The adoption and use of three Web 2.0 technologies (web conferencing, eSurveys, and YouTube videos) were studied using the following four adoption models: the Diffusion of Innovations, the Unified Theory of Acceptance and Use of Technology, the Adoption and Diffusion Outcome Prediction Tool (ADOPT), and Switch: How to change things when change is hard. It is believed that this research study comparing four quite divergent models is the first of its kind attempted, and similarly its focus on the adoption of Web 2.0 technologies.
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The biplot of the first two principal components (as shown in Figure 107) indicates that the questions form clusters with similar responses. For example, questions Q7.11 (senior mangt), Q7.12 (org support), Q7.13 (resources) and Q7.16 (assistance) appear to be quite correlated and would possibly be collecting the same sort of information. It would be possible to label that cluster ‘corporately supported’ to summarise the variables involved. The same is true for Questions 7.1 (useful), Q7.6 (skilful), Q7.7 (easy to use), Q7.8 (learning easy), Q7.10 (important people), Q7.14 (knowledge) and Q7.15 (compatible) forming another cluster. That cluster is more difficult to label as no one or two terms seem to summarise the rather diverse variables. The ones that contributed most to PC1 were Q7.7 (easy to use), Q7.10 (important people), Q7.15 (compatible), so perhaps ‘easy and compatible’ could be its label. Questions 7.4 (promotion), 7.5 (clear), 7.9 (influencers), 7.3 (productive) and 7.2 (quick) tend to be more separated from the other questions, and so don’t appear to have any strong connections. Question 7.4 (promotion) is nearly at right angles to 7.3 (productive), and so can be considered to be probably independent. Question 7.2 (quick) is nearly at right angles to the ‘corporately supported’ cluster of questions, so can be considered independent of those. So overall, what this indicates is that in the UTAUT model there are two main clusters of variables that promote adoption of the technologies – ‘corporately supported’ and ‘easy and compatible’.
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The literature reviews are obviously very theoretical. To validate what was found in the literature, a case study has been carried out. This will give a practical reflection on the theoretical findings of this research. An interview has been conducted with Boban Vukicevic, managing director of the Dutch company Comgate. The company Comgate calls itself the ‘one-stop-shop’ for Internet of Things solutions. Together with their IT-, software- and hardware-partners, they provide enterprises with a wide range of IoT services. Their main services are software, hardware, connectivity, consultancy and managed services. There were two reasons why Vukicevic was approached for this interview, besides being managing director of Comgate. First of all, he wrote an article on the website Marketingfacts, titled ‘Internet of Things shouldn’t be a toy for technicians’ (Vukicevic, 2018). In this article he discusses the importance of a management team that is convinced about the potential of Internet of Things and supports it. Furthermore, he states that Internet of Things creates a very complex environment which will influence industry structures, change the nature of competition and exposes enterprises to new opportunities and threats. The second reason is Vukicevic’ book ‘Implementing the Internet of Things’ together with Emmerson (2017) . In this book they write about the critical business and management issues when implementing Internet of Things. They also state that “these aspects are often overlooked, particularly in on-line articles and papers, mostly because IoT is still seen as a topic for engineers and IT manager” (Vukicevic & Emmerson, 2017, p. 10). This is an interesting overlap with this research, as that is what the literature review on IT adoption models and Internet of Things adoption challenges also showed.
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The convergence of technologies has broadened the scope of applications possible today that were not realisable until just a few years ago. Augmented Reality (AR) is one such technology that has been actualised recently owing to the rapid evolution and adoption of smartphone technologies. Built on ubiquitous devices like smartphones, the adoption of multimodal & multi-use technologies like AR has not been correspondingly fast. This study’s scope is to investigate the why and the how of the AR adoption process. Existing technology adoption models, although quite extensive, were formulated and used in a decade where technology-user interaction was one-dimensional in nature. However, owing to the increasing complexity of recent technologies, this interaction between the technology and the user has become immensely dynamic and complex as well, highlighting the insufficiency of current models to understand AR adoption better. Therefore, an exploratory study is undertaken to identify the user motivation to use AR applications on their smartphones to develop a holistic perspective of this process. This study conducted 18 in-depth interviews with smartphone AR users to understand their motivation, perception, attitude and usage of AR applications. The findings of the study suggest that apart from the already identified constructs in various technology adoption models, there are 5 key concepts that play important roles in this process, namely - 1) hedonistic or utilitarian projected attributes on the technology by the user, 2) context of interaction between the user and technology, 3) goal of the interaction, 4) motivators and 5) inhibitors that influence the interaction. Furthermore, this study identifies 4 major user motivations that push or pull a user to interact and continually use a technology - 1) to control, 2) to belong, 3) to escape, and 4) to explore. The findings of this study present a macro-perspective in the technology adoption process of AR applications on smartphones. It also proposes to adopt a social constructionist
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commitment and maturity of the deployment for those in the evaluation/trial stage will differ greatly from those classified as a general deployment. Only if adoption studies classify their sample by stage can the level and commitment to that adoption be determined and stage specific barriers and drivers identified. A study that does not classify its sample risks missing stage significant factors due to heterogeneous sample composition and potentially limits comparability and generalizability. Examples of the application staged adoption models to information technologies can be found dating back to the early days of mass-market computing (e.g. ). However, while existing studies of OSS have sought to examine drivers and barriers to OSS adoption (e.g. [23, 30, 31]), few have identified at what stage adoption is within a unit of analysis . When staged adoption models are used in OSS studies, critique of the models is limited, even where shortcomings have already been identified in their native field . This paucity of use and critique contrasts with practice in similar literature, such as the adoption of e-business systems. This field has benefited from numerous staged adoption models [34, 35], with this pedigree leading to critique and the development of more complex contingent  and latterly hybrid models .
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Adoption rates for HISs are variable and there are range of reasons for low adoption rates [46,47]. The CAMM was developed from a need to provide a focused descrip- tion of how HIS benefits could be achieved over time (or not) and to fill a perceived gap in the literature. Highlighted in Table 2, the CAMM differs from many generic adoption models, such as the diffusion of innovation, TAM, and UTAUT, as it is contextualized to the clinical domain. And, unlike several clinical adoption models, such as the PACS maturity model [32,33], the HIMSS EMRAMs [29,30], or EMR Adoption Model , the CAMM is less focused on purely feature adop- tion and is also is generic enough to be applied to a range of clinical adoption contexts and clinical informa- tion systems from personal health records to hospital systems. CAMM is explicitly focused on the measurable outcomes that are linked to integration of IT into clin- ical practice over time, unlike the FITT  or Design- Reality Gap model . Thus, the CAMM fills a gap in healthcare adoption models. The CAMM meets the Lahrmann criteria for an adoption model [13,48]: first, the CAMM has multiple dimensions (they describe clin- ical adoption over time); second, the CAMM allows for variability in assessment (methods are not specified); third, the CAMM is developed for specific audiences. Several audiences were considered as the CAMM was developed: implementers, evaluators, learners, and re- searchers. How the CAMM can support each of these audiences is described below.
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The body of knowledge on the options pricing techniques and application to cases in real life settings in the real estate sector is still growing. Earlier research has focused largely on definitions and developing models for pricing of embedded options without the empirical evidence to support the application of the theory in practice. As a result, literature on the value of staging real estate projects is quite limited. Rocha et al. (2007) determined the optimal staging strategy whether sequential or simultaneous for the development of a residential housing project in Rio de Janeiro. They concluded that the sequential strategy option resulted in an upsurge of the value of the project by 10% while limiting the exposure to risk in excess of 50% as compared to standard evaluation methodology (DCF). Guma et al. (2009) using four case studies in the US demonstrated the potential value of vertically phasing a corporate real estate building. The study found that, vertical phasing is valuable because it is capable of limiting downside risks of corporate organisations when there is need for future expansion to meet the needs of an expanding organisation. The study sought to create the attraction needed to drive flexible expansion real options in practice but did not evaluate to determine the single numerical information needed by an analyst to make a decision. Quite recently, Geltner and de Neufville (2012) demonstrated the value of horizontal phasing of an urban real estate development project using the certainty equivalence approach of the binomial option pricing method combined with Monte Carlo simulation analysis.
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A main strength of our study is that we based our model on existing and validated models. In particular, the underlying Technology Acceptance Model (TAM), commonly used outside  and within healthcare . As Holden and Karsh state TAM “predicts a substantial portion of the use or acceptance of health IT”  how- ever they also mention that the theory might benefit from additions and modifications . Or, as concluded by Legris et al., it is has to be integrated into a broader model  as we did in this study. Another major strength is the large number of respondents to our ques- tionnaire. This created a large sample size for our valid- ation with structural equation modelling using the partial least squares method. By including healthcare professionals from seven out of eight different university hospitals we gathered data independent of the centre-specific context, such as the used documentation processes or EHRs.
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The definition of cloud computing provided by National institute of standard and technology (NIST) has gained significant traction within the IT industry. According to this definition: ―Cloud computing is a model for enabling ubiquitous convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics, three service models, and four deployment models‖. Cloud computing has facilitated various ways which were unknown or not explored in the optimal directions in the world of Information Technology (IT). As cloud computing is found to have an impact on Knowledge management, it is one such field that has not been utilized in its full capacity. In order to recognize, develop, store, embody or distribute knowledge, the tools that exist and methodologies have been unable to help enterprises achieve desired growth. Cloud technologies are employed to support knowledge sharing due to increased developments in internet technologies and its prevalent popularity. Cloud computing, being combination of various existing technologies is not just a single technology. Fundamentals of cloud computing may bear a resemblance to previous computing eras, but developments in storage, connectivity, virtualization and power of processing are merging to develop a technological ecosystem for cloud computing. The results of this combination are a different phenomenon. After cloud computing was adopted, utilization of IT services has advanced to a new level. But costs like required infrastructure and maintenance of the said infrastructure for the long run has led to enterprises not migrating to cloud. This paper hence studies the factors dissuading migration into cloud. Usage of Cloud based technologies at a huge scale in any enterprise is the elemental advantage of adoption and implementation of Cloud computing. Since a lot of significance has been gained by
Recent studies in hospital context include importance of HRM in hospitals from a global context (Kabene et al., 2006), HRM in hospital (Sekhar, 2008), prototyping hospital HRIS (Kadhim et al., 2012), literature review on HRIS implementation processes in order to draw a baseline regarding their scope and capability around the world (Riley et al., 2012), importance of best HRM practices and need for HRIS in public health sector in Sri Lanka (Mujeeb, 2013), and transition of HRIS and its strengthening process used to implement an HRIS in Uganda health care sector (Spero et al., 2011). Sekhar (2008) suggested as HRIS makes the job of HRM much easier, organizations should adopt HRIS. Mujeeb (2013) argued in ensuring quality healthcare service effective use of HRIS is needed. Plus, the author mentioned the system should be sustainable and affordable by organizations. Other studies also suggest research in health care sector is needed to ensure successful adoption of HRIS in order to deliver quality health services to individuals (Kabene et al., 2006; Mujeeb, 2013; Spero et al., 2011).
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There are few studies involving the implementation of ABC in Thailand. Chimploy (1999), who studied ABC for the operating budget of Electricity Generating Authority of Thailand, found that top executives had important roles in the adoption of ABC in Thai firms since they had power to bring about the implementation of ABC and to convince employees to adopt it. Morakul and Wu (2001), who studied cultural influences on the implementation of ABC in Thailand, also found that many modifications were required, when the organisations tried to implement the ABC system in the Thai environment. They report that owing to a high-power distance in the Thai society, of which members accept the unequal distribution of power in their organisations, implementing ABC successfully in the Thai environment must not empower and redistribute the power to employees in the production department to have access to and control over information otherwise both cause a higher resistance level from the accounting department.
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Models have been written using several types of computer packages or programming tools. The most common option is to use a third generation programming language such as Pascal, Fortran, C, C++, Basic, Delphi, Visual C or Visual Basic. These languages are very versatile and can be used for almost any software development project. They allow a customised user interface and provide database capabilities. Despite the huge advances in computer technology over the past decade, speed, memory and system requirements are still an important issue in the development of complex mechanistic models. Because most computer languages produce compiled programs, models run faster and with less memory and fewer system requirements in this format. Models such as STOCKPOL ® (Marshal! et al. , 1 99 1), UDDER (Larcombe, 1989) and GRAZE (Loewer et al., 1987) were built using general purpose languages.
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explore an e-health resource adoption and use among phy- sicians. SEM was used to predict the strength of the rela- tionship within the model and although they established a relationship with the constructs with an explained variance of 44% this compared to 76% which was established when using the model in a previous study outside healthcare. However, they justified that the UTAUT should be integrated with other theories to enrich it when adopting it to the health- care context.
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As such, the joint adoption of the five complementary business models provides the e-commerce megalith with access to critical resources, that serve to augment its value creation activities and capabilities (see “About the Research”), and to fuel network effects for the explosive growth of its core e- retail platform. But what about the nature of the relationships with the remaining business models? The Consumer Electronics Manufacturing business model has specifically been deployed as an attempt to support the Amazon eco-system. Simply put, this backwards integration manoeuver aimed at offering to its core e-retail customers cheap technological products (i.e., Kindle reader, Kindle Fire, Fire TV, Fire Phone, Dash Button), bundled and sold with access to other business model attributes (i.e., Fire Phone: Firefly button). As such, the deployment of this “razor-and-blade” business model epitomizes Amazon’s direct pursuit of portfolio complementarities, in order to drive sales and growth of its core activities. And yet, amongst its seven business models, it is in fact the one that enjoys the least synergies with the others. In fact, it entails a focus drift from its core activities in favor of unrelated extra-industry activities, thus resulting in financial and strategic losses – as illustrated by the very disappointing Fire Phone launch and its subsequent rapid market withdrawal.
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It was decided to conduct explor tory studies first, collecting data from both primary and secondary sources inc ding in-depth interviews with menu planning decision makers and beef suppliers s well as focus groups with consumers in order to identify purchasing patterns and eas of need for new beef products. The results would then provide background mation for the first stages, idea generation and screening, in the supplier' s new bee product development process. Meat companies would be selected to participate in e study to provide both technical expertise and production facilities for the deve opment of new beef products. The product development process would be coo dinated with the investigation of the new beef product adoption process. The prod ct concepts for evaluation by the menu planning decision makers would be develo with the assistance of these companies. New beef products to represent the rang of acceptable products from the three new beef product categories would then be d veloped from the preferred concepts. These new products would be subjected to consumer trials, utilising a simulated dining experience, before prototype trials y the menu planning decision makers.
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The project focuses on achieving change for the woman; in order to benefit from the services, workers suggested that women needed to have some or all of the motivations listed above. In addition, workers explained that the mothers needed to be ‘ready’, be committed to working with the service, and have some degree of stability in their life. Some workers noted that they had received referrals for women who they felt were not yet able to benefit. They indicated that this was generally due to particularly pressing issues in their lives, for example, processes to remove their child were ongoing, or issues such as mental ill health, substance use, or domestic violence were currently at a crisis point. In some cases, Scottish Adoption had a prior relationship with the women involved in the Chance4Change service. This had advantages; it both enabled workers to
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The increasing adoption and use of modern ICTs have continued to affect the traditional understanding and ways of carrying out our job task in work places. These therefore calls for constant review of existing models aimed at explaining these interactions. A review of the existing models on IS usage and performance, shows some identified deficiencies. For example, studies that focus on intention-usage based models or framework have been identified as models that focus on intention to use IT attitude rather than actually assisting researchers fully understand usage and its outcomes.
with an inverse relationship: the less innovative and technically capable the firm is, the more likely it is to adopt IaaS. The model recorded an R2 of 0.219 for this subgroup, about 15% better than the full model. IT capabilities and expertise in cloud computing are more important drivers in cloud infrastructure adoption than for software application adoption. In many sectors, firms with IT knowledge and capabilities are better able to recognize and take advantage of new technology innovations. Zhu found technology competence as a significant driver of e-business adoption in a study on innovation diffusion in global contexts (Zhu et al., 2006). Additionally, IT infrastructure capability, the organization’s capacity to manage and deploy shareable IT platforms, has been identified as an antecedent of organizational agility (Lu & Ramamurthy, 2011). However, the results of this research suggest that manufacturing firms pursue
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This research was interested in tackling Internet related technologies as one approach in detecting EC capabilities within New Zealand SMEs. Particularly, in explaining the following issues pertaining to the technologies: (i) what e-commerce technologies are being adopted and (ii) where those technologies are being used by New Zealand SMEs. Issues arising from (i) and (ii) would highlight various accelerators and/or impediments to the adoption and diffusion of EC. The remaining of the paper is arranged in the following sequence: relevant literature about electronic commerce and SMEs in New Zealand, development of an adoption framework, and finally discussion and conclusion.
This dissertation aims to make two primary contributions. The first and most important contribution is the introduction of the concept of IT encountering as an alternative and relevant approach to study what happens before IT enters an organization. This early moment of IT innovation has been understood primarily from an adoption perspective, which assumes the saliency of a focal technology to a decision maker, and seeks to shed light on the factors that facilitate or hinder behavioural intention to acquire or start using IT, and secondarily from an IT selection and evaluation perspective, which assumes that suitable IT alternatives are known to the individual making choices. These perspectives, however, do not fully illuminate the IT encountering process. That is, they do not allow us to comprehensively explain how decision makers, often limited in their knowledge of the IT marketplace and faced with competing demands on their time and financial resources, attend to cues suggesting IT, interpret these cues and respond to them. The IT encountering perspective developed through this research can contribute to theory by shedding light on these issues.
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