Utilizing social media in software documentation and knowledge management

This Master’s thesis studies the possibilities that social media tools can bring to help knowledge management in software development companies. It will introduce the most popular tools of social media and their usage possibilities in companies, not forgetting the possible downsides. One relevant aspect in this study is to investigate the possibilities of social media to help converting existing tacit knowledge into explicit. The purpose of the work is to create a proposal of social media utilization for a mid-sized software company, which has not utilized social media tools before. To be able to create the proposal, employees of the company are interviewed and a survey is executed to analyze the current situation. In addition a pilot project for trying out new social media tools is executed. The final result of this thesis introduces a tailored solution for the target company to start utilizing social media in its documentation and knowledge sharing processes. This new solution consists of multiple individual suggestions that are categorized and prioritized based on the significance and benefit that they bring to the company.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Service innovation development and knowledge integration practices - a comparative case study on KIBS sector

Academic research on services and innovations on services has significantly grown during recent years. So far research concerning management of knowledge intensive work on service development activities is very limited. The objective of this study was to examine knowledge integration practices that support service innovation development and to the best of knowledge such studies have not been previously published in academic literature. In the theoretical part of the study a review of state‐of‐the‐art literature was conducted, research gap was indicated and a framework for analysis was built. In the empirical part an explorative comparative multi‐case study was carried out in KIBS sector. Four companies were selected and four service development projects were inspected. The service development activities and knowledge integration practices were identified. The cases were carefully compared and results formed. The empirical results indicated that service innovation development is partly linear and partly incremental flow of activities where knowledge integration practices have important role supporting the planning and execution of tasks. Knowledge integration practices supporting planning and workshops are close interaction, interpretation, project planning and sequencing of work tasks. The identified knowledge integration practices supporting building service solution were careful role and competence management, routines and common knowledge. The main implication is that to manage knowledge intensive service innovation development a firm should carefully develop and choose relevant knowledge integration practices to support the service development activities.

Lectio praecursoria : Systems between information and knowledge : in a memory management model of an extended enterprise

VTT Jouni Meriluodon valtio-opin alaan kuuluva väitöskirja Systems between information and knowledge : in a memory management model of an extended enterprise tarkastettiin 21.6.2011 Helsingin yliopistossa.

Local Embeddedness and Knowledge Acquisition and How They Affect Finnish Business Operations in Russia

This pilot project aims examine the factors of the Finnish subsidiaries local embeddedness, their knowledge creation capabilities and the transfer mechanisms of new practices in the context of the Russian market. The research is designed as a multiple case study conducted with a qualitative approach. The empirical data consists of the interviews of the four Finnish case companies operating in the Kaluga region and three local partner companies. The deductive and inductive approaches were employed to conduct the analysis of the data. The propositions for the future study were developed in the conclusive chapters of the research, where we propose that the factor of the economy growth and industrialization matters in terms of subsidiaries’ role dedication, their knowledge creation capabilities, and direction of the knowledge flow within the local environment.

Liber fostering Open Science and Knowledge Discovery

Presentation of Kristiina Hormia-Poutanen at the 25th Anniversary Conference of The National Repository Library of Finland, Kuopio 22th of May 2015.

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.