Forest inventory information needs in Northwest Russia

This research report applies the customer value hierarchy model to forestry in order to determine strategic options to enhance the value of LiDAR technology in Russian forestry. The study is conducted as a qualitative case study with semi-structured interviews as a main source of the primary data. The customer value hierarchy model constitutes a theoretical base for the research. Secondary data incorporates information on forest resource management, LiDAR technology and Russian forestry. The model is operationalised using forestry literature and forms a basis for analyses of primary data. Analyses of primary data coupled with comprehension of Russian forest inventory system and knowledge on global forest inventory have led to conclusions on the forest inventory methods selection criteria and the organizations that would benefit the most from LiDAR technology use. The report recommends strategic options for LiDAR technology’s value enhancement in Russian forestry. This work has been conducted as a part of the project ‘Finnish-Russian Forest Academy 2 - Exploiting and Piloting’, which has been supported financially by the South-East Finland- Russia ENPI CBC 2007-2014 Programme.

Show me your brain! Stories of interdisciplinary knowledge creation in practice. Experiences and observations from Aalto Design Factory, Finland.

This dissertation centres on the themes of knowledge creation, interdisciplinarity and knowledge work. My research approaches interdisciplinary knowledge creation (IKC) as practical situated activity. I argue that by approaching IKC from the practice-based perspective makes it possible to “deconstruct” how knowledge creation actually happens, and demystify its strong intellectual, mentalistic and expertise-based connotations. I have rendered the work of the observed knowledge workers into something ordinary, accessible and routinized. Consequently this has made it possible to grasp the pragmatic challenges as well the concrete drivers of such activity. Thus the effective way of organizing such activities becomes a question of organizing and leading effective everyday practices. To achieve that end, I have conducted ethnographic research of one explicitly interdisciplinary space within higher education, Aalto Design Factory in Helsinki, Finland, where I observed how students from different disciplines collaborated in new product development projects. I argue that IKC is a multi-dimensional construct that intertwines a particular way of doing; a way of experiencing; a way of embodied being; and a way of reflecting on the very doing itself. This places emphasis not only the practices themselves, but also on the way the individual experiences the practices, as this directly affects how the individual practices. My findings suggest that in order to effectively organize and execute knowledge creation activities organizations need to better accept and manage the emergent diversity and complexity inherent in such activities. In order to accomplish this, I highlight the importance of understanding and using a variety of (material) objects, the centrality of mundane everyday practices, the acceptance of contradictions and negotiations well as the role of management that is involved and engaged. To succeed in interdisciplinary knowledge creation is to lead not only by example, but also by being very much present in the very everyday practices that make it happen.

Customer Need Assessment for Differentiation in Building Information Modeling

Building Information Modeling – BIM is widely spreading in the Architecture, Engineering, and Construction (AEC) industries. Manufacturers of building elements are also starting to provide more and more objects of their products. The ideal availability and distribution for these models is not yet stabilized. Usual goal of a manufacturer is to get their model into design as early as possible. Finding the ways to satisfy customer needs with a superior service would help to achieve this goal. This study aims to seek what case company’s customers want out of the model and what they think is the ideal way to obtain these models and what are the desired functionalities for this service. This master’s thesis uses a modified version of lead user method to gain understanding of what the needs are in a longer term. In this framework also benchmarking of current solutions and their common model functions is done. Empirical data is collected with survey and interviews. As a result this thesis provides understanding that what is the information customer uses when obtaining a model, what kind of model is expected to be achieved and how is should the process optimally function. Based on these results ideal service is pointed out.

Modelling the simultaneous effects of intellectual capital and knowledge management on the organisational performance of Finnish companies

The aim of this study was to contribute to the current knowledge-based theory by focusing on a research gap that exists in the empirically proven determination of the simultaneous but differentiable effects of intellectual capital (IC) assets and knowledge management (KM) practices on organisational performance (OP). The analysis was built on the past research and theoreticised interactions between the latent constructs specified using the survey-based items that were measured from a sample of Finnish companies for IC and KM and the dependent construct for OP determined using information available from financial databases. Two widely used and commonly recommended measures in the literature on management science, i.e. the return on total assets (ROA) and the return on equity (ROE), were calculated for OP. Thus the investigation of the relationship between IC and KM impacting OP in relation to the hypotheses founded was possible to conduct using objectively derived performance indicators. Using financial OP measures also strengthened the dynamic features of data needed in analysing simultaneous and causal dependences between the modelled constructs specified using structural path models. The estimates were obtained for the parameters of structural path models using a partial least squares-based regression estimator. Results showed that the path dependencies between IC and OP or KM and OP were always insignificant when analysed separate to any other interactions or indirect effects caused by simultaneous modelling and regardless of the OP measure used that was either ROA or ROE. The dependency between the constructs for KM and IC appeared to be very strong and was always significant when modelled simultaneously with other possible interactions between the constructs and using either ROA or ROE to define OP. This study, however, did not find statistically unambiguous evidence for proving the hypothesised causal mediation effects suggesting, for instance, that the effects of KM practices on OP are mediated by the IC assets. Due to the fact that some indication about the fluctuations of causal effects was assessed, it was concluded that further studies are needed for verifying the fundamental and likely hidden causal effects between the constructs of interest. Therefore, it was also recommended that complementary modelling and data processing measures be conducted for elucidating whether the mediation effects occur between IC, KM and OP, the verification of which requires further investigations of measured items and can be build on the findings of this study.

Improving productivity by developing knowledge management practices for a consulting company

The objective of the research was to identify knowledge conversion states in consultancy sales and delivery processes for the company’s one business unit, to know where to store certain types of information and knowledge, and to create best practices for the company’s knowledge management activities in the selected business processes. The used research methodology was action research. The current business processes were analyzed by interviewing people involved in them. The results were documented and catego- rized, and based on them the target states of the processes were developed. Knowledge man- agement activities were integrated to the business processes. The main findings of the research were that roles and responsibilities in the processes were not clear to people, information systems did not fully support individuals and time was wasted searching for information and knowledge. There were also many variations of how the processes actually realized, which affected the overall quality of the process. The conclusions of the research were that knowledge management activities should be high- lighted in businesses where knowledge workers are the main assets of the company. Knowledge management practices can be supported by company culture, leadership and in- formation systems. However, one main factor is each individual’s willingness to share knowledge. By integrating knowledge management activities to business processes and hav- ing information systems supporting knowledge management, individual productivity can be improved.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Model of Big Data Failure: Review of Information System Failure

In the new age of information technology, big data has grown to be the prominent phenomena. As information technology evolves, organizations have begun to adopt big data and apply it as a tool throughout their decision-making processes. Research on big data has grown in the past years however mainly from a technical stance and there is a void in business related cases. This thesis fills the gap in the research by addressing big data challenges and failure cases. The Technology-Organization-Environment framework was applied to carry out a literature review on trends in Business Intelligence and Knowledge management information system failures. A review of extant literature was carried out using a collection of leading information system journals. Academic papers and articles on big data, Business Intelligence, Decision Support Systems, and Knowledge Management systems were studied from both failure and success aspects in order to build a model for big data failure. I continue and delineate the contribution of the Information System failure literature as it is the principal dynamics behind technology-organization-environment framework. The gathered literature was then categorised and a failure model was developed from the identified critical failure points. The failure constructs were further categorized, defined, and tabulated into a contextual diagram. The developed model and table were designed to act as comprehensive starting point and as general guidance for academics, CIOs or other system stakeholders to facilitate decision-making in big data adoption process by measuring the effect of technological, organizational, and environmental variables with perceived benefits, dissatisfaction and discontinued use.

Possibilities and challenges in utilization of information provided by Industrial Internet applications

Global digitalization has affected also industrial sector. A trend called Industrial Internet has been present for some years and established relatively steady position in businesses. Industrial Internet is also referred with the terminology Industry 4.0 and in consumer businesses IoT (Internet of Things). Eventually, trend consists of many traditionally proven technologies and concepts, such as condition monitoring, remote services, predictive maintenance and Internet customer portals. All these technologies and information related to them are estimated to change the rules of business in industrial sector. This may result even a new industrial revolution. This research has its focus on Industrial Internet products, services and applications. The study analyses four case companies and their digital service offerings. According to this analysis the comparison of these services is done to find out if there is still space for companies to gain competitive advantage through differentiation with these state of the art solutions. One of the case companies, Case Company Ltd., is working as a primary case company and a subscriber of this particular research. The research and results are analyzed primarily from this company’s perspective and need. In empirical part, the research clarifies how Case Company Ltd. has allocated its development resources through last five years. These allocations in certain categories are then compared to other case companies’ current customer offering and conclusions are made how the approach of different companies differ from each other. Existing theoretical knowledge of Industrial Internet is about to find its shape. In this research we take a look how the case company analysis and findings correlate with the existing knowledge and literature of the topic.

Social media in the purchasing of knowledge-intensive business services

The purpose of this thesis was to understand how industrial buyers utilize social media in the purchasing of knowledge-intensive business services. By combining theories from past research a theoretical framework was formed to visualize the role of the social media at the different stages of the purchasing process. The subject was approached from the industrial buyers’ perspective instead of the knowledge-intensive business firm. The research was conducted using two qualitative research methods: interviews and netnography. The selected interviewees have been involved in the decision-making unit for purchasing knowledge-intensive business services. Additionally all of them are using various social media. Based on the interviews social media is used merely to support decision-making. Some of the interviewees had also shared their own experiences about the service and collaboration with the service provider with other social media users. Based on the interviews two social media were chosen for closer examination. The findings from netnography support the results from the interviews. The outcome of knowledgeintensive business services is dependable of the professionals. Therefore the information is used during decision-making process to confirm the formed image of the service, and the professionals of the service provider. Information obtained from social media complements information provided by the supplier. Even though the interviewees had not themselves used social media to find information about the service during search process, finding from netnography suggest it to exist. Industrial buyers ask other users’ opinions and experience about the services, and receive recommendations to them. Some recommendations are given publicly, but more discreet information is shared in private conversations. Observations in social media show that industrial buyers might be exposed to triggers to promote problem recognition as well. Companies share news and successful customer cases through their social media profiles, which might affect the industrial buyers, but to confirm this requires further research. The industrial buyers’ use of social media during different purchasing processes of knowledgeintensive business services can be conceptualize based on the findings. This helps companies to create right content to their social media pages, and encourage professionals to develop their networks in social media.

Implementation of hospital-wide computer information system :a case study of this change process

This case study examines the impact of a computer information system as it was being implemented in one Ontario hospital. The attitudes of a cross section of the hospital staff acted as a barometer to measure their perceptions of the implementation process. With The Mississauga Hospital in the early stages of an extensive computer implementation project, the opportunity existed to identify staff attitudes about the computer system, overall knowledge and compare the findings with the literature. The goal of the study was to develop a greater base about the affective domain in the relationship between people and the computer system. Eight exploratory questions shaped the focus of the investigation. Data were collected from three sources: a survey questionnaire, focused interviews, and internal hospital documents. Both quantitative and qualitative data were analyzed. Instrumentation in the study consisted of a survey distributed at two points in time to randomly selected hospital employees who represented all staff levels.Other sources of data included hospital documents, and twenty-five focused interviews with staff who replied to both surveys. Leavitt's socio-technical system, with its four subsystems: task, structure, technology, and people was used to classify staff responses to the research questions. The study findings revealed that the majority of respondents felt positive about using the computer as part of their jobs. No apparent correlations were found between sex, age, or staff group and feelings about using the computer. Differences in attitudes, and attitude changes were found in potential relationship to the element of time. Another difference was found in staff group and perception of being involved in the decision making process. These findings and other evidence about the role of change agents in this change process help to emphasize that planning change is one thing, managing the transition is another.

An assessment of autism knowledge in the medical field

Once thought to be rare, pervasive developmental disorders (PDDs) are now recognized as the most common neurological disorders affecting children and one of the most common developmental disabilities (DD) in Canada (Autism Society of Canada, 2006). Recent reports indicate that PDDs currently affect 1 in 150 children (Centre for Disease Control and Prevention, 2007). The purpose of this research was to provide an understanding of medical resident and practicing physicians' basic knowledge regarding PDDs. With a population of children with PDDs who present with varying symptoms, the ability for medical professionals to provide general information, diagnosis, appropriate referrals, and medical care can be quite complex. A basic knowledge of the disorder is only a first step in providing adequate medical care to individuals with autism and their families. An updated version of Stone's (1987) Autism survey was administered to medical residents at four medical schools in Canada and currently practicing physicians at three medical schools and one community health network. As well, a group of professionals specializing in the field ofPDDs, participating in research and clinical practice, were surveyed as an 'expert' group to act as a control measure. Expert responses were consistent with current research in the field. General findings indicated few differences in overall knowledge between residents and physicians, with misconceptions evident in areas such as the nature of the disorder, qualitative characteristics of autism, and effective interventions. Results were also examined by specialty and, while pediatricians demonstrated additional accurate 11 knowledge regarding the nature of the disorder and select qualitative impairments, both residents and practicing physicians demonstrated misconceptions about PDDs. This preliminary study replicated the findings of Stone (1987) and Heidgerken (2005) concerning several misconceptions of PDDs held by residents and practicing physicians. Future research should focus on additional replications with validated measures as well as the gathering of qualitative information, in order to inform the medical profession of the need for education in PDDs at training and professional levels.

Interaction and knowledge exchange among academic business librarians in Ontario

A research project submitted to the Faculty of Extension, University of Alberta in partial fulfillment of the requirements for the degree of Master of Arts in Communications and Technology in 2005.

Anxiety-Related Disorders in Primary-Junior Grades (K-3): Teacher Perceptions and Knowledge

This study used a descriptive case study design to analyze teachers’ experiences of anxiety-related conditions and emotions in the primary-junior grades (K-3). The study sought to examine (a) educators’ perceptions of anxiety conditions and how such interpretations influence their teaching practice; (b) teachers’ knowledge of the diagnostic processes, symptomology, and emotions related to anxiety disorders; (c) primary teachers’ knowledge of and experience with emotional regulation strategies and therapeutic approaches for anxiety; and (d) additional strategies and knowledge that should be available to help students. The study adopted Bronfenbrenner’s (1986) Ecological Model to frame participants’ experiences and perspectives, as well as the impact of several factors (e.g., school, home) and individuals (e.g. teachers, parents, students) on students’ anxiety and the participants’ perspectives. Through in-person interviews, participants shared their experiences with and knowledge about students in their teaching practice who had experienced anxiety-related conditions and emotions. Four major themes emerged from the data: symptoms and situational contexts; knowledge of strategies and interventions; understanding and perspectives of students; anxious emotional responses; and challenges. The study contributes to the literature by providing the real-life perspectives and experiences of primary-junior teachers (K-3) related to students experiencing anxiety. The study provides further information for educators, administrators, and research regarding any additional support and knowledge that should be implemented to further assist educators and students in regards to anxiety.

GA approach for finding Rough Set decision rules based on bireducts

Feature selection plays an important role in knowledge discovery and data mining nowadays. In traditional rough set theory, feature selection using reduct - the minimal discerning set of attributes - is an important area. Nevertheless, the original definition of a reduct is restrictive, so in one of the previous research it was proposed to take into account not only the horizontal reduction of information by feature selection, but also a vertical reduction considering suitable subsets of the original set of objects. Following the work mentioned above, a new approach to generate bireducts using a multi--objective genetic algorithm was proposed. Although the genetic algorithms were used to calculate reduct in some previous works, we did not find any work where genetic algorithms were adopted to calculate bireducts. Compared to the works done before in this area, the proposed method has less randomness in generating bireducts. The genetic algorithm system estimated a quality of each bireduct by values of two objective functions as evolution progresses, so consequently a set of bireducts with optimized values of these objectives was obtained. Different fitness evaluation methods and genetic operators, such as crossover and mutation, were applied and the prediction accuracies were compared. Five datasets were used to test the proposed method and two datasets were used to perform a comparison study. Statistical analysis using the one-way ANOVA test was performed to determine the significant difference between the results. The experiment showed that the proposed method was able to reduce the number of bireducts necessary in order to receive a good prediction accuracy. Also, the influence of different genetic operators and fitness evaluation strategies on the prediction accuracy was analyzed. It was shown that the prediction accuracies of the proposed method are comparable with the best results in machine learning literature, and some of them outperformed it.

The Macroeconomic Effects of Infrequent Information with Adjustment Costs

In the last decade, the potential macroeconomic effects of intermittent large adjustments in microeconomic decision variables such as prices, investment, consumption of durables or employment – a behavior which may be justified by the presence of kinked adjustment costs – have been studied in models where economic agents continuously observe the optimal level of their decision variable. In this paper, we develop a simple model which introduces infrequent information in a kinked adjustment cost model by assuming that agents do not observe continuously the frictionless optimal level of the control variable. Periodic releases of macroeconomic statistics or dividend announcements are examples of such infrequent information arrivals. We first solve for the optimal individual decision rule, that is found to be both state and time dependent. We then develop an aggregation framework to study the macroeconomic implications of such optimal individual decision rules. Our model has the distinct characteristic that a vast number of agents tend to act together, and more so when uncertainty is large. The average effect of an aggregate shock is inversely related to its size and to aggregate uncertainty. We show that these results differ substantially from the ones obtained with full information adjustment cost models.