The contributions of netnography in new product development

Netnography has been studying in various aspects (e.g. definitions of netnography, application of netngoraphy, conducting procedure…) within different industrial contexts. Besides, there are many studies and researches about new product development in various perspectives, such as new product development models, management of new product development project, or interaction between customers and new product design, and so on. However, the connection and the interaction between netnography and new product development have not been studied recently. This opens opportunities for the writer to study and explore unrevealed issues regarding to applying netnography in new product development. In term of the relation between netnography and new product development, there are numerous of matters need to be explored; for instance, the process of applying netnography in order to benefit to new product development, the involvement degree of netnography in new product development process, or eliminating useless information from netnography so that only crucial data is utilized, and so on. In this thesis, writer focuses on exploring how netnography is applied in new product development process, and what benefits netnography can contribute to the succeed of the project. The aims of this study are to understand how netnography is conducted for new product development purpose, and to analyse the contributions of netnography in the new product development process. To do so, a case-study strategy will be conducted with triple case studies. The case studies are chosen bases on many different criteria in order to select the most relevant cases. Eventually, the writer selected three case studies, which are Sunless tanning product project (HYVE), Listerine (NetBase), and Nivea co-creation and netnography in black and white deodorant. The case study strategy applied in this thesis includes four steps e.g. case selection, data collection, case study analysis, and generating the research outcomes from the analysis. This study of the contributions of netnography in the new product development process may be useful for the readers in many ways. It offers the fundamental knowledge of netnography market research method and basic understanding of new product development process. Additionally, it emphasizes the differences between netnography and other market research methods in order to explain the reasons why many companies and market research agents recently utilized netnography in their market research projects. Furthermore, it highlights the contributions of netnography in the new product development process in order to indicate the importance of netnography in developing new product. Thus, the potential readers of the study can be students, marketers, researchers, product developers, or business managers.

Comparative Analysis of Solar PV Business Models

The goal of the thesis is to analyze the strengths and weaknesses of solar PV business model and point out key factors that affect the efficiency of business model, the results are expected to help in creating new business strategy. The methodology of case study research is chosen as theoretical background to structure the design of the thesis indicating how to choose the right research method and conduction of a case study research. Business model canvas is adopted as the tool for analyzing the case studies of SolarCity and Sungevity. The results are presented through the comparison between the cases studies. Solar services and products, cost in customer acquisition, intellectual resource and powerful sales channels are identified as the major factors for TPO model.

The early activities of front end of innovation in oem companies using a new fei platform as a framework for renewal

The main goal of this study is to create a seamless chain of actions and more detailed structure to the front end of innovation to be able to increase the front end performance and finally to influence the renewal of companies. The main goal is achieved through by the new concept of an integrated model of early activities of FEI leading to a discovery of new elements of opportunities and the identification of new business and growth areas. The procedure offers one possible solution to a dynamic strategy formation process in innovation development cycle. In this study the front end of innovation is positioned between a strategy reviews and a concept creation with needed procedures, tools, and frameworks. The starting point of the study is that the origins of innovation are not well enough understood. The study focuses attention on the early activities of FEI. These first activities are conceptualized in order to find out successful innovation initiatives and strategic renewal agendas. A seamless chain of activities resulting in faster and more precise identification of opportunities and growth areas available on markets and inside companies is needed. Three case studies were conducted in order to study company views on available theory doctrine and to identify the first practical experiences and procedures in the beginning of the front end of innovation. Successful innovation requires focus on renewal in both internal and external directions and they should be carefully balanced for best results. Instead of inside-out mode of actions the studied companies have a strong outside-in thinking mode and they mainly co-develop their innovation initiatives in close proximity with customers i.e. successful companies are an integral part of customers business and success. Companies have tailor-made innovation processes combined their way of working linked to their business goals, and priorities of actual needs of transformation. The result of this study is a new modular FEI platform which can be configured by companies against their actual business needs and drivers. This platform includes new elements of FEI documenting an architecture presenting how the system components work together. The system is a conceptual approach from theories of emergent strategy formation, opportunity identification and creation, interpretation-analysis-experimentation triad and the present FEI theories. The platform includes new features compared to actual models of FEI. It allows managers to better understand the importance of FEI in the whole innovation development stage and FEI as a phase and procedure to discover and implement emergent strategy. An adaptable company rethinks and redirects strategy proactively from time to time. Different parts of the business model are changed to remove identified obstacles for growth and renewal which gives them avenues to find right reforms for renewal.

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.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Future of Newspaper Business Models in Finland

The purpose of this Master’s thesis was to study the business model development in Finnish newspaper industry during the next then years through scenario planning. The objective was to see how will the business models develop amidst the many changes in the industry, what factors are affecting the change, what are the implications of these changes for the players in the industry and how should the Finnish newspaper companies evolve in order to succeed in the future. In this thesis the business model change is studied based on all the elements of business models, as it was discovered that the industry is too often focusing on changes in only few of those elements and a more broader view can provide valuable information for the companies. The results revealed that the industry is affected by many changes during the next ten years. Scenario planning provides a good tool for analyzing this change and for developing valuable options for businesses. After conducting series of interviews and discovering forces affecting the change, four different scenarios were developed centered on the role that newspaper will take and the level at which they are providing the content in the future. These scenarios indicated that there are varieties of options in the way the business models may develop and that companies should start making decisions proactively in order to succeed. As the business model elements are interdepended, changes made in the other elements will affect the whole model, making these decisions about the role and level of content important for the companies. In the future, it is likely that the Finnish newspaper industry will include many different kinds of business models, some of which can be drastically different from the current ones and some of which can still be similar, but take better into account the new kind of media environment.

New [18F]Tracers for Alzheimer's Disease Imaging. Labeling Synthesis And Biological Testing

Alzheimer’s disease (AD) is the most common form of dementia. Characteristic changes in an AD brain are the formation of β-amyloid protein (Aβ) plaques and neurofibrillary tangles, though other alterations in the brain have also been connected to AD. No cure is available for AD and it is one of the leading causes of death among the elderly in developed countries. Liposomes are biocompatible and biodegradable spherical phospholipid bilayer vesicles that can enclose various compounds. Several functional groups can be attached on the surface of liposomes in order to achieve long-circulating target-specific liposomes. Liposomes can be utilized as drug carriers and vehicles for imaging agents. Positron emission tomography (PET) is a non-invasive imaging method to study biological processes in living organisms. In this study using nucleophilic 18F-labeling synthesis, various synthesis approaches and leaving groups for novel PET imaging tracers have been developed to target AD pathology in the brain. The tracers were the thioflavin derivative [18F]flutemetamol, curcumin derivative [18F]treg-curcumin, and functionalized [18F]nanoliposomes, which all target Aβ in the AD brain. These tracers were evaluated using transgenic AD mouse models. In addition, 18F-labeling synthesis was developed for a tracer targeting the S1P3 receptor. The chosen 18F-fluorination strategy had an effect on the radiochemical yield and specific activity of the tracers. [18F]Treg-curcumin and functionalized [18F]nanoliposomes had low uptake in AD mouse brain, whereas [18F]flutemetamol exhibited the appropriate properties for preclinical Aβ-imaging. All of these tracers can be utilized in studies of the pathology and treatment of AD and related diseases.

Deep generative models for facial keypoints detection

A new area of machine learning research called deep learning, has moved machine learning closer to one of its original goals: artificial intelligence and general learning algorithm. The key idea is to pretrain models in completely unsupervised way and finally they can be fine-tuned for the task at hand using supervised learning. In this thesis, a general introduction to deep learning models and algorithms are given and these methods are applied to facial keypoints detection. The task is to predict the positions of 15 keypoints on grayscale face images. Each predicted keypoint is specified by an (x,y) real-valued pair in the space of pixel indices. In experiments, we pretrained deep belief networks (DBN) and finally performed a discriminative fine-tuning. We varied the depth and size of an architecture. We tested both deterministic and sampled hidden activations and the effect of additional unlabeled data on pretraining. The experimental results show that our model provides better results than publicly available benchmarks for the dataset.

Translational models of coronary artery disease, myocardial infarction and heart failure. Development, validation and in vivo imaging studies using positron emission tomography

Coronary artery disease is an atherosclerotic disease, which leads to narrowing of coronary arteries, deteriorated myocardial blood flow and myocardial ischaemia. In acute myocardial infarction, a prolonged period of myocardial ischaemia leads to myocardial necrosis. Necrotic myocardium is replaced with scar tissue. Myocardial infarction results in various changes in cardiac structure and function over time that results in “adverse remodelling”. This remodelling may result in a progressive worsening of cardiac function and development of chronic heart failure. In this thesis, we developed and validated three different large animal models of coronary artery disease, myocardial ischaemia and infarction for translational studies. In the first study the coronary artery disease model had both induced diabetes and hypercholesterolemia. In the second study myocardial ischaemia and infarction were caused by a surgical method and in the third study by catheterisation. For model characterisation, we used non-invasive positron emission tomography (PET) methods for measurement of myocardial perfusion, oxidative metabolism and glucose utilisation. Additionally, cardiac function was measured by echocardiography and computed tomography. To study the metabolic changes that occur during atherosclerosis, a hypercholesterolemic and diabetic model was used with [18F] fluorodeoxyglucose ([18F]FDG) PET-imaging technology. Coronary occlusion models were used to evaluate metabolic and structural changes in the heart and the cardioprotective effects of levosimendan during post-infarction cardiac remodelling. Large animal models were used in testing of novel radiopharmaceuticals for myocardial perfusion imaging. In the coronary artery disease model, we observed atherosclerotic lesions that were associated with focally increased [18F]FDG uptake. In heart failure models, chronic myocardial infarction led to the worsening of systolic function, cardiac remodelling and decreased efficiency of cardiac pumping function. Levosimendan therapy reduced post-infarction myocardial infarct size and improved cardiac function. The novel 68Ga-labeled radiopharmaceuticals tested in this study were not successful for the determination of myocardial blood flow. In conclusion, diabetes and hypercholesterolemia lead to the development of early phase atherosclerotic lesions. Coronary artery occlusion produced considerable myocardial ischaemia and later infarction following myocardial remodelling. The experimental models evaluated in these studies will enable further studies concerning disease mechanisms, new radiopharmaceuticals and interventions in coronary artery disease and heart failure.

Exploring business models for medical games: Key components and challenges

The costs of health care are going up in many countries. In order to provide affordable and effective health care solutions, new technologies and approaches are constantly being developed. In this research, video games are presented as a possible solution to the problem. Video games are fun, and nowadays most people like to spend time on them. In addition, recent studies have pointed out that video games can have notable health benefits. Health games have already been developed, used in practice, and researched. However, the bulk of health game studies have been concerned with the design or the effectiveness of the games; no actual business studies have been conducted on the subject, even though health games often lack commercial success despite their health benefits. This thesis seeks to fill this gap. The specific aim of this thesis is to develop a conceptual business model framework and empirically use it in explorative medical game business model research. In the first stage of this research, a literature review was conducted and the existing literature analyzed and synthesized into a conceptual business model framework consisting of six dimensions. The motivation behind the synthesis is the ongoing ambiguity around the business model concept. In the second stage, 22 semi-structured interviews were conducted with different professionals within the value network for medical games. The business model framework was present in all stages of the empirical research: First, in the data collection stage, the framework acted as a guiding instrument, focusing the interview process. Then, the interviews were coded and analyzed using the framework as a structure. The results were then reported following the structure of the framework. In the results, the interviewees highlighted several important considerations and issues for medical games concerning the six dimensions of the business model framework. Based on the key findings of this research, several key components of business models for medical games were identified and illustrated in a single figure. Furthermore, five notable challenges for business models for medical games were presented, and possible solutions for the challenges were postulated. Theoretically, these findings provide pioneering information on the untouched subject of business models for medical games. Moreover, the conceptual business model framework and its use in the novel context of medical games provide a contribution to the business model literature. Regarding practice, this thesis further accentuates that medical games can offer notable benefits to several stakeholder groups and offers advice to companies seeking to commercialize these games.

Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.

Business models for Finnish biobanks

This study concentrates on developing a suitable business model for Finnish biobanks, with particular emphasis on value creation to stakeholders. The sub-objective of this thesis are to map the commercial possibilities of biobanks and potential barriers for business development. The study approaches the subject from the biobanks’ as well as the stakeholders’ point of view, integrating their hopes and needs considering current and future co-operation into the findings. In 2013 the Biobank Act came into effect, after which six biobanks have been established and several other pending biobank projects are in process. There is relatively little research in regard to the commercial opportunities of this newcomer of the biomedical industry, and particularly in the Finnish markets. Therefore, the aim of this study is to partially fill the research gap of the commercial potential of biobanks and particularly outline the problematic elements in developing business. The theoretical framework consists of a few select theories, which depict business modeling and value creation of organizations. The theories are combined to form a synthesis, which best adapts to biobanks, and acts as a backbone for interviews. The empirical part of the study was conducted mainly by seven face-to-face interviews, and complemented by two phone interviews and an e-mail questionnaire with four responses. The findings consist mainly of the participants’ reflections on the potential products and services enabled by consumer genomics, as well as perceptions on different obstacles for biobanks’ business development. The nature of the study is tentative, as biobanks are relatively new organizations in Finland, and their operation models and activities are still molding. The aim is to bring to surface the hopes and concerns of biobanks’ representatives, as well as the representatives of stakeholders, in order to transparently discuss the current situation and suggestions for further development. The study concludes that in principle, the interviewees’ agree on the need for development in order not to waste the potential of biobanks; regardless, the participants emphasize different aspects and subsequently lean on differing methods.

New ways to do business plans in multicultural organizations

Business plans are made when establishing new company or when organizations launch new product or services. In this Master Thesis was examined the elements are included in the business plan and emphasized. Business plan is a wide document and can also contain company specific information, the literature review was restricted into three areas which were investigated from the relating literature and articles. The selected areas were Market Segmentation and Targeting, Competitive Environment, and Market Positioning and Strategy. The different business plan models were investigated by interviewing companies who operates in a different industry sectors from each other’s. The models were compared to each other and to the findings from literature. Based on interview results and literature findings, the business plan for fibre based packaging. The created business plan contains three selected areas. It was found that the selected business plan elements can be found from the interviewed companies’ business plans. The market segmentation was done by comparing the market share to known total market size. When analyzing the competitive environment, there was no one selected model in use. The tools to evaluate competitive environment was selected parts from both SWOT analysis and Porter’s five forces model in applicable part. Based on interview results, it can be state that the company or organization should find and built its own model for business plans. In order to receive the benefits for future planning, the company should use the same model for long time.

Models to study intermediate filament dynamics and functions

Intermediate filaments are part of the cytoskeleton and nucleoskeleton; they provide cells with structure and have important roles in cell signalling. The IFs are a large protein family with more than 70 members; each tightly regulated and expressed in a cell type-specific manner. Although the IFs have been known and studied for decades, our knowledge about their specific functions is still limited, despite the fact that mutations in IF genes cause numerous severe human diseases. In this work, three IF proteins are examined more closely; the nuclear lamin A/C and the cytoplasmic nestin and vimentin. In particular the regulation of lamin A/C dynamics, the role of nestin in muscle and body homeostasis as well as the functions and evolutionary aspects of vimentin are investigated. Together this data highlights some less well understood functions of these IFs. We used mass-spectrometry to identify inter-phase specific phosphorylation sites on lamin A. With the use of genetically engineered lamin A protein in combination with high resolution microscopy and biochemical methods we discovered novel roles for this phosphorylation in regulation of lamin dynamics. More specifically, our data suggests that the phosphorylation of certain amino acids in lamin A determines the localization and dynamics of the protein. In addition, we present results demonstrating that lamin A regulates Cdk5-activity. In the second study we use mice lacking nestin to gain more knowledge of this seldom studied protein. Our results show that nestin is essential for muscle regeneration; mice lacking nestin recover more slowly from muscle injury and show signs of spontaneous muscle regeneration, indicating that their muscles are more sensitive to stresses and injury. The absence of nestin also leads to decreased over-all muscle mass and slower body growth. Furthermore, nestin has a role in controlling testicle homeostasis as nestin-/- male mice show a greater variation in testicle size. The common fruit fly Drosophila melanogaster lacks cytoplasmic IFs as most insects do. By creating a fly that expresses human vimentin we establish a new research platform for vimentin studies, as well as provide a new tool for the studies of IF evolution.

Business models for Finnish biobanks

This study concentrates on developing a suitable business model for Finnish biobanks, with particular emphasis on value creation to stakeholders. The sub-objective of this thesis are to map the commercial possibilities of biobanks and potential barriers for business development. The study approaches the subject from the biobanks’ as well as the stakeholders’ point of view, integrating their hopes and needs considering current and future co-operation into the findings. In 2013 the Biobank Act came into effect, after which six biobanks have been established and several other pending biobank projects are in process. There is relatively little research in regard to the commercial opportunities of this newcomer of the biomedical industry, and particularly in the Finnish markets. Therefore, the aim of this study is to partially fill the research gap of the commercial potential of biobanks and particularly outline the problematic elements in developing business. The theoretical framework consists of a few select theories, which depict business modeling and value creation of organizations. The theories are combined to form a synthesis, which best adapts to biobanks, and acts as a backbone for interviews. The empirical part of the study was conducted mainly by seven face-to-face interviews, and complemented by two phone interviews and an e-mail questionnaire with four responses. The findings consist mainly of the participants’ reflections on the potential products and services enabled by consumer genomics, as well as perceptions on different obstacles for biobanks’ business development. The nature of the study is tentative, as biobanks are relatively new organizations in Finland, and their operation models and activities are still molding. The aim is to bring to surface the hopes and concerns of biobanks’ representatives, as well as the representatives of stakeholders, in order to transparently discuss the current situation and suggestions for further development. The study concludes that in principle, the interviewees’ agree on the need for development in order not to waste the potential of biobanks; regardless, the participants emphasize different aspects and subsequently lean on differing methods.