888 resultados para Drivers of Adoption


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To understand the diffusion of high technology products such as PCs, digital cameras and DVD players it is necessary to consider the dynamics of successive generations of technology. From the consumer’s perspective, these technology changes may manifest themselves as either a new generation product substituting for the old (for instance digital cameras) or as multiple generations of a single product (for example PCs). To date, research has been confined to aggregate level sales models. These models consider the demand relationship between one generation of a product and a successor generation. However, they do not give insights into the disaggregate-level decisions by individual households – whether to adopt the newer generation, and if so, when. This paper makes two contributions. It is the first large scale empirical study to collect household data for successive generations of technologies in an effort to understand the drivers of adoption. Second, in contrast to traditional analysis in diffusion research that conceptualizes technology substitution as an “adoption of innovation” type process, we propose that from a consumer’s perspective, technology substitution combines elements of both adoption (adopting the new generation technology) and replacement (replacing generation I product with generation II). Key Propositions In some cases, successive generations are clear “substitutes” for the earlier generation (e.g. PCs Pentium I to II to III ). More commonly the new generation II technology is a “partial substitute” for existing generation I technology (e.g. DVD players and VCRs). Some consumers will purchase generation II products as substitutes for their generation I product, while other consumers will purchase generation II products as additional products to be used as well as their generation I product. We propose that substitute generation II purchases combine elements of both adoption and replacement, but additional generation II purchases are solely adoption-driven process. Moreover, drawing on adoption theory consumer innovativeness is the most important consumer characteristic for adoption timing of new products. Hence, we hypothesize consumer innovativeness to influence the timing of both additional and substitute generation II purchases but to have a stronger impact on additional generation II purchases. We further propose that substitute generation II purchases act partially as a replacement purchase for the generation I product. Thus, we hypothesize that households with older generation I products will make substitute generation II purchases earlier. Methods We employ Cox hazard modeling to study factors influencing the timing of a household’s adoption of generation II products. A separate hazard model is conducted for additional and substitute purchases. The age of the generation I product is calculated based on the most recent household purchase of that product. Control variables include size and income of household, age and education of decision-maker. Results and Implications Our preliminary results confirm both our hypotheses. Consumer innovativeness has a strong influence on both additional purchases and substitute purchases. Also consistent with our hypotheses, the age of the generation I product has a dramatic influence for substitute purchases of VCR/DVD players and a strong influence for PCs/notebooks. Yet, also as hypothesized, there was no influence on additional purchases. This implies that there is a clear distinction between additional and substitute purchases of generation II products, each with different drivers. For substitute purchases, product age is a key driver. Therefore marketers of high technology products can utilize data on generation I product age (e.g. from warranty or loyalty programs) to target customers who are more likely to make a purchase.

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Principal Topic High technology consumer products such as notebooks, digital cameras and DVD players are not introduced into a vacuum. Consumer experience with related earlier generation technologies, such as PCs, film cameras and VCRs, and the installed base of these products strongly impacts the market diffusion of the new generation products. Yet technology substitution has received only sparse attention in the diffusion of innovation literature. Research for consumer durables has been dominated by studies of (first purchase) adoption (c.f. Bass 1969) which do not explicitly consider the presence of an existing product/technology. More recently, considerable attention has also been given to replacement purchases (c.f. Kamakura and Balasubramanian 1987). Only a handful of papers explicitly deal with the diffusion of technology/product substitutes (e.g. Norton and Bass, 1987: Bass and Bass, 2004). They propose diffusion-type aggregate-level sales models that are used to forecast the overall sales for successive generations. Lacking household data, these aggregate models are unable to give insights into the decisions by individual households - whether to adopt generation II, and if so, when and why. This paper makes two contributions. It is the first large-scale empirical study that collects household data for successive generations of technologies in an effort to understand the drivers of adoption. Second, in comparision to traditional analysis that evaluates technology substitution as an ''adoption of innovation'' type process, we propose that from a consumer's perspective, technology substitution combines elements of both adoption (adopting the new generation technology) and replacement (replacing the generation I product with generation II). Based on this proposition, we develop and test a number of hypotheses. Methodology/Key Propositions In some cases, successive generations are clear ''substitutes'' for the earlier generation, in that they have almost identical functionality. For example, successive generations of PCs Pentium I to II to III or flat screen TV substituting for colour TV. More commonly, however, the new technology (generation II) is a ''partial substitute'' for existing technology (generation I). For example, digital cameras substitute for film-based cameras in the sense that they perform the same core function of taking photographs. They have some additional attributes of easier copying and sharing of images. However, the attribute of image quality is inferior. In cases of partial substitution, some consumers will purchase generation II products as substitutes for their generation I product, while other consumers will purchase generation II products as additional products to be used as well as their generation I product. We propose that substitute generation II purchases combine elements of both adoption and replacement, but additional generation II purchases are solely adoption-driven process. Extensive research on innovation adoption has consistently shown consumer innovativeness is the most important consumer characteristic that drives adoption timing (Goldsmith et al. 1995; Gielens and Steenkamp 2007). Hence, we expect consumer innovativeness also to influence both additional and substitute generation II purchases. Hypothesis 1a) More innovative households will make additional generation II purchases earlier. 1 b) More innovative households will make substitute generation II purchases earlier. 1 c) Consumer innovativeness will have a stronger impact on additional generation II purchases than on substitute generation II purchases. As outlined above, substitute generation II purchases act, in part like a replacement purchase for the generation I product. Prior research (Bayus 1991; Grewal et al 2004) identified product age as the most dominant factor influencing replacements. Hence, we hypothesise that: Hypothesis 2: Households with older generation I products will make substitute generation II purchases earlier. Our survey of 8,077 households investigates their adoption of two new generation products: notebooks as a technology change to PCs, and DVD players as a technology shift from VCRs. We employ Cox hazard modelling to study factors influencing the timing of a household's adoption of generation II products. We determine whether this is an additional or substitute purchase by asking whether the generation I product is still used. A separate hazard model is conducted for additional and substitute purchases. Consumer Innovativeness is measured as domain innovativeness adapted from the scales of Goldsmith and Hofacker (1991) and Flynn et al. (1996). The age of the generation I product is calculated based on the most recent household purchase of that product. Control variables include age, size and income of household, and age and education of primary decision-maker. Results and Implications Our preliminary results confirm both our hypotheses. Consumer innovativeness has a strong influence on both additional purchases (exp = 1.11) and substitute purchases (exp = 1.09). Exp is interpreted as the increased probability of purchase for an increase of 1.0 on a 7-point innovativeness scale. Also consistent with our hypotheses, the age of the generation I product has a dramatic influence for substitute purchases of VCR/DVD (exp = 2.92) and a strong influence for PCs/notebooks (exp = 1.30). Exp is interpreted as the increased probability of purchase for an increase of 10 years in the age of the generation I product. Yet, also as hypothesised, there was no influence on additional purchases. The results lead to two key implications. First, there is a clear distinction between additional and substitute purchases of generation II products, each with different drivers. Treating these as a single process will mask the true drivers of adoption. For substitute purchases, product age is a key driver. Hence, implications for marketers of high technology products can utilise data on generation I product age (e.g. from warranty or loyalty programs) to target customers who are more likely to make a purchase.

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This study empirically examines the motivators that influence a consumer’s intentions to use mobile banking. A web-based survey was employed to collect data from 348 respondents, split across Thailand and Australia. Data were analysed by employing exploratory and confirmatory factor analyses, path and invariance analyses. The findings indicate that for Australian consumers, perceived ease of use, perceived usefulness and perceived risk were the primary determinants of mobile banking adoption. For Thai consumers, the main factors were perceived usefulness, perceived risk and social influence. National culture was found to impact key antecedents that lead to adoption of m-banking. Interestingly, the actual variance explained by this study’s model was higher in Australia than for Thailand, suggesting future research of m-banking adoption in emerging Asian cultures. The findings of this research give banking organisations a foundational model that can be used to support m-banking implementation. This study is perhaps the first to examine and compare the intention to adopt m-banking across Thai and Australian consumers, and responds to calls for additional research that generalises m-banking and m-services acceptance across cultures. This study has proposed and validated additional constructs that are not present in the original SST Intention to Use model.

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The automotive industry is confronted with increasing competition, leading to higher cost pressures and the demand to optimize production processes and value chains. Here the RFID technology promises to improve a range of processes in logistics and manufacturing. Despite its promising potential in the automotive industry, RFID has not yet made a decisive step from pilots to real-life implementations in the supply chain. Building on existing models of technology adoption, we analyze RFID adoption dynamics in the automotive industry. Building on existing IOS adoption models tailored to RFID specifics and based on ten semi-structured interviews with OEMs and suppliers, we evaluate main drivers of RFID adoption in the automotive industry. Our key findings are that the use of a coercive approach by the OEM could be redundant because of the market-driven RFID adoption among many suppliers. Furthermore, suppliers implementing RFID can now gain an early mover competitive advantage by developing higher trust in their relationship with the OEM as well as accumulating unique expertise in this area.

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Arthropods that have a direct impact on crop production (i.e. pests, natural enemies and pollinators) can be influenced by both local farm management and the context within which the fields occur in the wider landscape. However, the contributions and spatial scales at which these drivers operate and interact are not fully understood, particularly in the developing world. The impact of both local management and landscape context on insect pollinators and natural enemy communities and on their capacity to deliver related ecosystem services to an economically important tropical crop, pigeonpea was investigated. The study was conducted in nine paired farms across a gradient of increasing distance to semi-native vegetation in Kibwezi, Kenya. Results show that proximity of fields to semi-native habitats negatively affected pollinator and chewing insect abundance. Within fields, pesticide use was a key negative predictor of pollinator, pest and foliar active predator abundance. On the contrary, fertilizer application significantly enhanced pollinator and both chewing and sucking insect pest abundance. At a 1 km spatial scale of fields, there were significant negative effects of the number of semi-native habitat patches within fields dominated by mass flowering pigeonpea on pollinators abundance. For service provision, a significant decline in fruit set when insects were excluded from flowers was recorded. This study reveals the interconnections of pollinators, predators and pests with pigeonpea crop. For sustainable yields and to conserve high densities of both pollinators and predators of pests within pigeonpea landscapes, it is crucial to target the adoption of less disruptive farm management practices such as reducing pesticide and fertilizer inputs.

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In this theoretical paper, motives for CSR are considered. An underlying assumption is that the commercial imperative is not the sole driver of CSR decision-making in private sector companies, but that the formal adoption and implementation of CSR by corporations could be associated with the changing personal values of individual managers. These values may find expression through the opportunity to exercise discretion, which may arise in various ways. It is suggested that in so far as CSR initiatives represent individuals' values, so the “responsibility” in evidence is less obviously “corporate.” Our emphasis on personal initiative is intended to counter a tendency to view the corporation as the agent, and may serve to remind us that individuals can, indeed, make a difference.

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The rate of water reform in Australia is gathering pace with Federal and State initiatives promoting a more integrated approach to water management. This approach encompasses a more competitive environment and a greater role for the private sector. There is a growing recognition of the importance of water recycling in these initiatives and the need to provide opportunities for its development. In March 2008 the Productivity Commission published its discussion paper on urban water reform (Productivity Commission, 2008). The paper cited inadequate institutional arrangements for the management of Australian urban water resources and noted the benefits to be gained from a comprehensive public review of urban water management. This development can be supported through the promotion of a sewer mining industry. This industry, offers flexible and innovative solutions to water recycling demands in a variety of situations and structures. In addition it has the capability of satisfying government competition and private sector policy initiatives.

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Building Information Modelling (BIM) is an IT enabled technology that allows storage, management, sharing, access, update and use of all the data relevant to a project through out the project life-cycle in the form of a data repository. BIM enables improved inter-disciplinary collaboration across distributed teams, intelligent documentation and information retrieval, greater consistency in building data, better conflict detection and enhanced facilities management. While the technology itself may not be new, and similar approaches have been in use in some other sectors like Aircraft and Automobile industry for well over a decade now, the AEC/FM (Architecture, Engineering and Construction/ Facilities Management) industry is still to catch up with them in its ability to exploit the benefits of the IT revolution. Though the potential benefits of the technology in terms of knowledge sharing, project management, project co-ordination and collaboration are near to obvious, the adoption rate has been rather lethargic, inspite of some well directed efforts and availability of supporting commercial tools. Since the technology itself has been well tested over the years in some other domains the plausible causes must be rooted well beyond the explanation of the ‘Bell Curve of innovation adoption’. This paper discusses the preliminary findings of an ongoing research project funded by the Cooperative Research Centre for Construction Innovation (CRC-CI) which aims to identify these gaps and come up with specifications and guidelines to enable greater adoption of the BIM approach in practice. A detailed literature review is conducted that looks at some of the similar research reported in the recent years. A desktop audit of some of the existing commercial tools that support BIM application has been conducted to identify the technological issues and concerns, and a workshop was organized with industry partners and various players in the AEC industry for needs analysis, expectations and feedback on the possible deterrents and inhibitions surrounding the BIM adoption.