911 resultados para drivers of SR technology adoption


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 Social Recruiting technologies such as LinkedIn and Twitter have been fast emerging as one of the modern recruitment methods. However, research on their effective usage is scarce and outpaced by organisational practice. The current study addresses this gap by investigating the drivers of SR technology adoption on one hand, and their pre-hire outcomes on the other.

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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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This thesis presents a design investigation into how traditional technology-orientated markets can use design led innovation (DLI) strategies in order to achieve better market penetration of disruptive products. In a review of the Australian livestock industry, considering historical information and present-day trends, a lack of socio-cultural consideration was identified in the design and implementation of products and systems, previously been taken to market. Hence the adoption of these novel products has been documented as extremely slow. Classical diffusion models have typically been used in order to implement these products. However, this thesis poses that it is through the strategic intent of design led innovation, where heavily technology-orientated markets (such as the Australian livestock industry), can achieve better final adoption rates. By considering a range of external factors (business models, technology and user needs), rather than focusing design efforts solely on the technology, it is argued that using DLI approach will lead to disruptive innovations being made easier to adopt in the Australian livestock industry. This thesis therefore explored two research questions: 1. What are the social inhibitors to the adoption of a new technology in the Australian livestock industry? 2. Can design be used to gain a significant feedback response to the proposed innovation? In order to answer these questions, this thesis used a design led innovation approach to investigate the livestock industry, centring on how design can be used early on in the development of disruptive products being taken to market. This thesis used a three stage data collection programme, combining methods of design thinking, co-design and participatory design. The first study found four key themes to the social barriers of technology adoption; Social attitudes to innovation, Market monitoring, Attitude to 3D imaging and Online processes. These themes were built upon through a design thinking/co-design approach to create three ‘future scenarios’ to be tested in participant workshops. The analysis of the data collection found four key socio-cultural barriers that inhibited the adoption of a disruptive innovation in the Australian livestock industry. These were found to be a lack of Education, a Culture of Innovation, a Lack of Engagement and Communication barriers. This thesis recommends five key areas to be focused upon in the subsequent design of a new product in the Australian livestock industry. These recommendations are made to business and design managers looking to introduce disruptive innovations in this industry. Moreover, the thesis presents three design implications relating to stakeholder attitudes, practical constraints and technological restrictions of innovations within the industry.

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We develop a stochastic endogenous growth model to explain the diversity in growth and inequality patterns and the non-convergence of incomes in transitional economies where an underdeveloped financial sector imposes an implicit, fixed cost on the diversification of idiosyncratic risk. In the model endogenous growth occurs through physical and human capital deepening, with the latter being the more dominant element. We interpret the fixed cost as a ‘learning by doing’ cost for entrepreneurs who undertake risk in the absence of well developed financial markets and institutions that help diversify such risk. As such, this cost may be interpreted as the implicit returns foregone due to the lack of diversification opportunities that would otherwise have been available, had such institutions been present. The analytical and numerical results of the model suggest three growth outcomes depending on the productivity differences between the projects and the fixed cost associated with the more productive project. We label these outcomes as poverty trap, dual economy and balanced growth. Further analysis of these three outcomes highlights the existence of a diversity within diversity. Specifically, within the ‘poverty trap’ and ‘dual economy’ scenarios growth and inequality patterns differ, depending on the initial conditions. This additional diversity allows the model to capture a richer range of outcomes that are consistent with the empirical experience of several transitional economies.

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The purpose of this paper is to explore the use of automated inventory management systems (IMS) and identify the stage of technology adoption for restaurants in Aruba. A case study analysis involving twelve members of the Aruba Gastronomic Association was conducted using a qualitative research design to gather information on approaches currently used as well as the reasons and perceptions managers/owners have for using or not using automated systems in their facilities. This is the first study conducted using the Aruba restaurant market. Therefore, the application of two technology adoption models was used to integrate critical factors relevant to the study. Major findings indicated the use of an automated IMS in restaurants is limited, thus underscoring the lack of adoption of technology in this area. The results also indicated that two major reasons that restaurants are not adopting IMS technology are budgetary constraints and service support. This study is imperative for two reasons: (1) the results of this study can be used as a comparison for future IMS adoption, not only for Aruba’s restaurant industry but also for other Caribbean destinations and the U.S., (2) this study also provides insight into the additional training and support help needed in hospitality technology services.

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We analyse the incentives and welfare implications of costly technology adoption in a two-period duopoly model where firms have different amounts of capital. We also extend our framework to an open economy set-up and examine the relationship between trade and technology adoption. Our findings are as follows. First, no monotone relationship exists between the threshold cost of adoption and capital shares. Second, an unequal distribution of capital, despite lessening competition, can increase total surplus. Third, trade generally encourages adoption of modern technology unless the share of capital for the adopters is too low.

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IS/IT investments are seen has having an enormous potential impact on the competitive position of the firm, on its performance, and demand an active and motivated participation of several stakeholder groups. The shortfall of evidence concerning the productivity of IT became known as the ‘productivity paradox’. As Robert Solow, the Nobel laureate economist stated “we see computers everywhere except in the productivity statistics”. An important stream of research conducted all over the world has tried to understand these phenomena, called in the literature as «IS business value» field. However, there is a gap in the literature, addressing the Portuguese situation. No empirical work has been done to date in order to understand the impact of Information Technology adoption on the productivity of those firms. Using data from two surveys conducted by the Portuguese National Institute of Statistics (INE), Inquiry to the use of IT by Portuguese companies (IUTIC) and the Inquiry Harmonized to (Portuguese) companies (accounting data), this study relates (using regression analysis) the amounts spent on IT with the financial performance indicator Returns on Equity, as a proxy of firm productivity, of Portuguese companies with more than 250 employees. The aim of this paper is to shed light on the Portuguese situation concerning the impact of IS/IT on the productivity of Portuguese top companies. Empirically, we test the impact of IT expenditure on firm productivity of a sample of Portuguese large companies. Our results, based on firm-level data on Information Technology expenditure and firm productivity as measured by return on equity (1186 observations) for the years of 2003 and 2004, exhibit a negative impact of IT expenditure on firm productivity, in line with “productivity paradox” claimants.

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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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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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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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This paper examines the interactions between knowledge and power in the adoption of technologies central to municipal water supply plans, specifically investigating decisions in Progressive Era Chicago regarding water meters. The invention and introduction into use of the reliable water meter early in the Progressive Era allowed planners and engineers to gauge water use, and enabled communities willing to invest in the new infrastructure to allocate costs for provision of supply to consumers relative to use. In an era where efficiency was so prized and the role of technocratic expertise was increasing, Chicago’s continued failure to adopt metering (despite levels of per capita consumption nearly twice that of comparable cities and acknowledged levels of waste nearing half of system production) may indicate that the underlying characteristics of the city’s political system and its elite stymied the implementation of metering technologies as in Smith’s (1977) comparative study of nineteenth century armories. Perhaps, as with Flyvbjerg’s (1998) study of the city of Aalborg, the powerful know what they want and data will not interfere with their conclusions: if the data point to a solution other than what is desired, then it must be that the data are wrong. Alternatively, perhaps the technocrats failed adequately to communicate their findings in a language which the political elite could understand, with the failure lying in assumptions of scientific or technical literacy rather than with dissatisfaction in outcomes (Benveniste 1972). When examined through a historical institutionalist perspective, the case study of metering adoption lends itself to exploration of larger issues of knowledge and power in the planning process: what governs decisions regarding knowledge acquisition, how knowledge and power interact, whether the potential to improve knowledge leads to changes in action, and, whether the decision to overlook available knowledge has an impact on future decisions.

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Construction firms are increasingly utilizing information technologies to better manage geographically dispersed projects. Often these technologies involve changes to existing working practices and processes and are viewed as disruptive by members of the organization. Understanding the factors that can influence individuals’ intention to utilize technology can assist managers to implement strategies to increase and improve the uptake of technologies and improve the innovation adoption process. Using a case study organization, factors identified in the Unified Theory of Acceptance and Use of Technology (UTAUT) are examined and the UTAUT is extended and by including resistance to change and top management support. The findings indicate effort expectancy, internal facilitating conditions and top management support all influence individuals’ intention to use information technology. The results also show that resistance to change or fear of change does not always play a role in innovation adoption. The findings reinforce the need to support new technologies from both a managerial and technical perspective.

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When the acronym of ëBRICí was coined in 2001 by Jim OíNeill of Goldman Sachs, it was expected that economic growth rates in India, Brazil and Russia would eventually catch up with that of China. However, China has continued to outperform the other economies in the group, even after it was renamed ëBRICSí to reflect the inclusion of South Africa in 2010. The focus of this chapter is on one of the BRICS economies, namely India. Its aim is to examine from an economic perspective, why Indiaís performance has not lived up to expectations, and comment on the key challenges it faces in meeting them. We begin with some descriptive statistics regarding the progress of the Indian economy since 1990. While it has been growing at a rapid rate since the reforms it introduced in the1990s, there has been a slowdown in its overall GDP growth rates since 2008. The rate of growth experienced in the period 2003ñ07 was an average of 10.5 per cent. However, since the recession following the Global Financial Crisis (GFC) of 2008, the growth rate has fallen. From the period 2008ñ12 it has only registered an average growth rate of 6.5 per cent (World Bank, 2013). This chapter suggests that one of the major factors underpinning this slowdown is the performance of Indiaís agricultural sector. The importance of the agricultural sector is highlighted by the following stylized facts.