19 resultados para technology acceptance model
Resumo:
This paper develops a two-period model with heterogeneous agents to analyze the e¤ects of transfers across locations on convergence, growth and welfare. The model has two important features. First, locations are asymmetric as it is assumed that there are more specialized occupations in the more developed one. Second, the returns on the investment to acquire new technology depend positively on the level of each region’s knowledge and on the level of the world knowledge assumed to be available to all. In one hand, the poor region has a disadvantage as it has a lower stock of knowledge. On the other hand, it has the advantage of not having yet exploited a greater stock of useable knowledge available in the world. Hence, there are two possible cases. When the returns are greater in the poor region, we obtain the following results: (i) the rich location grows slower; (ii) the transfers to the poor location enhances the country’s growth rate; and (iii) there is a positive amount of transfers to the poor region that is welfare improving. When the returns are greater in the rich region, the …rst two results are reversed and transfers to the rich region are welfare improving. In both cases, the optimal amount of transfer increases with the level of income disparity across regions and is not dependent on the level of the country’s economic development (measured by its income per capita). Barriers to the adoption of new technology available in the world can constrain the convergence process as it harms in greater length the poor region. The results do not change whether migration is allowed or not.
Resumo:
In 2000, the city of Barcelona launched 22@ Barcelona, dubbed the innovation district. The city sees the project as a means to accelerate Barcelona’s transition toward the knowledge economy. Other cities around the world have since followed the example of Barcelona, building or planning to build their own innovation districts. Boston began to establish its innovation district in 2010. Cities’ ultimate goal for these initiatives is to become more innovative and thus more competitive. Innovative districts are different from technology parks in that they aim to respond to a new economic paradigm in which economic production flows back to cities. The 22@ Barcelona model involves theoretical designs regarding five layers of innovation: economics, urban planning, productive, innovative, and creative. The comparative approach between 22@ Barcelona and Boston’s Innovation District intends to highlight the similarities and differences between those two innovation districts as well as providing a framework to define innovation districts.
Resumo:
In this paper, the learning intentions and outcomes for corporate venture capital are questioned. Through qualitative research in the oil and gas sector, we identified a desire to control the direction and pace of innovation as the main driver for this type of investments. A new model and framework for CVC are presented. Contrary to the traditional model of CVC, which features a dyadic relation between corporate investor and venture entrepreneur, our model shows that CVC investments create a more complex conjoint of relations between multiple stakeholders. These relations challenge the neo-Schumpeterian model of competition. Using the grounded theory approach, we created a theoretical framework explaining and predicting outcomes of corporate venture capital other than learning. At firm level, our framework conceptualizes CVC programs as dynamic capabilities, and suggests a competitive advantage for the corporate investor through its ability to faster and better integrate the new technology. At market level, we proposed that CVC investments positively affect the pace of innovation in the market through an increased speed of acceptance of technologies supported by corporate investors.
Resumo:
Since some years, mobile technologies in healthcare (mHealth) stand for the transformational force to improve health issues in low- and middle-income countries (LMICs). Although several studies have identified the prevailing issue of inconsistent evidence and new evaluation frameworks have been proposed, few have explored the role of entrepreneurship to create disruptive change in a traditionally conservative sector. I argue that improving the effectiveness of mHealth entrepreneurs might increase the adoption of mHealth solutions. Thus, this study aims at proposing a managerial model for the analysis of mHealth solutions from the entrepreneurial perspective in the context of LMICs. I identified the Khoja–Durrani–Scott (KDS) framework as theoretical basis for the managerial model, due to its explicit focus on the context of LMICs. In the subsequent exploratory research I, first, used semi-structured interviews with five specialists in mHealth, local healthcare systems and investment to identify necessary adaptations to the model. The findings of the interviews proposed that especially the economic theme had to be clarified and an additional entrepreneurial theme was necessary. Additionally, an evaluation questionnaire was proposed. In the second phase, I applied the questionnaire to five start-ups, operating in Brazil and Tanzania, and conducted semi-structured interviews with the entrepreneurs to gain practical insights for the theoretical development. Three of five entrepreneurs perceived that the results correlated with the entrepreneurs' expectations of the strengths and weaknesses of the start-ups. Main shortcomings of the model related to the ambiguity of some questions. In addition to the findings for the model, the results of the scores were analyzed. The analysis suggested that across the participating mHealth start-ups the ‘behavioral and socio-technical’ outcomes were the strongest and the ‘policy’ outcomes were the weakest themes. The managerial model integrates several perspectives, structured around the entrepreneur. In order to validate the model, future research may link the development of a start-up with the evolution of the scores in longitudinal case studies or large-scale tests.