Browsing by Subject "Market research"

Sort by: Order: Results:

Now showing items 1-3 of 3
  • Lilja, Anna (Helsingin yliopisto, 2019)
    The aim of this study is to assess future export markets for the Finnish industrial wood construction sector. This is done by analysing secondary materials, previous studies and creating a future vision of Finnish industrial wood construction sector and particularly its exports by the year 2030. This analysis is based on qualitative individual expert interviews and a backcasting analysis using expert panel data. In addition, the study compares the current status of the forest industry exports and future assessments between Finland, Sweden and Estonia by analysing secondary materials, previous studies and expert views. The study was implemented using two different qualitative data sets. Semi-structured thematic expert interviews were collected from Finland, Sweden and Estonia. Expert interviews were used to get an in-depth understanding of the current status of the domestic industrial wood construction sector and the related export opportunities in Finland, Sweden and Estonia. A panel made up of Finnish experts were invited to create an ideal vision of the industrial wood construction sector in Finland and its exports for the year 2030. The panel gathered at a workshop, where their visions were created. In addition, pre- and post-event-questionnaires were part of the expert panel data collection, and this data was used to identify the most promising export countries/regions and the entities of exports in the industrial wood construction sector (e.g., whether to export materials, modules or construction projects). The results emphasised that concrete collaborative actions are needed as soon as possible in knowledge sharing and the industrial wood construction marketing. Based on the International market selection model (IMS), which is employed in this study and combining all the information from the workshop, interviews, literature and questionnaires have proven that the most promising future markets would be Central Europe, the UK and the Nordics by 2030. Otherwise the Finnish expert views of most promising export entities by 2030 varies between products, know-how and projects. During the research process it was realised that future markets need to take a closer look especially from the companies’ perspective. Finnish experts have varying views of the industrial wood construction export in their ideal vision for 2030. The study proved that the experts’ views were divided. Many of them desired that Finland should export more know-how and projects in 2030. Others believed that Finland should concentrate on the export of value-added materials. However, all the experts agreed that Finland should activate the local market and harmonize the regulations, which has had a positive influence on competence and know-how. In the ideal vision for 2030 Finland has improved its networks and co-operation inside the forest industry but also together with other fields. Finland has an open digital platform for knowledge sharing and the standards and regulations are more advanced. The wood construction industry is ideally in 2030 more attractive for students and experts than now, domestic market is wider and Finland has gained more experience and knowledge in the field of industrial wood construction. Finnish experts saw that the future exports markets for industrial wood construction are China, the Nordics, Germany, Russia and Central Europe. China was seen as an attractive market due to the size of the market, rising environmental awareness, wealthier middle class and increasing urbanization. However, China and other emerging countries have to be treated with caution, because they were not highlighted in the Estonian, Swedish or literature-based data analysis. Secondly, the Nordics construction culture is similar, location is nearby and the use of wood is increasing. Also, the harmonization of standards with Nordics came up in the expert data. Overall, the practise of industrial wood construction and environmental awareness are increasing in Europe, especially the countries where there are traditions in wood construction like countries in Central Europe. Swedish experts saw market potential and competitiveness in Central Europe and Eastern Europe, but the data from Sweden is limited to researchers’ opinions. The Estonian experts saw market potential in the UK, Germany and Ireland by 2030. However, the future markets for industrial wood construction needs a closer look as well as export entities, which divided the expert’s views.
  • He, Chen; Micallef, Luana; He, Liye; Peddinti, Gopal; Aittokallio, Tero; Jacucci, Giulio (2021)
    Understanding the quality of insight has become increasingly important with the trend of allowing users to post comments during visual exploration, yet approaches for qualifying insight are rare. This article presents a case study to investigate the possibility of characterizing the quality of insight via the interactions performed. To do this, we devised the interaction of a visualization tool—MediSyn—for insight generation. MediSyn supports five types of interactions: selecting, connecting, elaborating, exploring, and sharing. We evaluated MediSyn with 14 participants by allowing them to freely explore the data and generate insights. We then extracted seven interaction patterns from their interaction logs and correlated the patterns to four aspects of insight quality. The results show the possibility of qualifying insights via interactions. Among other findings, exploration actions can lead to unexpected insights; the drill-down pattern tends to increase the domain values of insights. A qualitative analysis shows that using domain knowledge to guide exploration can positively affect the domain value of derived insights. We discuss the study’s implications, lessons learned, and future research opportunities.
  • Zhang, Guangyi; Ashrafi, Reza A.; Juuti, Anne; Pietiläinen, Kirsi; Marttinen, Pekka (2021)
    Estimating the impact of a treatment on a given response is needed in many biomedical applications. However, methodology is lacking for the case when the response is a continuous temporal curve, treatment covariates suffer extensively from measurement error, and even the exact timing of the treatments is unknown. We introduce a novel method for this challenging scenario. We model personalized treatment-response curves as a combination of parametric response functions, hierarchically sharing information across individuals, and a sparse Gaussian process for the baseline trend. Importantly, our model accounts for errors not only in treatment covariates, but also in treatment timings, a problem arising in practice for example when data on treatments are based on user self-reporting. We validate our model with simulated and real patient data, and show that in a challenging application of estimating the impact of diet on continuous blood glucose measurements, accounting for measurement error significantly improves estimation and prediction accuracy.