatkuvasti. Yritykset tarvitsevat jatkossa yhä enemmän kyvykkyyksiä sekä resursseja, jotta sekä strukturoitua että strukturoimatonta tietoa voidaan hyödyntää lähteestä riippumatta. Nykyiset Business Intelligence -ratkaisut mahdollistavat tehokkaan liiketoimintatiedon hallinnan osana johdon päätöksentekoa. Aiemman kirjallisuuden pohjalta, tutkimuksen empiirinen osuus tunnistaa liiketoimintatiedon hyödyntämiseen liittyviä tekijöitä, jotka joko tukevat tai rajoittavat johdon päätöksentekoprosessia. Tutkimuksen teoreettinen osuus johdattaa lukijan tutkimusaiheeseen kirjallisuuskatsauksen avulla. Keskeisimmät tutkimukseen liittyvät käsitteet, kuten Business Intelligence ja johdon päätöksenteko, esitetään relevantin kirjallisuuden avulla – tämän lisäksi myös dataan liittyvät käsitteet analysoidaan tarkasti. Tutkimuksen empiirinen osuus rakentuu tutkimusteorian pohjalta. Tutkimuksen empiirisessä osuudessa paneudutaan tutkimusteemoihin käytännön esimerkein: kolmen tapaustutkimuksen avulla tutkitaan sekä kuvataan toisistaan irrallisia tapauksia. Jokainen tapaus kuvataan sekä analysoidaan teoriaan perustuvien väitteiden avulla – nämä väitteet ovat perusedellytyksiä menestyksekkäälle liiketoimintatiedon hyödyntämiseen perustuvalle päätöksenteolle. Tapaustutkimusten avulla alkuperäistä tutkimusongelmaa voidaan analysoida tarkasti huomioiden jo olemassa oleva tutkimustieto. Analyysin tulosten avulla myös yksittäisiä rajoitteita sekä mahdollistavia tekijöitä voidaan analysoida. Tulokset osoittavat, että rajoitteilla on vahvasti negatiivinen vaikutus päätöksentekoprosessin onnistumiseen. Toisaalta yritysjohto on tietoinen liiketoimintatiedon hallintaan liittyvistä positiivisista seurauksista, vaikka kaikkia mahdollisuuksia ei olisikaan hyödynnetty. Tutkimuksen merkittävin tulos esittelee viitekehyksen, jonka puitteissa johdon päätöksentekoprosesseja voidaan arvioida sekä analysoida. Despite the fact that the literature on Business Intelligence and managerial decision-making is extensive, relatively little effort has been made to research the relationship between them. This particular field of study has become important since the amount of data in the world is growing every second. Companies require capabilities and resources in order to utilize structured data and unstructured data from internal and external data sources. However, the present Business Intelligence technologies enable managers to utilize data effectively in decision-making. Based on the prior literature, the empirical part of the thesis identifies the enablers and constraints in computer-aided managerial decision-making process. In this thesis, the theoretical part provides a preliminary understanding about the research area through a literature review. The key concepts such as Business Intelligence and managerial decision-making are explored by reviewing the relevant literature. Additionally, different data sources as well as data forms are analyzed in further detail. All key concepts are taken into account when the empirical part is carried out. The empirical part obtains an understanding of the real world situation when it comes to the themes that were covered in the theoretical part. Three selected case companies are analyzed through those statements, which are considered as critical prerequisites for successful computer-aided managerial decision-making. The case study analysis, which is a part of the empirical part, enables the researcher to examine the relationship between Business Intelligence and managerial decision-making. Based on the findings of the case study analysis, the researcher identifies the enablers and constraints through the case study interviews. The findings indicate that the constraints have a highly negative influence on the decision-making process. In addition, the managers are aware of the positive implications that Business Intelligence has for decision-making, but all possibilities are not yet utilized. As a main result of this study, a data-driven framework for managerial decision-making is introduced. This framework can be used when the managerial decision-making processes are evaluated and analyzed.

Scheduling dynamic dataflow graphs with model checking

With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

Comparison and problems between Traditional and Agile software development methods

In today’s world because of the rapid advancement in the field of technology and business, the requirements are not clear, and they are changing continuously in the development process. Due to those changes in the requirements the software development becomes very difficult. Use of traditional software development methods such as waterfall method is not a good option, as the traditional software development methods are not flexible to requirements and the software can be late and over budget. For developing high quality software that satisfies the customer, the organizations can use software development methods, such as agile methods which are flexible to change requirements at any stage in the development process. The agile methods are iterative and incremental methods that can accelerate the delivery of the initial business values through the continuous planning and feedback, and there is close communication between the customer and developers. The main purpose of the current thesis is to find out the problems in traditional software development and to show how agile methods reduced those problems in software development. The study also focuses the different success factors of agile methods, the success rate of agile projects and comparison between traditional and agile software development.

Nonconventional amide bond formation catalysis: programming enzyme specificity with substrate mimetics

This article reports on the design and characteristics of substrate mimetics in protease-catalyzed reactions. Firstly, the basis of protease-catalyzed peptide synthesis and the general advantages of substrate mimetics over common acyl donor components are described. The binding behavior of these artificial substrates and the mechanism of catalysis are further discussed on the basis of hydrolysis, acyl transfer, protein-ligand docking, and molecular dynamics studies on the trypsin model. The general validity of the substrate mimetic concept is illustrated by the expansion of this strategy to trypsin-like, glutamic acid-specific, and hydrophobic amino acid-specific proteases. Finally, opportunities for the combination of the substrate mimetic strategy with the chemical solid-phase peptide synthesis and the use of substrate mimetics for non-peptide organic amide synthesis are presented.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Optimization and Measuring Techniques for Collect-and-Place Machines in Printed Circuit Board Industry

This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.

Developing an introductory object-oriented programming course

The state of the object-oriented programming course in Lappeenranta University of Technology had reached the point, where it required changes to provide better learning opportunities and thus the learning outcomes. Based on the student feedback the course was partially dated and ineffective. The components of the course were analysed and the ineffective elements were removed and new methods were introduced to improve the course. The major changes included the change from traditional teaching methods to reverse classroom method and the use of Java as the programming language. The changes were measured by the student feedback, lecturer’s observations and comparison to previous years. The feedback suggested that the changes were successful; the course received higher overall grade than before.

Gender-related pathways for behavior problems in the offspring of alcoholic fathers

The objective of the present study was to examine gender differences in the influence of paternal alcoholism on children's social-emotional development and to determine whether paternal alcoholism is associated with a greater number of externalizing symptoms in the male offspring. From the Mannheim Study of Risk Children, an ongoing longitudinal study of a high-risk population, the developmental data of 219 children [193 (95 boys and 98 girls) of non-alcoholic fathers, non-COAs, and 26 (14 boys, 12 girls) of alcoholic fathers, COAs] were analyzed from birth to the age of 11 years. Paternal alcoholism was defined according to the ICD-10 categories of alcohol dependence and harmful use. Socio-demographic data, cognitive development, number and severity of behavior problems, and gender-related differences in the rates of externalizing and internalizing symptoms were assessed using standardized instruments (IQ tests, Child Behavior Checklist questionnaire and diagnostic interviews). The general linear model analysis revealed a significant overall effect of paternal alcoholism on the number of child psychiatric problems (F = 21.872, d.f. = 1.217, P < 0.001). Beginning at age 2, significantly higher numbers of externalizing symptoms were observed among COAs. In female COAs, a pattern similar to that of the male COAs emerged, with the predominance of delinquent and aggressive behavior. Unlike male COAs, females showed an increase of internalizing symptoms up to age 11 years. Of these, somatic complaints revealed the strongest discriminating effect in 11-year-old females. Children of alcoholic fathers are at high risk for psychopathology. Gender-related differences seem to exist and may contribute to different phenotypes during development from early childhood to adolescence.

A SOA-based Framework for Multi-Devices and Multi-Platform User Interfaces

This thesis reports investigations on applying the Service Oriented Architecture (SOA) approach in the engineering of multi-platform and multi-devices user interfaces. This study has three goals: (1) analyze the present frameworks for developing multi-platform and multi-devices applications, (2) extend the principles of SOA for implementing a multi-platform and multi-devices architectural framework (SOA-MDUI), (3) applying and validating the proposed framework in the context of a specific application. One of the problems addressed in this ongoing research is the large amount of combinations for possible implementations of applications on different types of devices. Usually it is necessary to take into account the operating system (OS), user interface (UI) including the appearance, programming language (PL) and architectural style (AS). Our proposed approach extended the principles of SOA using patterns-oriented design and model-driven engineering approaches. Synthesizing the present work done in these domains, this research built and tested an engineering framework linking Model-driven Architecture (MDA) and SOA approaches to developing of UI. This study advances general understanding of engineering, deploying and managing multi-platform and multi-devices user interfaces as a service.

Genetic, prenatal and postnatal determinants of weight gain and obesity in young children – The STEPS Study

Genetic, Prenatal and Postnatal Determinants of Weight Gain and Obesity in Young Children – The STEPS Study University of Turku, Faculty of Medicine, Department of Paediatrics, University of Turku Doctoral Program of Clinical Investigation (CLIPD), Turku Institute for Child and Youth Research. Conditions of being overweight and obese in childhood are common health problems with longlasting effects into adulthood. Currently 22% of Finnish boys and 12% of Finnish girls are overweight and 4% of Finnish boys and 2% of Finnish girls are obese. The foundation for later health is formed early, even before birth, and the importance of prenatal growth on later health outcomes is widely acknowledged. When the mother is overweight, had high gestational weight gain and disturbances in glucose metabolism during pregnancy, an increased risk of obesity in children is present. On the other hand, breastfeeding and later introduction of complementary foods are associated with a decreased obesity risk. In addition to these, many genetic and environmental factors have an effect on obesity risk, but the clustering of these factors is not extensively studied. The main objective of this thesis was to provide comprehensive information on prenatal and early postnatal factors associated with weight gain and obesity in infancy up to two years of age. The study was part of the STEPS Study (Steps to Healthy Development), which is a follow-up study consisting of 1797 families. This thesis focused on children up to 24 months of age. Altogether 26% of boys and 17% of girls were overweight and 5% of boys and 4% of girls were obese at 24 months of age according to New Finnish Growth references for Children BMI-for-age criteria. Compared to children who remained normal weight, the children who became overweight or obese showed different growth trajectories already at 13 months of age. The mother being overweight had an impact on children’s birth weight and early growth from birth to 24 months of age. The mean duration of breastfeeding was almost 2 months shorter in overweight women in comparison to normal weight women. A longer duration of breastfeeding was protective against excessive weight gain, high BMI, high body weight and high weight-for-length SDS during the first 24 months of life. Breast milk fatty acid composition differed between overweight and normal weight mothers, and overweight women had more saturated fatty acids and less n-3 fatty acids in breast milk. Overweight women also introduced complementary foods to their infants earlier than normal weight mothers. Genetic risk score calculated from 83 obesogenic- and adiposity-related single nucleotide polymorphisms (SNPs) showed that infants with a high genetic risk for being overweight and obese were heavier at 13 months and 24 months of age than infants with a low genetic risk, thus possibly predisposing to later obesity in obesogenic environment. Obesity Risk Score showed that children with highest number of risk factors had almost 6-fold risk of being overweight and obese at 24 months compared to children with lowest number of risk factors. The accuracy of the Obesity Risk Score in predicting overweight and obesity at 24 months was 82%. This study showed that many of the obesogenic risk factors tend to cluster within children and families and that children who later became overweight or obese show different growth trajectories already at a young age. These results highlight the importance of early detection of children with higher obesity risk as well as the importance of prevention measures focused on parents. Keywords: Breastfeeding, Child, Complementary Feeding, Genes, Glucose metabolism, Growth, Infant Nutrition Physiology, Nutrition, Obesity, Overweight, Programming