Broadening the CRM domain of application to higher educational (e-learning) environments

In this paper, we reflect about the broadening of the field of application of CRM from the business domain to a wider context of relationships in which the inclusion of non-profit making organizations seems natural. In particular, we focus on analyzing the suitability of adopting CRM processes by universities and higher educational institutions dedicated to e-learning. This is an issue that, in our opinion, has much potential but has received little attention in research so far.

The FaceUOC Project : An Open Social Learning experience by the Open University of Catalonia

The possibilities and expansion of the use of Web 2.0 has opened up a world of possibilities in online learning. In spite of the integration of these tools in education major changes are required in the educational design of instructional processes.This paper presents an educational experience conducted by the Open University of Catalonia using the social network Facebook for the purpose of testing a learning model that uses a participation and collaboration methodology among users based on the use of open educational resources.- The aim of the experience is to test an Open Social Learning (OSL) model, understood to be a virtual learning environment open to the Internet community, based on the use of open resources and on a methodology focused on the participation and collaboration of users in the construction of knowledge.- The topic chosen for this experience in Facebook was 2.0 Journeys: online tools and resources. The objective of this 5 weeks course was to provide students with resources for managing the various textual, photographic, audiovisual and multimedia materials resulting from a journey.- The most important changes in the design and development of a course based on OSL are the role of the teacher, the role of the student, the type of content and the methodology:- The teacher mixes with the participants, guiding them and offering the benefit of his/her experience and knowledge.- Students learn through their participation and collaboration with a mixed group of users.- The content is open and editable under different types of license that specify the level of accessibility.- The methodology of the course was based on the creation of a learning community able to self-manage its learning process. For this a facilitator was needed and also a central activity was established for people to participate and contribute in the community.- We used an ethnographic methodology and also questionnaires to students in order to acquire results regarding the quality of this type of learning experience.- Some of the data obtained raised questions to consider for future designs of educational situations based on OSL:- Difficulties in breaking the facilitator-centred structure- Change in the time required to adapt to the system and to achieve the objectives- Lack of commitment with free courses- The trend to return to traditional ways of learning- Accreditation- This experience has taught all of us that education can happen any time and in any place but not in any way.

Reflective Learning in Higher Education: A Comparative Analysis

A descriptive, exploratory study is presented based on a questionnaire regarding the following aspects of reflective learning: a) self-knowledge, b) relating experience to knowledge, c) self-reflection, and d) self-regulation of the learning processes. The questionnaire was completed by students studying four different degree courses (social education, environmental sciences, nursing, and psychology). Specifically, the objectives of a self-reported reflective learning questionnaire are: i) to determine students’ appraisal of reflective learning methodology with regard to their reflective learning processes, ii) to obtain evidence of the main difficulties encountered by students in integrating reflective learning methodologies into their reflective learning processes, and iii) to collect students’ perceptions regarding the main contributions of the reflective learning processes they have experienced

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Inter organizational learning within and by innovation networks

The thesis deals with the phenomenon of learning between organizations in innovation networks that develop new products, services or processes. Inter organizational learning is studied especially at the level of the network. The role of the network can be seen as twofold: either the network is a context for inter organizational learning, if the learner is something else than the network (organization, group, individual), or the network itself is the learner. Innovations are regarded as a primary source of competitiveness and renewal in organizations. Networking has become increasingly common particularly because of the possibility to extend the resource base of the organization through partnerships and to concentrate on core competencies. Especially in innovation activities, networks provide the possibility to answer the complex needs of the customers faster and to share the costs and risks of the development work. Networked innovation activities are often organized in practice as distributed virtual teams, either within one organization or as cross organizational co operation. The role of technology is considered in the research mainly as an enabling tool for collaboration and learning. Learning has been recognized as one important collaborative process in networks or as a motivation for networking. It is even more important in the innovation context as an enabler of renewal, since the essence of the innovation process is creating new knowledge, processes, products and services. The thesis aims at providing enhanced understanding about the inter organizational learning phenomenon in and by innovation networks, especially concentrating on the network level. The perspectives used in the research are the theoretical viewpoints and concepts, challenges, and solutions for learning. The methods used in the study are literature reviews and empirical research carried out with semi structured interviews analyzed with qualitative content analysis. The empirical research concentrates on two different areas, firstly on the theoretical approaches to learning that are relevant to innovation networks, secondly on learning in virtual innovation teams. As a result, the research identifies insights and implications for learning in innovation networks from several viewpoints on organizational learning. Using multiple perspectives allows drawing a many sided picture of the learning phenomenon that is valuable because of the versatility and complexity of situations and challenges of learning in the context of innovation and networks. The research results also show some of the challenges of learning and possible solutions for supporting especially network level learning.

Efficiency and Equity in Learning Communities and schools

Traditionally, school efficiency has been measured as a function of educational production. In the last two decades, however, studies in the economics of education have indicated that more is required to improve school efficiency: researchers must explore how significant changes in school organization affect the performance of at-risk students. In this paper we introduce Henry Levin’s adoption of the X-efficiency approach to education and we describe the efficient and cost-effective characteristics of one Learning Communities Project School that significantly improved its student outcomes and enrollment numbersand reduced its absenteeism rate to zero. The organizational change that facilitatedthese improvements defined specific issues to address. Students’ school success became the focus of the school project, which also offered specific incentives, selected teachers, involved parents and community members in decisions, and used the most efficient technologies and methods. This case analysis reveals new two elements—family training and community involvement—that were not explicit parts of Levin’s adaptation. The case of the Antonio Machado Public School should attract the attention of both social scientists and policy makers

The Transformation of Practical Teaching Focusing on Dialogic Learning

This study investigates the transformation of practical teaching in a Catalan school, connected to the design, implementation and development of project-based learning, and focusing on dialogic learning to investigate its limits and possibilities. Qualitative and design-based research (DBR) methods are applied. These methods are based on empirical educational research with the theory-driven of learning environments. DBR is proposed and applied using practical guidance for the teachers of the school. It can be associated with the current proposals for Embedding Social Sciences and Humanities in the Horizon 2020 Societal Challenges. This position statement defends the social sciences and the humanities as the most fundamental and important ideas to face all societal challenges. The results of this study show that before the training process, teachers apply dialogic learning in specific moments (for example, when they speak about the weekend); however, during the process and after the process, they work systematically with dialogic learning through the PEPT: they start and finish every activity with a individual and group reflection about their own processes, favouring motivation, reasoning and the implication of all the participants. These results prove that progressive transformations of teaching practice benefit cooperative work in class

Machine Learning and Clinical Text. Supporting Health Information Flow

Fluent health information flow is critical for clinical decision-making. However, a considerable part of this information is free-form text and inabilities to utilize it create risks to patient safety and cost-­effective hospital administration. Methods for automated processing of clinical text are emerging. The aim in this doctoral dissertation is to study machine learning and clinical text in order to support health information flow.First, by analyzing the content of authentic patient records, the aim is to specify clinical needs in order to guide the development of machine learning applications.The contributions are a model of the ideal information flow,a model of the problems and challenges in reality, and a road map for the technology development. Second, by developing applications for practical cases,the aim is to concretize ways to support health information flow. Altogether five machine learning applications for three practical cases are described: The first two applications are binary classification and regression related to the practical case of topic labeling and relevance ranking.The third and fourth application are supervised and unsupervised multi-class classification for the practical case of topic segmentation and labeling.These four applications are tested with Finnish intensive care patient records.The fifth application is multi-label classification for the practical task of diagnosis coding. It is tested with English radiology reports.The performance of all these applications is promising. Third, the aim is to study how the quality of machine learning applications can be reliably evaluated.The associations between performance evaluation measures and methods are addressed,and a new hold-out method is introduced.This method contributes not only to processing time but also to the evaluation diversity and quality. The main conclusion is that developing machine learning applications for text requires interdisciplinary, international collaboration. Practical cases are very different, and hence the development must begin from genuine user needs and domain expertise. The technological expertise must cover linguistics,machine learning, and information systems. Finally, the methods must be evaluated both statistically and through authentic user-feedback.

Cultural aspects of globalizing university-industry knowledge interaction in China

Previous studies of the local involvement of multinational corporation (MNC) subsidiaries focus on host-country firms and local business partners such as suppliers and customers. The role of host-country universities in the same context of innovation networks is neglected. Furthermore, there are many organizational culture- and knowledge-related differences between universities and companies, and this is likely to pose additional challenges for successful collaboration. Early university-industry (U-I) studies have primarily been limited within a national boundary, being concerned with a single level of culture (i.e., at an organizational level) and one-way knowledge transfer from university to industry. Research on more dynamic knowledge interaction in multinational settings is lacking. This is particularly true in the business context of China. In today’s globalizing and rapidly changing organizations, addressing cultural differences and clashes is an everyday reality, and inter-cultural U-I collaboration is becoming a key asset for gaining global competitiveness. This study deals with Finnish MNC subsidiaries’ research collaboration with Chinese universities. It aims to explore the essence of such U-I collaboration and knowledge interaction, uncovering the deep functioning mechanisms of culture underlying effective collaborative knowledge creation and innovation. The study reviews critically different bodies of literature including knowledge management theories and studies, U-I collaboration and knowledge interaction, and cross-cultural research in terms of organizational knowledge generation and utilization. It adopts a case study strategy with qualitative research methods, and data is collected through in-depth interviews and participant observation. The study presents the following major findings: 1. In the light of a comprehensive analysis of U-I collaboration, an effective matching strategy is proposed, in the assumption that good alignment of knowledge interaction strategies and approaches with their corresponding knowledge type, capability development and research task may greatly enhance the effectiveness of cross-cultural U-I collaboration and knowledge interaction. 2. It is proposed that in the Chinese MNC context more dynamic types of knowledge interaction like knowledge co-creation should be of key concern particularly when dealing simultaneously with multi-disciplinary applied research of human factors and technologies. U-I knowledge interaction, otherwise, pays attention only to the study of one-way technology and knowledge transfer. 3. It is posited that the influence of culture on collaborative knowledge interaction can be studied in a valuable way when knowledge-related variables are simultaneously taken into account. A systematic analysis of the role of knowledge in cross-cultural knowledge interaction could best be approached from multi-aspects of knowledge including not only nature, characteristics and types of knowledge but also the process of knowledge (e.g., intensifications of knowledge interaction). 4. The study demonstrates the significant role of aspects of the host-country culture (e.g., Chinese guanxi) in U-I collaboration and knowledge interaction. This is evident, for instance, in issues related to interpersonal relationships and trust, true interest and the relatedness of the research, mutual commitment and learning, communication intensity and interaction, and awareness of cultural and knowledge-related differences between collaboration partners. Theoretical and practical implications of the findings are suggested and discussed.

Att lära för livet hemma och i skolan : elevers uppfattningar av kost och hälsa, konsumtion och privatekonomi samt hushåll och miljö

The home is an important societal arena for upbringing and learning. A child can experience a feeling of participation in the household he or she belongs to very early in life. In this manner, the home environment constitutes an essential foundation for instruction in the subject of Home Economics. At school, Home Economics pupils should fulfill the intentions that school curriculum has for the subject, that is to say develop the knowledge, skills, and values that allow pupils to be able to take responsibility for their health, finances, comfort, and safety in their close environment. The purpose of this study is twofold. Firstly, the study aims to examine what knowledge and attitudes children and teenagers have acquired from their home environment, close environment, as well as school. Secondly, the study aims to evaluate the effects of instruction in Home Economics, at the 7th grade level, as regards diet and health, consumption and private finances, as well as household and the environment. The study’s methodological foundation focuses on pupils’ understanding of the surrounding world. A phenomenographical approach to the research phenomenon basis itself on the supposition that knowledge is fixed in human beings’ consciousness and experiences. Furthermore, the study stresses individual variations in conjunction with the experienced phenomenon. The empirical portion of the study is based on semistructured interviews of 30 pupils divided into two reference groups. The pupils were interviewed before instruction in the subject of Home Economics started and upon completing instruction. The interview data was analyzed and interpreted in accordance with the “multistage model”. The study results show that upbringing in the home environment is determinative as pertains to understanding of the socio-cultural household environment. Mealtime traditions, for example, are deeply ingrained but nonetheless influenced by lifestyle changes. The study shows that a didactic challenge exists to draw attention to the consequences of poor mealtime habits and stress for everyone raising or educating children and teenagers. Despite good knowledge of what a healthy diet is, the majority of pupils choose fast-food and junk-food when they eat out to save time and money. Studies of pupils’ preparedness for consumption show that a purposeful upbringing in the home in combination with relevant instruction in Home Economics, results in knowledgeable consumers. This study also shows that upbringing in the home environment and instruction in Home Economics requires an intense and conscious focus on the consequences of a household not run in accordance with nature, where the household lifestyle is nonsustainable. Pupils’ understanding is often based on the disregarding of the survival perspective for a comfort perspective. Parents and Home Economics teachers should be able to bring up and teach children and teenagers in a manner that allows children and teenagers to take responsibility for their health, private finances, as well as comfort and safety in the close environment. The method is conscious nurturing and instruction.

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.

Playing to Learn: Business Simulation Games as Leadership Learning Environments

The aim of this dissertation is to investigate if participation in business simulation gaming sessions can make different leadership styles visible and provide students with experiences beneficial for the development of leadership skills. Particularly, the focus is to describe the development of leadership styles when leading virtual teams in computer-­supported collaborative game settings and to identify the outcomes of using computer simulation games as leadership training tools. To answer to the objectives of the study, three empirical experiments were conducted to explore if participation in business simulation gaming sessions (Study I and II), which integrate face-­to-­face and virtual communication (Study III and IV), can make different leadership styles visible and provide students with experiences beneficial for the development of leadership skills. In the first experiment, a group of multicultural graduate business students (N=41) participated in gaming sessions with a computerized business simulation game (Study III). In the second experiment, a group of graduate students (N=9) participated in the training with a ‘real estate’ computer game (Study I and II). In the third experiment, a business simulation gaming session was organized for graduate students group (N=26) and the participants played the simulation game in virtual teams, which were organizationally and geographically dispersed but connected via technology (Study IV). Each team in all experiments had three to four students and students were between 22 and 25 years old. The business computer games used for the empirical experiments presented an enormous number of complex operations in which a team leader needed to make the final decisions involved in leading the team to win the game. These gaming environments were interactive;; participants interacted by solving the given tasks in the game. Thus, strategy and appropriate leadership were needed to be successful. The training was competition-­based and required implementation of leadership skills. The data of these studies consist of observations, participants’ reflective essays written after the gaming sessions, pre-­ and post-­tests questionnaires and participants’ answers to open-­ ended questions. Participants’ interactions and collaboration were observed when they played the computer games. The transcripts of notes from observations and students dialogs were coded in terms of transactional, transformational, heroic and post-­heroic leadership styles. For the data analysis of the transcribed notes from observations, content analysis and discourse analysis was implemented. The Multifactor Leadership Questionnaire (MLQ) was also utilized in the study to measure transformational and transactional leadership styles;; in addition, quantitative (one-­way repeated measures ANOVA) and qualitative data analyses have been performed. The results of this study indicate that in the business simulation gaming environment, certain leadership characteristics emerged spontaneously. Experiences about leadership varied between the teams and were dependent on the role individual students had in their team. These four studies showed that simulation gaming environment has the potential to be used in higher education to exercise the leadership styles relevant in real-­world work contexts. Further, the study indicated that given debriefing sessions, the simulation game context has much potential to benefit learning. The participants who showed interest in leadership roles were given the opportunity of developing leadership skills in practice. The study also provides evidence of unpredictable situations that participants can experience and learn from during the gaming sessions. The study illustrates the complex nature of experiences from the gaming environments and the need for the team leader and role divisions during the gaming sessions. It could be concluded that the experience of simulation game training illustrated the complexity of real life situations and provided participants with the challenges of virtual leadership experiences and the difficulties of using leadership styles in practice. As a result, the study offers playing computer simulation games in small teams as one way to exercise leadership styles in practice.

Perspektivmöten i skola och handledning : lärares tankar om specialpedagogisk handledning

To create a more inclusive school, an increase in multidisciplinary cooperation is needed. One possible form of collaboration could encompass the special education teacher taking on the role of a consultant for other teachers in need of support in working with heterogeneous groups of pupils. Previous research shows that special education teachers see the role as consultant as diffuse and complex. The overarching aim of the present study involves deepening the knowledge on how consultation in a special educational context can be understood and developed based on teachers’ descriptions on this particular form of activity interpreted against various perspectives on consultation. The study is qualitative in nature and rests on a hermeneutic interpretive research tradition in combination with an abductive approach. The theoretical framework consists of two different approaches to consultation: the directive and the non-directive approach. The approaches differ regarding particular emphasis on advice and reflection during the consultation and with respect to who or what should be the focus of the consultation. The two approaches are here studied through various theories such as social learning theory, Bruner's theory of scaffolding, Roger’s humanist psychology, and constructivism. Semi-structured interviews were held with eighteen special education teachers (n=9) and class teachers (n=9) working in the compulsory school. The overall interpretation of the results shows that special education consultation can be understood as three different types of consultation. Consultation as counseling which harmonizes with the directive perspective on consultation is the most prominent type. In the consultation as counseling conversation, the special educational knowledge transfer is central and the focus is placed on the pupil. Although special education knowledge transfer emerges as a unique aspect of special education consultation, there are several inherent challenges in this type of consultation that can be addressed in that teachers also describe two other types of consultation. In the reflective consultation, there is a move away from the pupil focus and toward a focus on the class teacher and the use of reflection. The reflective consultation harmonizes with the non-directive approach to consultation. This type of consultation does not as of yet have a prominent place in the Finland-Swedish school context and at this stage it is not seen as a legitimate type of consultation according to the teachers’ descriptions. Despite this, certain aspects of the reflective conversation could be given more space in the development of consultation within special educational contexts. The co-operative consultation is characterized by the teachers acting as teammates and using professional exchange as a strategy for consultation. Both teachers' knowledge is seen as central, and rather than the special education teacher acting as the expert and moderator, the teachers control the consultation together and jointly move the work along. The co-operative consultation enables the focus to move from the pupil toward the context, which can lead to the development of inclusive practices. The results indicate that this type of consultation holds potential in the development of special educational consultation that takes place between equal colleagues. The co-operative consultation opens up for a third collaborative approach to consultation, where aspects of the directive and non-directive perspective can merge and develop. The thesis concludes with the proposal that special pedagogical consultation can be understood from an integrated perspective. The characteristics of the consultation can vary depending on the type of problem or situation, while co-operative consultation can be seen as the ideal as equal colleagues meet in consultation conversations. In order to develop the co-operative consultation, both teachers are required to have knowledge of consultation as a practice, to be part of a collaborative school climate, and that teachers are provided with enough time to take part in consultations.

The demand for global student talent: Capitalizing on the value of university-industry collaboration

The university sector in Europe has invested money and effort into the internationalization of higher education. The benefits of internationalizing higher education are fuelled by changing global values, choices and practices. However, arguments that serve the internationalization of higher education tend to stress either local organizational or individual interests; seldom do they emphasize the societal benefits. This dissertation investigates how collaboration between university and industry facilitates a shift in thinking about attracting and retaining global student talent, in terms of co-creating solutions to benefit the development of our knowledge society. The macro-structures of the higher education sector have the tendency to overemphasize quantitative goals to improve performance verifiability. Recruitment of international student talent is thereby turned into a mere supply issue. A mind shift is needed to rethink the efficacy of the higher education sector with regard to retaining foreign student talent as a means of contributing to society’s stock of knowledge and through that to economic growth. This thesis argues that academic as well as industrial understanding of the value of university-industry collaboration might then move beyond the current narrow expectations and perceptions of the university’s contribution to society’s innovation systems. This mind shift is needed to encourage and generate creative opportunities for university-industry partnerships to develop sustainable solutions for successful recruitment of foreign student talent, and thereby to maximize the wealth-creating potential of global student talent recruitment. This thesis demonstrates through the use of interpretive and participatory methods, how it is possible to reveal new and important insights into university-industry partnering for enhancing attraction and retention of global student talent. It accomplishes this by expressly pointing out the central role of human collaborative experiencing and learning. The narratives presented take the reader into a Finnish and Dutch universityindustry partnering environment to reflect on the relationship between the local universities of technology and their operational surroundings, a relationship that is set in a context of local and global entanglements and challenges.

Research framework for the connection between environmental collaboration and firm performance

This thesis focuses on collaborative activities with regard to environmental issues both within the firm and outside the firm with the key suppliers and customers, i.e. internal and external environmental collaboration. Integrating environmental thinking into supply chain management has received increasing interest in recent years. The relational view and the natural resource-based-view together suggest that environmental capabilities can be built jointly with supply chain partners and used to gain sustained competitive advantage. Several studies have been undertaken to analyse the connection between environmental activities and firm performance but most studies have taken only economic performance into account. This study pays attention also to two other dimensions of firm performance, intra-firm supply chain performance and environmental performance, and aims at presenting the linkages between them and environmental collaboration. This thesis creates a research framework for the connections between environmental collaboration and firm performance and suggests approaches to analyse these. In order to find out the key concepts and their relationship, an extensive literature review is conducted. The research framework proposes a positive connection between internal and external environmental collaboration and all three dimensions of firm performance. In addition, environmental performance and intra-firm supply chain performance are expected to contribute positively to economic performance. Hence, firms are suggested to benefit from environmental collaboration both within the firm and outside the firm. Empirical testing of the developed research framework is out of the scope of this study. However, this thesis proposes using a mixed methods research approach, including survey research and multiple case studies. Finland State of Logistics 2012 survey commissioned by the Finnish Ministry of Transport and Communications and conducted by Turku School of Economics is used as an example of data for the quantitative phase. The applicability of these two methods is discussed at a general level and with regard to analysing the research framework developed in the thesis. Future research will aim at the development of the research framework and the methods in order to confirm the connection between environmental collaboration and firm performance.