127 resultados para Conditional sales
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This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.
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Product reviews are the foremost source of information for customers and manufacturers to help them make appropriate purchasing and production decisions. Natural language data is typically very sparse; the most common words are those that do not carry a lot of semantic content, and occurrences of any particular content-bearing word are rare, while co-occurrences of these words are rarer. Mining product aspects, along with corresponding opinions, is essential for Aspect-Based Opinion Mining (ABOM) as a result of the e-commerce revolution. Therefore, the need for automatic mining of reviews has reached a peak. In this work, we deal with ABOM as sequence labelling problem and propose a supervised extraction method to identify product aspects and corresponding opinions. We use Conditional Random Fields (CRFs) to solve the extraction problem and propose a feature function to enhance accuracy. The proposed method is evaluated using two different datasets. We also evaluate the effectiveness of feature function and the optimisation through multiple experiments.
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This study investigates friendships between gay sales associates and heterosexual female customers in luxury retail settings. By employing grounded theory methodology, the study integrates theories and findings from diverse literature streams into an original conceptual framework to illustrate the resources gay sales associates and straight female customers receive from and provide to each other during retail exchanges. The study explains why gay male–straight female friendships are uniquely suited for luxury consumption settings. Female customers characterize their friendships with gay sales associates as providing honesty, security, trust, and comfort, which stems from the absence of sexual interest and a lack of inter-female competition. Gay sales associates receive acceptance for who they are and for their displays of unconventional masculinity in retail settings. They also obtain a temporary rite from their female customers, a so-called mandate of privacy, which permits both parties to ignore the bounds of modesty and accept a degree of intimacy. Such intimacy facilitates transactions that require both personalization and customer–employee closeness, such as the selling of high-end apparel, accessories, and jewelry.
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Deep convolutional neural networks (DCNNs) have been employed in many computer vision tasks with great success due to their robustness in feature learning. One of the advantages of DCNNs is their representation robustness to object locations, which is useful for object recognition tasks. However, this also discards spatial information, which is useful when dealing with topological information of the image (e.g. scene labeling, face recognition). In this paper, we propose a deeper and wider network architecture to tackle the scene labeling task. The depth is achieved by incorporating predictions from multiple early layers of the DCNN. The width is achieved by combining multiple outputs of the network. We then further refine the parsing task by adopting graphical models (GMs) as a post-processing step to incorporate spatial and contextual information into the network. The new strategy for a deeper, wider convolutional network coupled with graphical models has shown promising results on the PASCAL-Context dataset.
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Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.
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Purpose – This paper compares the experiential consumption values that motivate consumer choice to purchase online for both male and female purchasers and non-purchasers. Design/methodology/approach – Using the theory of consumption value the study examines gendered perceptions of the functional, social and conditional value of using a virtual consumption setting for purchasing. Data was collected through an online survey and analysed using multiple discriminant analysis to determine meaningful differences between male and female purchasers and non-purchasers. Findings – The findings show that male online purchasers are discriminated from female purchasers by social value and from male non-purchasers by conditional value. Female purchasers are discriminated from male purchasers by functional value and from female non-purchasers by social value. Female non-purchasers are discriminated from female purchasers by conditional value. Male non-purchasers are discriminated from male purchasers by functional and social value. Research limitations/implications – Limitations include using an Internet survey and an Australian sample which may impact the generalisability of the findings to a wider population of Internet users. Future research should involve replication of the study in a country more or less developed in terms of gender composition of internet users to extend the generalisability of the findings. Additionally, researchers should examine whether other dimensions of consumption value,such as social influence through on- and off-line communication networks, may influence consumer choice to purchase online. Practical implications – The study provides practical implications for marketers to leverage consumption values that influence male and female consumers’ choice to purchase online and then drive their behaviour online through integrated marketing campaigns that involve both on- and offline strategies. Originality/value – The research makes an original contribution to the consumer behaviour literature as to date, no research has been found that undertakes such a comprehensive gender-based comparison of the perceived value of using a virtual consumption setting for purchasing.
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Principal topic: Effectuation theory suggests that entrepreneurs develop their new ventures in an iterative way by selecting possibilities through flexibility and interactions with the market; a focus on affordability of loss rather than maximal return on the capital invested, and the development of pre-commitments and alliances from stakeholders (Sarasvathy, 2001, 2008; Sarasvathy et al., 2005, 2006). In contrast, causation may be described as a rationalistic reasoning method to create a company. After a comprehensive market analysis to discover opportunities, the entrepreneur will select the alternative with the higher expected return and implement it through the use of a business plan. However, little is known about the consequences of following either of these two processes. One aspect that remains unclear is the relationship between newness and effectuation. On one hand it can be argued that the combination of a means-centered, interactive (through pre-commitments and alliances with stakeholders from the early phases of the venture creation) and open-minded process (through flexibility of exploiting contingencies) should encourage and facilitate the development of innovative solutions. On the other hand, having a close relationship with their “future first customers” and focussing too much on the resources and knowledge already within the firm may be a constraint that is not conducive to innovation, or at least not to a radical innovation. While it has been suggested that effectuation strategy is more likely to be used by innovative entrepreneurs (Sarasvathy, 2001), this hypothesis has not been demonstrated yet (Sarasvathy, 2001). Method: In our attempt to capture newness in its different aspects we have considered the following four domains where newness may happen: new product/service; new method for promotion and sales; new production methods/sourcing; market creation. We identified how effectuation may be differently associated with these four domains of newness. To test our four sets of hypotheses a dataset of 1329 firms (702 nascent and 627 young firms) randomly selected in Australia was examined through ANOVA Tukey HSD Test. Results and Implications: Results indicate the existence of a curvilinear relationship between effectuation and newness where low and high levels of newness are associated with low level of effectuation while medium level of newness is associated with high level of effectuation. Implications for academia, practitioners and policy makers are also discussed.
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The paper examines the decision by Australian Real Estate Trusts (A-REITs) to issue seasoned equity offerings from 2000 - 2008 and stock market reaction to the offerings using panel data and event study methodologies, respectively. The global financial crisis has resulted in freezing of the Australian bond markets, with several A-REITs left with seasoned equity issuance and asset sales as the only viable modes of raising additional capital. The findings review that leverage and operating risk are negative significant determinants of seasoned equity offerings; profitability and growth opportunities are positive significant determinants. Of the structure and type of properties held by the A-REIT, only stapled management structure and international operations are significant determinants. Type of properties held by A-REITs show inconsistent results. Similar to previous studies of seasoned equity offerings, we find a significant negative abnormal return associated with their announcement and no evidence of excessive leakage of information. Cross-sectional regressions show that the issued amount raised and leverage are significant factors affecting abnormal returns.
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This study contributes to the growth of design knowledge in China, where vehicle design for the local, older user is in its initial developmental stages. Therefore, this research has explored the travel needs of older Chinese vehicle users in order to assist designers to better understand users’ current and future needs. A triangulation method consisting of interviews, logbook and co-discovery was used to collect multiple forms of data and so explore the research question. Grounded theory has been employed to analyze the research data. This study found that users’ needs are reflected through various ‘meanings’ that they attach to vehicles – meanings that give a tangible expression to their experiences. This study identified six older-user need categories: (i) safety, (ii) utility, (iii) comfort, (iv) identity, (v) emotion and (vi) spirituality. The interrelationships among these six categories are seen as an interactive structure, rather than as a linear or hierarchical arrangement. Chinese cultural values, which are generated from particular local context and users’ social practice, will play a dynamic role in linking and shaping the travel needs of older vehicle users in the future. Moreover, this study structures the older-user needs model into three levels of meaning, to give guidance to vehicle design direction: (i) the practical meaning level, (ii) the social meaning level and (ii) the cultural meaning level. This study suggests that a more comprehensive explanation exists if designers can identify the vehicle’s meaning and property associated with the fulfilled older users’ needs. However, these needs will vary, and must be related to particular technological, social, and cultural contexts. The significance of this study lies in its contributions to the body of knowledge in three areas: research methodology, theory and design. These theoretical contributions provide a series of methodological tools, models and approaches from a vehicle design perspective. These include a conditional/consequential matrix, a travel needs identification model, an older users’ travel-related needs framework, a user information structure model, and an Older-User-Need-Based vehicle design approach. These models suggest a basic framework for the new design process which might assist in the design of new vehicles to fulfil the needs of future, aging Chinese generations. The models have the potential to be transferred to other design domains and different cultural contexts.
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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 investigated the effects of factors like member satisfaction and social rituals on desirable outcomes such as attendance, intention to rejoin and merchandise sales. This study focuses on the inaugural members of a new team in Australia’s A-League to gain insight into how loyalty develops amongst fans of new sporting organisations. The results show the importance to sports marketers of satisfying members and building ritual behaviour, as both are correlated with all of the positive outcomes investigated here.
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Solar Cities Congress 2008 “Energising Sustainable Communities – Options for Our Future” THEME 3: Climate Change. Impact on Society and Culture. Sub Theme: planning and implementing holistic strategies for sustainable transport Abstract Promoting the use of cycling as an environmentally and socially sustainable form of transport. We need to reduce carbon emissions. We need to reduce fuel consumption. We need to reduce pollution. We need to reduce traffic congestion. As obesity levels and associated health problems in the developed nations continue to increase we need to adopt a healthier lifestyle. Few if any would argue with these statements. In fact many would consider these problems to be amongst the most urgent that our society faces. What if we had a vehicle that uses no fossil fuel to power it, creates no pollution, takes up far less space on the roads and promotes an active, healthy lifestyle. What if this machine would have energy efficiency levels 50 times greater than the car? This is a solution that is here, now and ready to go and many of us already own one. It is the humble bicycle. Although bicycle sales in Australia now outnumber car sales, bicycle use as a form of transport (as opposed to recreation) only constitutes around 3% to 4% of all trips. So, why are bicycles the forgotten form of transport if they promise to deliver the benefits that I have just outlined? This paper examines the underlying reasons for the relatively low use of bicycles as a means of transport. It identifies the areas of greatest potential for encouraging the use of the world’s most efficient form of transport. Tim Williams - May 2007
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This paper proposes a novel relative entropy rate (RER) based approach for multiple HMM (MHMM) approximation of a class of discrete-time uncertain processes. Under different uncertainty assumptions, the model design problem is posed either as a min-max optimisation problem or stochastic minimisation problem on the RER between joint laws describing the state and output processes (rather than the more usual RER between output processes). A suitable filter is proposed for which performance results are established which bound conditional mean estimation performance and show that estimation performance improves as the RER is reduced. These filter consistency and convergence bounds are the first results characterising multiple HMM approximation performance and suggest that joint RER concepts provide a useful model selection criteria. The proposed model design process and MHMM filter are demonstrated on an important image processing dim-target detection problem.
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With increasing revenues for video game manufacturers, higher software sales and a more diverse audience, the video games industry has been experiencing strong and rapid growth in recent times, rivalling other forms of entertainment. As a result, games have begun to attract the attention of marketing practitioners who are finding it increasingly difficult to attract consumer attention, and are seeking alternative media for marketing communications. This paper provides a review of the video games industry in the United States and raises the question as to whether games are a viable new medium for marketing messages. Areas for research are identified.