The paradigm of diffusion research can be traced back all the way to the 1940s when Ryan and Gross investigated the diffusion of hybrid seed among farmers in Iowa. Since the 1960s diffusion research has been applied in a wide variety of disciplines, for instance, to study the diffusion of the Internet and the non-diffusion of the Dvorak keyboard. Currently, the technologies that are on top of the Gartner Hype Cycle are all associated with Artificial Intelligence (AI), which shortly can be defined as learning devices that perceive their environment and take actions to maximize their success at some goal. Consequently, some people suggest that the current hype surrounding AI can be the end of the human kind, while others believe it will give way for millions of fresh jobs and cleverer decision-making. In recent years both media and political organizations have shown great interest in AI. In addition, the industry is captivated by the potential uses of AI. In the last years, AI-related companies in the US have raised billions of dollars in the stock market together with a large number of acquisitions. The large flow of capital into AI technology underpins the fast development of AI solutions. The purpose of this study is to investigate how groups approach AI. What can be concluded after reviewing different sectors is that organizations seem to share a common interest of AI. Furthermore, organizations share the opinion that eventually AI will be a more natural part of their processes. Organizations investing a larger share of their budget in R&D have a longer experience of using AI and are currently doing projects utilizing more advanced technologies within AI. In organizations from other sectors, the investments in AI depend on the people with the authority to invest money in projects and their view on AI. Organizations generally seem to approach AI in a similar way. Firstly, they evaluate what AI is. Secondly, they find areas to make small iterative PoC-projects utilizing AI, usually with machine learning. Finally, more money is invested if the PoC-projects were successful and the organization starts looking at how to acquire more competence within the area to fully exploit the value of AI. / Paradigmet för innovationsspridning kan spåras ända tillbaka till 1940-talet när Ryan och Gross undersökte spridningen av hybridfrön bland bönder i Iowa. Sedan 1960-talet har forskningen tillämpats inom en mängd olika discipliner, till exempel för att studera spridningen av Internet och icke-spridningen av Dvorak-tangentbordet. För närvarande är teknologierna som ligger på toppen av Gartner Hype-cykeln alla förknippade med artificiell intelligens (AI), som kan definieras som lärande enheter som uppfattar sin miljö och vidtar åtgärder för att maximera sin framgång gällande något mål. Hypen som nu finns kring AI har lett till att vissa människor tror att det kan innebära slutet för mänskligheten medan andra tror att det kommer att ge plats för miljoner nya jobb och smartare beslutsfattande. Under de senaste åren har både medier och politiska organisationer visat stort intresse för AI samt visat intresse för potentiella användningsområden av AI. AI-relaterade företag i USA har under de senaste åren har tagit in miljarder dollar i riskkapital. Ett stort antal förvärv och kapitalflödet till AI-teknik ökar den snabba utvecklingen av AI-lösningar. Syftet med denna studie är att beskriva spridningen av AI i organisationer från ett antal olika sektorer. Vad som kan sägas efter att ha studerat olika sektorer är att organisationer delar en gemensam nyfikenhet för AI och att de tror att AI kommer bli en allt mer naturlig del av sina processer. De företag som spenderar mycket pengar på FoU har längre erfarenhet av att använda AI och gör för närvarande projekt som använder mer avancerade tekniker. I andra organisationer är investeringarna inom AI beroende av de anställda som har rätt att investera pengar i projekt och deras syn på AI. Organisationer verkar allmänt närma sig AI på ett liknande sätt där de först utvärderar vad AI är. Därefter väljer de ett antal områden där de gör små iterativa projekt där de utnyttjar AI, vanligtvis via ML. Därefter investerades mer pengar om de små projekten lyckas och företaget börjar titta på hur man kan förvärva mer kompetens inom området.

The concept of Sustainable Forest Management (SFM) has been promoted in the past few decades all over the world. Non-industrial private forest (NIPF) owners play an important role in that aspect in the U.S. because of their number (about 16 millions), the size of forest land under their control (about half of all forest land in the continental US), and the dynamism of their population (increasing number of new owners). This study sought to better understand how NIPF owners come to a decision for adoption (or non-adoption) of SFM practices. We developed a theoretical model combining four theories (the Value-Belief-Norm theory, the Theory of Planned Behavior, the Elaboration Likelihood Model, and the Innovation-Diffusion Process) to explain NIPF's decision making. Using multivariate analyses, we determined which elements of the developed theoretical model were significant in explaining adoption of eight groups of practices. Overall, some of the most significant predictors of adoption we identified were technical assistance, motivations for owning land and the use of a written management plan. Particular attention was also directed toward the eventual relationship between education and adoption of SFM practices and it was found that NIPF owners who attended educational programs tended to be likely adopters compared to those who did not attend any educational program. Since SFM was not limited to the US, we also analyzed the concept of SFM with the same goals as in the US, but under a completely different context (socio-cultural, economic and ecologic) in Africa, through the community-based natural resource management (CBNRM) system. We used four case studies and focused on criteria such as participation, equity (both procedural and distributive, power devolution, trust, etc) to analyze how CBNRM works on the field, what lessons to take from the cases to better ensure the goal of sustainability of the resources. / Ph. D.

Object of study: The innovation “Digital health care center” from a multi-level stakeholder’s perspective. Problem: A new technology era has opened up for new kind of innovations. Digital health care centers are a service that recently has been introduced on the Swedish market, which needs further investigation. To be able to better understand, explain and predict future behavior of an innovation the innovation could be theoretical conceptualized and classified. In the specific area of health care, new innovation should preferable be investigated in from a multilevel perspective, including different stakeholders opinions. One if the stakeholders are the customers. If new innovative products and services want to be successful, it required consumers to adopt the product or service, but relatively few studies have focused on the adoption of technology services among customers. Purpose: The purpose of this thesis is to gain a better understanding of the innovation “digital health care center” in Sweden. Research question: How can the innovation “digital health care center” be described through a stakeholder perspective? Method: The empirical data were collected through qualitative semi-structured interviews and a structured quantitative questionnaire. Conclusions: The innovation digital health care center can from a multi-level perspective be described as an innovation that contributes and have an impact on the market and the healthcare industry in many ways. The innovation could be described as a complement to traditional health care. The innovation has influences from different theoretical classes of innovation which means that the innovation cannot be categorized in a specific class. The innovation can be considered successful because it facilitates for the patient.. According to the stakeholder group potential patients, a majority of the respondents thinks that increased availability and time-efficiency would be facilitating factors and reasons for using the service. The innovation is described by the various stakeholders as contributing to a better society. The care becomes more productive, cost effective, more available, and in the broader perspective, the innovation contributes to increased digitalization of the healthcare sector as a whole. There are many new possible fields of application which in the healthcare industry which could develop the innovation further. Strengths and opportunities with the innovation can be considering outweighing weaknesses with the innovation and potential threats of the innovation.