We consider the following story. There is an oligopolistic industry in a country. The firms in the industry produce a homogeneous good. The firms can use a common new production technology which is more efficient than the present technology. The production cost with the newtechnology is lower than that with the present technology, however each firm in the industry must expend some fixed set-up cost to adopt and use the newtechnology. Adoption of newtechnology by firms is very important for economic growth of a country. However, it may be insufficient or excessive in less competitive industries from the point of view of social welfare. Then, subsidization or taxation by the government is necessary.
In the above model, the three boxes in dark borders show the relationship between various factors that influence the acceptance of technology. The box on the left indicates various factors influencing wireless technology I any given setting. The three categories of factors – hardware, software and telecommunication – affect the way in which wireless technology is implemented. The factors portrayed in the box are generic and their role to specific healthcare setting varies depending upon the level of implementation. Once the technology is implemented, it is expected to be used. In healthcare settings, it appears that the usage, relevance and need are the three most important influencing factors for the continual usage of newtechnology. Following the terminology used by Davies et al. (1989), we call these as mapping factors, as these mappings influence adoption of technology in healthcare settings. When the correct balance is established, users exhibit positive perceptions about using a newtechnology such as wireless handheld devices for data management purposes. This, in turn, brings out positive attitude towards using the system, both short and long term usage. The positive usage would then determine the intentions to use, resulting in usage behaviour. The usage behaviour then determines the factors that influence the adoption of newtechnology in a given setting. This is shown by the arrow that flows from right to left.
We present an analysis about adoption of newtechnology by firms in a duopoly with differentiated goods under absolute and relative profit maximization. Technology itself is free, but each firm must expend a fixed set-up cost, for example, for education of its staff. Under absolute profit maximization there are three types of sub-game perfect equi- libria depending on the value of set-up cost. Both firms, or one firm, or no firm adopt newtechnology. On the other hand, under relative profit maximization there are two sub-game perfect equilibria. Both firms, or no firm adopt newtechnology. And we show that if demand is sufficiently high, it is more probable that both firms adopt new tech- nology under relative profit maximization than that both firms, or one firm adopt newtechnology under absolute profit maximization.
We present an analysis about subsidy (or tax) policy for adoption of newtechnology in a duopoly with a homogeneous good. Technology itself is free. However, firms must expend fixed set-up costs for adoption of new technol- ogy, for example, education costs of their staffs. We assume linear demand function, and consider two types of cost functions of firms. Quadratic cost functions and linear cost functions. There are various cases of optimal poli- cies depending on the level of the set-up cost and the forms of cost functions. In particular, under linear cost functions there is the following case.
About social welfare and optimal policy, it has shown that optimal R&D investment is S-shaped with respect to competitiveness, and enhancement of competitiveness changes the optimal policy from taxation to subsidization . Their results and the results of this paper are similar, but the model in Matsumura et. al. (2013) is restricted to a symmetric equilibrium, and do not refer to fixed cost and the difference of cost functions. The model about technologyadoption behavior where newtechnology is exogenously given as this paper is discussed in Zhang et. al. (2014) which focuses on the uncertainty of R&D investment, and Hattori and Tanaka (2014) which focuses on the relation between technologyadoption and competitiveness using the relative profit maximization, but these do not analyze the social welfare. About social welfare, Pal (2010) shows that technologyadoption may change the market outcome, and the social welfare is larger in Cournot competition than in Bertrand competition. The model in Pal (2010) and the model of this paper are similar. But in Pal (2010) government’s policies are not analyzed. Moreover, Elberfeld and Nti (2004) focuses on the spillover of newtechnology, and Hattori and Y. Tanaka (2015) focuses on the difference of cost functions, and these claim the over or under investment for the society in some situation. This paper extends Hattori and Y. Tanaka (2015) to a case of various competitiveness.
The first criterion, suitability, describes whether the strategy is economically reasonable in terms of environment and capabilities. Bronder & Pritzl (1992) believe increasing competition and technology breakthroughs result in collaboration, which may allow the firm to better adapt in global markets. As firms are no longer an integrated unit of value chains, forming a network associated with operative cooperation and technology collaboration might be a wise choice. The European aerospace alliance, Airbus, formed in 1965, is a typical example of core competencies integration by European civil aircraft companies in order to compete against their common rivals, the American market leader, Boeing and McDonnell Douglas. Another example of a strategic alliance may be found between drug companies, Bayer Health Care AG and Millennium Pharmaceuticals in the biotech industry (Ziegelbauer & Farquhar, 2004). The goal of their collaboration is to beat other common rivals on time scale so that they could be first to patent partial DNA sequences and dominate the access to potential drugs discoveries. The area of cooperation/ collaboration does not only cover collaboration in technology, but also includes product development, service and operation management. The main purpose of the alliance therefore is to jointly compete with the dominant firms and greatly expand market share.
Eminent authors have been illustrated the main obstacles that lead to weaken the process of technologyadoption. For instance, Brinkerhoff (2006) illustrates that teachers often are not able to build on technology‟s instructional potential. This matter of fact relates to barriers such as institutional and administrative support, training and experience, attitudinal or personality factors, and resources as well. Thus, these obstacles are defined as ". . . any factor that prevents or restricts teachers‟ use of technology in the classroom". In relation to this issue, the British Educational Communications and Technology Agency (BECTA, 2003, 1) states that teacher-level barriers consist of the following factors: lack of time, lack of necessary knowledge, as well as the lack of self-confidence in using technology. However, barriers that surround the administrative level are the lack of: technical support, access to equipment, availability of up to-date software, and institutional support too. On the first hand, BECTA ,2003, (Redmann and Kotrlik, 2004, and Mumtaz, 2000)clarify that technology unavailability comes to be marked as an important element deterring the use of technology by teachers. On the second hand, (Park andErtmer,2008) adds that". . . a lack of a clear, shared vision was the primary barrier. Hence, other barriers may include the lack of sufficient knowledge and skills, unclear expectations, and insufficient feedback".
the situation turns around drastically from 1980s by registering high positive growth in foodgrains production. During the period 1981-82 to 1990-91, West Bengal shows 6.4 per cent annual growth in agricultural output (Saha and Swaminathan, 1994). Once the desired level of growth is achieved, the unsettled debate centering the alleged association between high rates of growth and instability in agricultural production has become a subject in the agricultural economic literature. Instability in production affects price stability and the consumers; it increases vulnerability of low income households to market and it is also important for food management and macro economic stability (Chand and Raju, 2009). Reviews of past literatures concerning the relationship between green revolution generated modern crop production technologies induced agricultural growth and instability present quite conflicting evidence. Mehra 1981, Hazell, 1982, Ray, 1983a, Rao et al. 1988 have reported that instability in agricultural production has increased with the adoption of newtechnology whereas Mellor (1966) and Mahendradev (1987) have concluded that the introduction of modern technology has resulted in impressive growth in food production and year to year variability in cereal production has grown up. Again, the survey of literature on sources of assumed instability in crop production shows that natural factors such as rainfall, temperature, flood, droughts etc. play dominant role in such production variability through fluctuation in area and yield. Taking all this issues into consideration, this study is a modest approach to examine growth rate of major crops of West Bengal during period 1950-51 to 2007-08, and an attempt will also be made to find out the relationship between technology induced growth and associated instability by dividing entire study period into three phases, a) pre green-revolution period, 1950-51 to 1964-65, b) initial phases of adoption of improved technology, 1965-66 to 1984-85 and c) post green revolution period , 1985-86 and onwards (Chand, and Raju, 2009). Another issue that will be discussed is the contribution of area and yield rise of individual crop on over all production growth.
2. Early Adopters (13.5%) – Early Adopters are also known as the Visionaries. These individuals love newtechnology and they procure and the use the technology before it in the hands of many. They appreciate, embrace and accept the solution for the problem that existed in the earlier technology. They can envision the impact and makes efforts for the technology to work. 3. Early Majority (34%) – Early Majority are also known
Australia‟s higher education sector. The findings further imply that university management groups need to develop plans for employees so that the new technologies are accepted more easily in tertiary institutions. Specific attention needs to be paid to freeing up time for employees so they can familiarize themselves with new technologies in terms of learning how to use them. The real and measurable benefits of using the innovation can be clearly delineated through pilot surveys of users of technological innovation. This is an important issue that needs to be addressed so employees can use an innovation as informed users. Furthermore, active support from internal peers and external social networks will enhance employees‟ ability to adopt innovative practices in the workplace. Besides this, resistance of university employees to the introduction of newtechnology adds to the complexity surrounding uptake of an innovation in the workplace. Although resistance to change is not a new issue in management literature, resistance of employees to technological change in an educational institution setting is of particular relevance to this paper. Employees‟ resistance to newtechnology or in other words „technophobia‟ may stem from the perceived fear resulting from uncertainty associated with the complexity of use, learning problems, extra workloads and additional time needed to familiarize oneself with newtechnology. Management needs to develop a well thought out strategy on managing resistance to adopting newtechnology at the organizational level. The strategy may include providing solid management support that directly reduces user resistance to newtechnologyadoption (Kim & Kankanhalli, 2009) and also tend to ease the use of an innovation (Lewis et al., 2003). Furthermore, senior management commitment to innovation implementation has been found to be instrumental in increasing the possibility of organizational support for the technological change (Kim & Kankanhalli, 2009). Since favorable opinion of peers about an innovation can contribute to countering resistance to a newtechnology, Massey et al. (2001) suggested that management can first influence opinion leaders in favor of the innovation to enhance acceptance by others.
The decision to adopt EVAR was driven by a few individu- als interested in adopting the newtechnology focusing on a very narrow range of factors. Communication was made with a hospital decision-maker and the Research Ethics Board to inform them of the procedure prior to adoption, however other departments that were affected should have been engaged in this process (such as the radiology department). Communication occurred primarily among the members of the vascular surgery department. Greater involvement from administration to identify financial constraints would have been beneficial to help avoid stop- ping EVAR once it began. A key hospital decision-maker at the time was a vascular surgeon, which may have posed a conflict of interest in the decision. On the other hand, it is possible that this decision-maker had better knowledge about the value of EVAR at a time when other stakehold- ers were less enthusiastic about its value.
influenced behavior of the small farmers regarding new farm technology. Truong (2008) says that there are many obstacles to running a successful technology strategy. The main reasons for non-adoption of technology are weak perceptions of technology and low education of farmers, low teaching capacities, limited knowledge among extension workers, disorganization, geographical conditions, and inadequate resources and funds. Furthermore, farmers should must have a certain level of education and be very familiar with rice farming in order to be motivated to learn newtechnology. The choice of farming technologies will continue to increase in the future. One problem, however, is the price of newtechnology, which is often high. Adopting new technologies can thus require making significant investments and farmers are only willing to invest money when it is profitable for them to do so. This can require expanding the scale of the farm operation through buying more farmland or livestock. Thus new technologies are a major driving force behind structural change resulting in fewer and larger farms, more machinery used on farms, and less manpower needed to run the farm (Gaemelke, 2001). Moreover, factors like age, education and gender also influence farmers’ willingness to invest.
Adoption on the other hand is also defined in different ways by various authors. Loevinsohn et al., 2013 defines adoption as the integration of a newtechnology into existing practice and is usually proceeded by a period of ‘trying’ and some degree of adaptation. Citing the work of Feder, Just and Zilberman (1985), Bonabana-Wabbi defines adoption as a mental process an individual passes from first hearing about an innovation to final utilization of it. Adoption is in two categories; rate of adoption and intensity of adoption. The former is the relative speed with which farmers adopt an innovation, has as one of its pillars, the element of ‘time’. On the other hand, intensity of adoption refers to the level of use of a given technology in any time period (Bonabana-Wabbi 2002).
A common theme of ICT research is the need to demonstrate returns on investments in underserved regions (Keniston, 2002). Other initiatives could include public/private partnerships, incentives for non-profit organizations, training and education programs or the provision of subsidized access for disadvantaged people and communities. Our research provides evidence that such subsidies can have a considerable impact on the adoption process. Future research in this area will attempt to quantify this effect. Homeland Security issues will lead to a substantial deployment of wireless resources in the areas of healthcare and public safety. This deployment will be particularly significant in rural areas because of the threat of bio-terrorism. These efforts will provide a model for the private sector and possibly some infrastructure.
The study shows that highest potential of wind energy is located in the East coast of Peninsular Malaysia with an annual vector resultant wind speed of 4.1m/s. The offshore characteristics were reportedly stronger than that of the coast with wind speed more than 5m/s during the northeast monsoon (September to March) but, low for the rest of the year. Hence, the offshore wind turbines adoption needs the areas of strong wind blows. Labuan Island at the South China Sea could be selected for this research.
Technology and technical capabilities are increasing in importance for us all. At home, in the classroom, at work, we’re using technology more. Technology is everywhere: it impacts virtually every area of our lives, from the appliances we use, to the infrastructure our cities are built on, to the ability of our companies to compete in global markets. As New Zealand makes the transition to a knowledge economy, and technology becomes more complex, individuals, companies and institutions increasingly need to specialise. For New Zealand, as a small country, the need is to maximise the resources of knowledge and capability that we do have. And that’s where CAE contributes: through linking New Zealand’s businesses, government agencies, academic and research institutions, we enable effective networking and collaboration, for the creation of new knowledge and opportunity.
The problem of the emergence of institutions is the starting point of classic economics (Elsner, 1986, 1989), also is the fundamental issue of the modern institutional economics. It is difficult to neglect that, some economists, mainly of self-deemed new institutionalists, argue that institutions, strictly are inanimate objects, can be designed artificially and therefore exogenously given. Actually, such so-called institutions are apparently designed, but they are just the external expressions of the existed results of social interactions that are endogenous in economy and related activities. For example, the establishments of laws always are the results of artificially designed, written and published by some experts and official organizations, but it is not the whole story of the emergence of laws indeed. In general, it is required by the objective needs of real worlds in which the people and some lawsuits have been harmed since lacking of proper laws or, of the strict implement of the laws. Moreover, it is natural to image some people have tried to find suitable law cases or legal provisions to remedy those problems, but it is not adequate to cover all potential loopholes. Hence, a lot of uncertainties and gambling will be emerged due to the imperfection of the legal system. As we are at the legislation, the different parties with own interests will definitely intervene the establishment of specific provisions, and finally, the established law will be a result of compromise, coordination as well as cooperation, or say, of series of games. Therefore, institutions have always been considered as the device to reduce uncertainties, but their emergence are frequently sketched as the results of strategic interactions of agents (Elsner, 1989, Lesourne et al., 2006), hence, a crucial question arises here is “why and in what ways do individuals coordinate their behavior ( Elsner, 1989, p.190)” in the process of something new comes out.
vii Lastly, to Momma and Daddy – I can’t even express my gratitude to you both. Daddy, growing up, I can remember random scientific conversations at the dinner table where you’d talk about lyophilization and chromatography. I had no idea what you were talking about, but I always knew you were so passionate about your career. You are a great example of loving what you do. Your satisfaction in your career makes me want to find something I am completely enthralled with. I have also admired your quiet sense of leadership. You don’t have to be a commander, but people still look up to and respect your opinion. Furthermore, you taught me to love traveling and discovering other cultures. I’ve had so many amazing experiences (and hope to have more) around the world. I’m not sure whether the Wanderlust gene is real or not, but your love to seeking new adventures was certainly passed down to me. Momma, you have always been my biggest supporter. You’d listen to me talk at the end of every day whether I was excited about something or just need to vent. I’ve always looked up to you, and you always put your girls first. You drove me all over the state for 4-H, horseback riding and piano lessons, and school functions. You drove me all over the country for 4-H competitions, work opportunities, etc. You sacrificed so all 3 of us could go to schools that were best for each of us. You’ve always had my back, and you always will. I know that whenever I need you, you are just a phone call away. You got me involved in 4-H because agriculture is in my blood, as is my love for animals (Daddy may have given me the Wanderlust gene, but you gave me the Animal People gene). So many of my life choices are because of values you instilled. Both of you are so important to me, and I am who I am because of you. Thank you. I know the only way I can pay you back is to make you proud – I hope to do everything I can to make that happen. I love you.
In terms of broader implications, our results show that, at sub-maximal levels of capacity utilisation, unit costs are dependent on quantity as well as build composition, as expressed by Ruffo and Hague (2007). Yet, if it is considered that the units of build space are capable of mutual substitution in AM, known as the property of “fungibility”, AM users are in principle able to drive up the degree of capacity utilisation through populating available machine capacity by inserting other parts, subject to manufacturability constraints. This observation suggests that to make any statement on efficient AM utilisation, as required by technologyadoption decisions, a problem of using the available capacity must be addressed. Whether this problem extends to other aspects such as machine scheduling forms a subject for future investigation.