<p>The aim of the research was to identify what female and male farmersthink are the best strategies to enhance the role of conservation farming as a buffer against social, economic and environmental hazards, and a means of ensuring livelihood sustainability and food security. The study also aimed at coming up with information useful to policy and other decision makers on how to improve adoption of these technologies. The empirical component of the research included a questionnaire survey of one hundred and fifty two(152) selected households in one identified ward in Insiza District, focus group discussions and semi-structured interviews with key informants and in-depth interviews of individual male and female members of a few selected farming households from the sampled population. The desktop portion of the study used secondary data from non-governmental organizations (NGOs), government and other stakeholders involved in conservation farming. Collected data was then disaggregated by gender and analyzed using the Statistical Package for the Social Sciences (SPSS). Perception statements that emerged as significant in chi-square tests of independence were be subjected to factor analysis and weighted factor scores from factor analysis were then used as independent variables in binary logistic regression analysis. The study concluded that both practising and non practising farmers were of the opinion that conservation farming was good though they indicated that information on conservation farming was not readily available The study found out that most farmers agreed on the possible positive effects of CA in addressing livelihood challenges effected by hazards such as HIV and AIDS and environmental hazards such as declining soil fertility but it had is labour intensive therefore is not suitable for people affected and infected by HIV and AIDS...</p>

Soil degradation and low crop productivity negatively affect the food security of smallholder farmers in West Africa. Various agricultural techniques have been developed as components of food security interventions, but their effectiveness in addressing food insecurity in part depends upon farmers’ willingness to adopt these techniques. Likewise, adoption depends upon the effectiveness of these techniques in fulfilling farmers’ objectives. The institutional and biophysical environments mediate not only the effectiveness of the techniques, but also how farmers value a technique. This study examined the evidence for fertilizer microdosing as a form of agricultural intensification and the socio-economic conditions that influence its adoption among smallholder farmers. A census was conducted in one village in northwest Benin that had recently seen the introduction of fertilizer microdosing. Key household-level determinants of adoption identified in the literature—household resources, household demographics, and access to inputs— were included in the household surveys. Using partial budgeting analysis and yield data from demonstration plots, the relative profitability of fertilizer microdosing was calculated as a necessary condition of adoption. Drawing from farmers’ stories, the potential value of microdosing was contextualized within the larger social and institutional context. Based upon the village census, there was little adoption outside of the research project that introduced microdosing to the village. Households using microdosing (predominantly found within the research project) had, on average, higher socio-economic status, more cultivable land and larger labour forces. Profitability analysis indicated that microdosing was on average less profitable than the point-source application of the recommended dosage rate in Benin (the common alternative). However, farmers still expressed a desire to microdose, due to poorly functioning input markets, poor infrastructure, and lack of access to financial instruments, all of which limited the availability, access and utilization of inorganic fertilizer.

Global cities have recognized the need to reduce greenhouse gas (GHG) emissions and have begun to take action to balance of the carbon cycle. This thesis examines the nuances of quantification methods used and the implications of current policy for long-term emissions. Emissions from waste management, though relatively small when compared with building and transportation sectors, are the largest source of emissions directly controlled by municipal government. It is important that municipalities understand the implications of methodological selection when quantifying GHG emissions from waste management practices. The “Waste-in-Place” methodology is presented as the most relevant for inventorying purposes, while the “Methane Commitment” approach is best used for planning. Carbon sinks, divided into “Direct” and “Embodied”, are quantified using the Greater Toronto Area (GTA) as a case study. “Direct” sinks, those whose sequestration processes occur within urban boundaries, contribute the largest share of carbon sinks with regional forests providing a significant proportion. “Embodied” sinks, those whose sequestration processes (or in the case of concrete, the processes that enable sequestration) are independent of the urban boundary, can contribute to the urban carbon pool, but greater uncertainty exists in upstream emissions as the management/processing prior to its use as a sink are generally beyond the consumer’s purview. The Pathways to Urban Reductions in Greenhouse gas Emissions (or PURGE) model is developed as a means to explore emissions scenarios resulting from urban policy to mitigate climate change by quantifying future carbon sources/sinks (from changes in building stock, vehicle stock, waste treatment and urban/regional forests). The model suggests that current policy decisions in the GTA provide short-term reductions but are not sufficient in the long term to balance the pressures of economic and population growth. Aggressive reductions in energy demand from personal transportation and existing building stock will be necessary to achieve long-term emissions targets.

Global cities have recognized the need to reduce greenhouse gas (GHG) emissions and have begun to take action to balance of the carbon cycle. This thesis examines the nuances of quantification methods used and the implications of current policy for long-term emissions. Emissions from waste management, though relatively small when compared with building and transportation sectors, are the largest source of emissions directly controlled by municipal government. It is important that municipalities understand the implications of methodological selection when quantifying GHG emissions from waste management practices. The “Waste-in-Place” methodology is presented as the most relevant for inventorying purposes, while the “Methane Commitment” approach is best used for planning. Carbon sinks, divided into “Direct” and “Embodied”, are quantified using the Greater Toronto Area (GTA) as a case study. “Direct” sinks, those whose sequestration processes occur within urban boundaries, contribute the largest share of carbon sinks with regional forests providing a significant proportion. “Embodied” sinks, those whose sequestration processes (or in the case of concrete, the processes that enable sequestration) are independent of the urban boundary, can contribute to the urban carbon pool, but greater uncertainty exists in upstream emissions as the management/processing prior to its use as a sink are generally beyond the consumer’s purview. The Pathways to Urban Reductions in Greenhouse gas Emissions (or PURGE) model is developed as a means to explore emissions scenarios resulting from urban policy to mitigate climate change by quantifying future carbon sources/sinks (from changes in building stock, vehicle stock, waste treatment and urban/regional forests). The model suggests that current policy decisions in the GTA provide short-term reductions but are not sufficient in the long term to balance the pressures of economic and population growth. Aggressive reductions in energy demand from personal transportation and existing building stock will be necessary to achieve long-term emissions targets.

The prices of technological equipment have seen significant declines in recent decades. In Chapter 2 of this thesis, we examine the evidence and causes of these price declines. Among several factors, we focus on the learning curve effect where the cost of producing technological equipment declines as the cumulative number of produced units increases. In Chapter 3 we review the literature on technology adoption and the timing decisions of such adoptions. We aim to contribute to the literature by examining the timing of technology adoption under price declines. Furthermore, we consider the effect of human capital on such adoption decisions. We begin in Chapter 4 by developing a model of the timing of technology adoption under an exogenous price decline. Section 1 considers a single price drop in followed by multiple price drops in section 2. From the analytical results developed in these sections, we examine the effect of human capital on the adoption decision. Chapter 5 considers the price of the technological equipment to be endogenous to the model. We run computational experiments to demonstrate the declining price as a function of time. We examine the effect of the distribution of human capital on the price decline and adoption decision of the individuals of the population. We conclude with insights on the relationship between human capital inequality and technology adoption decisions.

Background:  Marketing is evolving because of Big data, and there are a lot of possibilities as well as challenges associated with Big data, especially for small and medium-sized companies (SMEs), who face barriers that prevent them from taking advantage of Big data. For companies to analyze Big data, Big data analytics are used which helps companies analyze large amounts of data. However, previous research is lacking in regard to how SMEs can implement Big data analytics and how Big data analytics are perceived by SMEs. Purpose:  The purpose of this study is to investigate how the employees of Swedish SMEs perceive Big data analytics. Research Questions: How do employees of Swedish SMEs perceive Big data analytics in their current work environment? How do the barriers impact the perceptions of Big data analytics? Methodology: The research proposes a quantitative cross-sectional design as the source of empirical data. To gather the data, a survey was administered to the employees of Swedish companies that employed less than 250 people, these companies were regarded as SMEs. 139 answered the survey and out of those, the analysis was able to use 93 of the answers. The data was analyzed using previous theories, such as the Technology Acceptance Model (TAM). Findings: The research concluded that the employees had positive perceptions about Bigdata analytics. Further, the research concluded that two of the barriers (security and resources) analyzed impacted the perceptions of the employees, whereas privacy of personal data did not. Theoretical Implications: This study adds to the lacking Big data research and improves the understanding of Big data and Big data analytics. The study also adds to the existing gap in literature to provide a more comprehensive view of Big data. Limitations: The main limitation of the study was that previous literature has been vague and ambiguous and therefore may not be applicable. Practical Implications: The study helps SMEs understand how to better implement Big data analytics and what barriers need to be prioritized regarding Big data analytics. Originality: To the best of the author’s knowledge, there is a significant lack of academic literature regarding Big data, Big data analytics and Swedish SMEs, therefore this study could be one of the pioneer studies examining these topics which will significantly contribute to current research.

Mobile phone usage involves the mobile phone, the telecommunications system, mobile phone users, and the adoption and use of the system. Mobile communications is a complex and rapidly changing industry consisting of the hardware, software, network and business aspects. Mobile phone users are influenced by demographic, social, cultural and contextual factors that complicate the understanding of mobile phone usage. Advances in technology and market competition drive the addition of new services and features. In contrast, human cognition and attention are more constrained and many users find it difficult to cope with the cognitive demands of mobile phone technology. The aim of this study is to develop a model for representing the influence of motivational needs and cultural factors on mobile phone usage variety. The link between motivational needs and mobile phone usage variety, the cultural factors that influence mobile phone usage variety, as well as usage spaces as an approach to representing usage variety, are researched. The research encompasses a literature study, structured interviews, a pilot study and a survey. The pilot study and survey yielded data about mobile phone usage of university students under the age of 30 in South Africa. The results from the statistical analysis were triangulated with the findings of the literature study and the observations made about mobile phone usage during this two-year period. A final survey was conducted to verify the model. The contribution of this study is a mobile phone technology usage model (MOPTUM) for representing the motivational and cultural factors that influence mobile phone usage variety in such a way that users can use the model to express their mobile phone usage needs in non-technical terms while marketers and designers can use the model to convert the expressed user needs into the features required. MOPTUM draws on concepts and models from sociology, computer-supported cooperative work, human-computer interaction and technology adoption models from the field of marketing. MOPTUM verifies some existing findings on mobile phone usage and then integrates and extends these existing models to provide a new model for understanding the motivational and cultural factors that influence mobile phone usage variety. / Computing / Ph. D. (Computer Science)

Made available in DSpace on 2016-08-02T21:42:17Z (GMT). No. of bitstreams: 1 Fabiana Martins de Souza Tacco.pdf: 1002317 bytes, checksum: 0571bc5b8a176b075343ed0217522897 (MD5) Previous issue date: 2011-07-27 / The acceptance and use of Information Technology (IT) by the individual have been studied by different conceptual models that, in general, derived from theories of psychology as the TRA - Theory of Reasoned Action and TPB - Theory of Planned Behavior, derived from the first. An important analysis&#8223; model derived from it, resulted of thorough analysis of eight other previous models, for while UTAUT - Unified Theory of Acceptance and Use of Technology in VENKATESH et. al. (2003) has been extensively analyzed and validated in many scenarios and technology environments. This work seeks to understand a broader way of background factors on the intended use and usage behavior UTAUT from the model, as well as the factors that best explain the intention and usage behavior, as well as the analysis of moderators. In its development, Venkatesh et al. made comparisons in three deployment stages and in two scenarios: in mandatory adoption, the one that occurred in a business environment where the system is required to process execution and decision making, and voluntary adoption scenario in which the adoption takes place by the individual. In the second case, the authors concluded that "social influence" factor has a low magnitude and significance, not being revealed as an important factor in technology adoption. This study aims to examine too whether the same phenomenon occurs that is given up for voluntarily adoption, but able to be highly influenced by social ties, such as occurs among users of social networks like Orkut, Facebook, Twitter and Linkedin, especially in technologies that enable the financial gains associated with these ties, such as the use of collective purchasing sites such as Peixe Urbano, Clickon and Groupon. Based on the model UTAUT, we applied a research and were later analyzed the results of 292 respondents who were validated accessed through social networks. The technique used consisted of using structural equation modeling, based on PLS - Partial Least Square, with 1000 bootstrap re-sampling. The results demonstrated high predictive significance and magnitude of the Intention of technology use by factors of Expected Desempenho (0,288 @ 0.1%), and Social Influence (0,176@ 0, 1 %),). The first, consistent with previous studies. Since the magnitude and significance of the latter factor resulted in vastly superior to the original study by Venkatesh et al. (2003) ranged between 0.02 to 0.04, not significant, depending on the data are grouped or not (p.465). The main conclusion of this study is that when considering the phenomenon of collective purchasing in an environment of voluntary adoption, therefore, the social factor is highly influential in the intention to use technology, which contrasts strongly with the original study of UTAUT and presents several possibilities for future research and managerial implications. / A aceitação e o uso de Tecnologia da Informação (TI) pelo indivíduo têm sido estudadas por diferentes modelos conceituais que, em geral, derivaram de teorias da Psicologia como a TRA Theory of Reasoned Action e a TPB Theory of Planned Behavior, derivada da primeira. Um importante modelo de análise dai derivado, resultado da minuciosa análise de outros 8 modelos anteriores, o UTAUT - Unified Theory of Acceptance and Use of Technology de VENKATESH et. al. (2003) tem sido largamente analisado e validado em vários cenários de tecnologia e ambientes. Este trabalho visa compreender de uma maneira mais ampla dos fatores antecedentes da intenção de uso e comportamento de uso a partir do modelo UTAUT, bem como os fatores que melhores explicam a intenção e o comportamento de uso, assim como a análise de seus moderadores. Em seu desenvolvimento, Venkatesh et al. empreenderam comparações em três etapas de implantação e em dois cenários: na adoção mandatória, aquela em que se deu em ambiente empresarial onde o sistema é requerido para execução de processos e tomada de decisões, e na adoção voluntária, cenário em que a adoção se dá pelo indivíduo. No segundo caso, os autores concluíram que o fator influência social tem baixa magnitude e significância, não se revelando um fator importante na adoção da tecnologia. Este trabalho visa analisar também se o mesmo fenômeno ocorre para adoção que se dá de forma voluntária, mas passível de ser altamente influenciada pelos laços sociais, como o que ocorre entre usuários das redes sociais como Orkut, Facebook, Twitter e Linkedin, especialmente em tecnologias que habilitam ganhos associados ao exercício desses laços, como no caso do uso de sites de compras coletivas tais como Peixe Urbano, Groupon e Clickon. Com base no modelo UTAUT, foi aplicada uma pesquisa e posteriormente foram analisados os resultados de 292 respondentes validados que foram acessados por e-mails e redes sociais. A técnica de análise empregada consistiu do uso de modelagem por equações estruturais, com base no algoritmo PLS Partial Least Square, com bootstrap de 1000 reamostragens. Os resultados demonstraram alta magnitude e significância preditiva sobre a Intenção de uso da tecnologia pelos fatores de Expectativa de Desempenho (0,288@0,1%), Influência Social (0,176@0,1%). Os primeiro, compatível com estudos anteriores. Já a magnitude e significância do último fator resultou amplamente superior ao estudo original de Venkatesh et al. (2003) variando entre 0,02 a 0,04, não significante, dependendo dos dados estarem agrupados ou não (p.465). A principal conclusão deste estudo é que, ao considerarmos o fenômeno das compras coletivas, em um ambiente de adoção voluntária, portanto, o fator social é altamente influente na intenção de uso da tecnologia, o que contrasta fortemente com o estudo original do UTAUT (já que no estudo de Venkatesh et al. (2003) este fator não foi significante) e apresenta várias possibilidades de pesquisas futuras e possíveis implicações gerenciais.

A computação em nuvem emerge quando se trata da necessidade dos desenvolvedores de TI de sempre aumentar ou incluir novas capacidades, o mais rápido possível, com o menor investimento possível. Ela vem sendo apontada como uma das maiores inovações em TI nos últimos anos e por isso vem chamando a atenção tanto da comunidade acadêmica quanto da comercial. Apesar deste crescente interesse na tecnologia pela literatura acadêmica, a maior parte do foco das pesquisas se dá nos aspectos técnicos, como potencial computacional e custos. Pesquisas sobre as preferências dos profissionais da área relativa à computação em nuvem como uma ferramenta de negócios estão limitadas a estudos de consultorias e empresas privadas. Esta pesquisa tem como objetivo apresentar um estudo do impacto de diferentes dimensões sobre a intenção de adoção da computação em nuvem por profissionais de TI. Para isto, utiliza uma variação do modelo TAM/UTAUT para verificação de intenção de adoção de novas tecnologias. O método escolhido foi a pesquisa survey, realizada a partir de um instrumento previamente proposto e adaptado, sendo feita em duas etapas: estudo de pré-teste e estudo final. Diferentes técnicas estatísticas foram empregadas para refinar o instrumento, como Análise de Confiabilidade, Análise Fatorial Exploratória e Análise Fatorial Confirmatória, utilizando o método PLS (Partial Least Squares) para Equações Estruturais. Como resultado deste refinamento emergiu um modelo teórico de pesquisa final contendo 8 dimensões e 36 itens. Como contribuição para a área de SI, o modelo teórico de pesquisa final se mostrou adequado para avaliar a intenção de adoção da computação em nuvem por profissionais de TI. A principal contribuição da pesquisa para a prática gerencial é o modelo de intenção de adoção da computação em nuvem, que pode auxiliar provedores de computação em nuvem, através da mensuração das principais razões para sua adoção, que são Utilidade Percebida e Atitude Frente à Inovação Tecnológica. Também demonstra que não existe uma relação positiva entre Segurança e Confiança e a Intenção Comportamental. Doze hipóteses foram validadas e seis das hipóteses propostas foram negadas pelos dados. Estas informações buscam fornecer material para que se possa inspirar os esforços no desenvolvimento da tecnologia como ferramenta de negócio. / Cloud computing emerges when we talk about the necessity of the IT developers to always increase or add new capabilities, as soon as possible, with the lowest investment possible. It has been appointed as one of the biggest IT innovations in the recent years, and for that reason it’s been calling the attention of the academic and management communities. Even with the growing interest by the academic community, most of the research focus on technical aspects, such as computational potencial and costs. Researches involving professionals’ preferences with cloud computing as a business tool are limited to consultant and private studies at most. This research has the purpose of presenting a study about the impact of different dimensions in the intention of adoption of cloud computing by IT professionals. To do so, it uses a variation of the TAM/UTAUT model for the verification of the intention of adopting new technologies. The research method is the survey research, made with a previously proposed and adapted instrument, conducted in two stages: pre-test study and final study. Different statistical techniques were used to refine the instrument, such as Reliability Analisis, Exploratory Factor Analysis and Confirmatory Factor Analysis, this one using the PLS (Partial Least Squares) Path modeling for SEM (Structural Equation Modeling). As a result of this refinement, emerged a theorical research model containing 8 dimensions and 36 measuring items. As contribution to the IS area, the theorical model proved adequate to assess the intention of adoption of cloud computing by IT professionals. The research’s main contribution to the business practice is the model of cloud computing intention of adoption, that aids cloud providers, trought the measurement of the main reasons behind the adoption of the technology, wich are Perceived Utility and Attitude Towards Technology Innovation. Also demonstrates that there are no positive relation between Security and Trust and the Behaviorial Intention. Twelve of the hypothesis were sustained, and six of the proposed hypothesis were denied by the data. This information intends to inspire efforts in developing the technology as a business tool.

Utilisant des données sur les expéditions de robots industriels, ce document constate que les secteurs volatils sont automatisés de façon disproportionnée dans les pays avec des règles strictes sur le licenciement. L'idée derrière le résultat empirique est que contrairement aux travailleurs humains, les entreprises peuvent disposer librement des robots, tout comme avec tout autre bien de capital. Puisque les droits des robots ne sont pas protégés par la loi, ils fournissent des services de main d’œuvre à volonté. L'incitation à l'automatisation apportée par la réglementation est plus forte dans les secteurs volatils, où l'incertitude sur les conditions d'affaires augmente les exigences de flexibilité des entreprises. Mes estimations prédisent que dans les secteurs incertains, le pays le plus réglementé (l'Italie) devrait être deux fois plus automatisé que le plus réglementé (États-Unis). Les données montrent que le nombre de robots par employé en Italie est 90% plus élevé qu'aux États-Unis. La stratégie d'identification consiste à exploiter le calendrier différent dans les réformes du travail entre les pays. L'identification provient de l'effet avant-après sur l'investissement sectoriel dans les robots dans les pays réformés (le "groupe de traitement"), vis-à-vis de l'effet avant-après dans les pays où l'EPL n'a pas changé (le "groupe témoin"). Ce document explique pourquoi les entreprises investissent dans l'automatisation. Contrairement à la sagesse conventionnelle, les robots n'augmentent pas la productivité parce qu'ils sont meilleurs ou plus rapides à faire les choses, mais plutôt parce qu'ils augmentent l'efficacité de la répartition. Le lien entre réglementation et automatisation implique que la politique du marché du travail peut être utilisée pour atténuer l'effet perturbateur de la technologie. / Using data on shipments of industrial robots, this paper finds that volatile sectors are disproportionally automated in countries with strict rules on employment dismissal. The idea behind the empirical result is that unlike for human workers, firms can freely dispose of robots, just as with any other capital good. Since robot’s rights are not protected by law, they deliver labor services at will. The incentive to automate induced by regulation is stronger in volatile sectors, where uncertainty about business conditions increase the flexibility requirements of firms. My estimates predict that in uncertain sectors, the most regulated country (Italy) should be twice as automated as the least regulated one (the United States). Data show that the number of robots per employee in Italy is 90% higher than in the United States. The identification strategy consists in exploiting different timing in labor re-forms across countries. Identification comes from the before-after effect on sectorial investment in robots in reformed countries (the \treatment group"), vis-a-vis the before-after effect in countries where EPL did not change (the \control group").This paper sheds light on why firms invest in automation. In contrast to conventional wisdom, robots do not increase productivity because they are better or faster at doing things, but rather because they increase allocative efficiency. The link between regulation and automation implies that labor market policy can be used to mitigate the disruptive effect of technology.