Making Sense of Shared Leadership. A case study of leadership processes and practices without formal leadership structure in the team context

Leadership is essential for the effectiveness of the teams and organizations they are part of. The challenges facing organizations today require an exhaustive review of the strategic role of leadership. In this context, it is necessary to explore new types of leadership capable of providing an effective response to new needs. The presentday situations, characterized by complexity and ambiguity, make it difficult for an external leader to perform all leadership functions successfully. Likewise, knowledge-based work requires providing professional groups with sufficient autonomy to perform leadership functions. This study focuses on shared leadership in the team context. Shared leadership is seen as an emergent team property resulting from the distribution of leadership influence across multiple team members. Shared leadership entails sharing power and influence broadly among the team members rather than centralizing it in the hands of a single individual who acts in the clear role of a leader. By identifying the team itself as a key source of influence, this study points to the relational nature of leadership as a social construct where leadership is seen as social process of relating processes that are co-constructed by several team members. Based on recent theoretical developments concerned with relational, practice-based and constructionist approaches to the study of leadership processes, this thesis proposes the study of leadership interactions, working processes and practices to focus on the construction of direction, alignment and commitment. During the research process, critical events, activities, working processes and practices of a case team have been examined and analyzed with the grounded theory –approach in the terms of shared leadership. There are a variety of components to this complex process and a multitude of factors that may influence the development of shared leadership. The study suggests that the development process of shared leadership is a common sense -making process and consists of four overlapping dimensions (individual, social, structural, and developmental) to work with as a team. For shared leadership to emerge, the members of the team must offer leadership services, and the team as a whole must be willing to rely on leadership by multiple team members. For these individual and collective behaviors to occur, the team members must believe that offering influence to and accepting it from fellow team members are welcome and constructive actions. Leadership emerges when people with differing world views use dialogue and collaborative learning to create spaces where a shared common purpose can be achieved while a diversity of perspectives is preserved and valued. This study also suggests that this process can be supported by different kinds of meaning-making and process tools. Leadership, then, does not reside in a person or in a role, but in the social system. The built framework integrates the different dimensions of shared leadership and describes their relationships. This way, the findings of this study can be seen as a contribution to the understanding of what constitutes essential aspects of shared leadership in the team context that can be of theoretical value in terms of advancing the adoption and development process of shared leadership. In the real world, teams and organizations can create conditions to foster and facilitate the process. We should encourage leaders and team members to approach leadership as a collective effort that the team can be prepared for, so that the response is rapid and efficient.

From protein structure to function with bioinformatics

It has long been known that amino acids are the building blocks for proteins and govern their folding into specific three-dimensional structures. However, the details of this process are still unknown and represent one of the main problems in structural bioinformatics, which is a highly active research area with the focus on the prediction of three-dimensional structure and its relationship to protein function. The protein structure prediction procedure encompasses several different steps from searches and analyses of sequences and structures, through sequence alignment to the creation of the structural model. Careful evaluation and analysis ultimately results in a hypothetical structure, which can be used to study biological phenomena in, for example, research at the molecular level, biotechnology and especially in drug discovery and development. In this thesis, the structures of five proteins were modeled with templatebased methods, which use proteins with known structures (templates) to model related or structurally similar proteins. The resulting models were an important asset for the interpretation and explanation of biological phenomena, such as amino acids and interaction networks that are essential for the function and/or ligand specificity of the studied proteins. The five proteins represent different case studies with their own challenges like varying template availability, which resulted in a different structure prediction process. This thesis presents the techniques and considerations, which should be taken into account in the modeling procedure to overcome limitations and produce a hypothetical and reliable three-dimensional structure. As each project shows, the reliability is highly dependent on the extensive incorporation of experimental data or known literature and, although experimental verification of in silico results is always desirable to increase the reliability, the presented projects show that also the experimental studies can greatly benefit from structural models. With the help of in silico studies, the experiments can be targeted and precisely designed, thereby saving both money and time. As the programs used in structural bioinformatics are constantly improved and the range of templates increases through structural genomics efforts, the mutual benefits between in silico and experimental studies become even more prominent. Hence, reliable models for protein three-dimensional structures achieved through careful planning and thoughtful executions are, and will continue to be, valuable and indispensable sources for structural information to be combined with functional data.

GIS-based approach for optimization of onshore wind park infrastructure alignment in Finland

Wind power is a rapidly developing, low-emission form of energy production. In Fin-land, the official objective is to increase wind power capacity from the current 1 005 MW up to 3 500–4 000 MW by 2025. By the end of April 2015, the total capacity of all wind power project being planned in Finland had surpassed 11 000 MW. As the amount of projects in Finland is record high, an increasing amount of infrastructure is also being planned and constructed. Traditionally, these planning operations are conducted using manual and labor-intensive work methods that are prone to subjectivity. This study introduces a GIS-based methodology for determining optimal paths to sup-port the planning of onshore wind park infrastructure alignment in Nordanå-Lövböle wind park located on the island of Kemiönsaari in Southwest Finland. The presented methodology utilizes a least-cost path (LCP) algorithm for searching of optimal paths within a high resolution real-world terrain dataset derived from airborne lidar scannings. In addition, planning data is used to provide a realistic planning framework for the anal-ysis. In order to produce realistic results, the physiographic and planning datasets are standardized and weighted according to qualitative suitability assessments by utilizing methods and practices offered by multi-criteria evaluation (MCE). The results are pre-sented as scenarios to correspond various different planning objectives. Finally, the methodology is documented by using tools of Business Process Management (BPM). The results show that the presented methodology can be effectively used to search and identify extensive, 20 to 35 kilometers long networks of paths that correspond to certain optimization objectives in the study area. The utilization of high-resolution terrain data produces a more objective and more detailed path alignment plan. This study demon-strates that the presented methodology can be practically applied to support a wind power infrastructure alignment planning process. The six-phase structure of the method-ology allows straightforward incorporation of different optimization objectives. The methodology responds well to combining quantitative and qualitative data. Additional-ly, the careful documentation presents an example of how the methodology can be eval-uated and developed as a business process. This thesis also shows that more emphasis on the research of algorithm-based, more objective methods for the planning of infrastruc-ture alignment is desirable, as technological development has only recently started to realize the potential of these computational methods.

Stand structure of undrained and drained peatland forests in central Finland

Tiivistelmä: Suometsien rakenne-erot keskisessä Suomessa

Growth, crown structure and seed production of birch seedlings, grafts and micropropagated plants

Summary

Impact of regeneration method on stand structure prior to first thinning

Summary