993 resultados para Retail operations


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This report describes the diet-related health of the Australian population and identifies potential opportunities for the food retail sector.

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Reviews and synthesizes nutrition policy actions to improve food retail for NSW Health

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This paper proposes a new multi-stage mine production timetabling (MMPT) model to optimise open-pit mine production operations including drilling, blasting and excavating under real-time mining constraints. The MMPT problem is formulated as a mixed integer programming model and can be optimally solved for small-size MMPT instances by IBM ILOG-CPLEX. Due to NP-hardness, an improved shifting-bottleneck-procedure algorithm based on the extended disjunctive graph is developed to solve large-size MMPT instances in an effective and efficient way. Extensive computational experiments are presented to validate the proposed algorithm that is able to efficiently obtain the near-optimal operational timetable of mining equipment units. The advantages are indicated by sensitivity analysis under various real-life scenarios. The proposed MMPT methodology is promising to be implemented as a tool for mining industry because it is straightforwardly modelled as a standard scheduling model, efficiently solved by the heuristic algorithm, and flexibly expanded by adopting additional industrial constraints.

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This paper discusses the prototypical implementation of an ambient display and the results of an empirical study in a retail store. It presents the context of shopping as an application area for Ambient Intelligence (AmI) technologies. The prototype consists of an ambient store map that enhances the awareness of customer activity. The results of our study indicate potentials and challenges for an improvement of the shopping experience with AmI technologies. Based on our findings we discuss challenges and future developments for applying AmI technologies to shopping environments.

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Abstract is not available.

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Assignment clauses in non-retail commercial leases are as infinitely varied as the circumstances in which disputes arise. Each clause must be individually interpreted as part of the lease in which it is embedded. Whilst the assignment of a lease is one of the most commonplace transactions between lessor and lessee, the case law reveals few unifying principles. This article seeks to cautiously identify a set of principles which should be in the mind of any lawyer when a dispute relating to an assignment arises. It concludes with a short checklist of matters which must be considered by such a person to encourage the application of principles in the first instance towards a resolution of the dispute.

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This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

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Although occasionally illustrated and referenced in contemporary histories of modern furniture and design, there is surprisingly little critical discussion or consideration of the role of the showroom in the promotion and dissemination of modern design during the mid-twentieth century. In these years, when the American lifestyle was popularly articulated and forcefully propagandized, the furniture showroom served as a principle site of professional and public indoctrination. Appropriating display techniques from modern exhibition design to showcase the American lifestyle as an abstracted, spatially integrated art form, the showroom provided an unencumbered landscape ideally suited to camera’s lens and the public’s imagination. Leading modern American furniture manufacturers, such as Herman Miller and Knoll Associates collaborated with major cultural institutions as well as department stores and retailers to maximize exposure and consumer demand for their products. Through such integrated marketing and merchandising strategies, showrooms also contributed to the broader social project to educate American consumers about modern design and the advantages of modern living. Related to the many model home programs and “good design” exhibitions of the 1950s, the furniture showroom occupies a unique place within the history and discourse of the postwar era. The peculiarities of the furniture showroom and its position as a point of intersection between the trade and the consumer, the commercial and the cultural, and the aesthetic and the ideological form the focus of this study.

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The aim of this study is to explore whether Australian mineral companies operating in high human rights risk countries provide more human rights disclosures than companies operating in low risk countries. A content analysis instrument containing 88 specific human rights performance items derived from a number of international human rights guidelines has been developed to investigate the annual reports, social responsibility reports and corporate websites of the top 50 Australian mineral companies (2010/2011). The findings show that human rights performance disclosures by companies with operations in high human rights risk countries are significantly higher than companies with operations in the low risk countries. By disclosing extended human rights performance information, companies operating in high risk countries appear to ease community concerns about human rights violations. The finding is consistent with legitimacy theory which posits that organisations respond to community concerns in relation to particular social issues.

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Background Australia’s mineral, resource and infrastructure sectors continues to expand as operations in rural and remote locations increasingly rely on fly-in, fly-out or drive-in, drive-out workforces in order to become economically competitive. The issues in employing these workforces are becoming more apparent and include a range of physical, mental, psychosocial, safety and community challenges. Objectives This review aims to consolidate a range of research conducted to communicate potential challenges for industry in relation to a wide variety of issues when engaging and using FIFO/DIDO workforces which includes roster design, working hours, fatigue, safety performance, employee wellbeing, turnover, psychosocial relationships and community concerns. Methods A wide literature review was performed using EBSCOhost and Google Scholar, with a focus on FIFO or DIDO workforces engaged within the resources sector. Results A number of existing gaps in the management of FIFO workforces and potential for future research were identified. This included the identification of various roster designs and hours worked across the resources industry and how to best understand the influences of roster swings, and work hours on fatigue, safety, psychological wellbeing and job satisfaction. Fatigue management, particularly in relation to travelling after extended work shifts can increase the risk for road safety and influence safety performance while at work due to a culmination of long hours, roster cycle and accumulated sleep debt. Further challenges associated with the engagement of this workforce include feelings of isolation, physiological and general health and lifestyle concerns. Conclusions FIFO workforces appear to be at an increased risk physically and mentally due to a wide range of influences of this unique lifestyle, particularly in relation to rosters, length of shift and feelings of community disengagement. Research and data collected has been limited in understanding the influences on employee engagement, satisfaction, retention and safety. Ensuring the challenges associated with FIFO employment are understood, addressed and communicated to workers and their families may assist.

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In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.

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The increasing focus of relationship marketing and customer relationship management (CRM) studies on issues of customer profitability has led to the emergence of an area of research on profitable customer management. Nevertheless, there is a notable lack of empirical research examining the current practices of firms specifically with regard to the profitable management of customer relationships according to the approaches suggested in theory. This thesis fills this research gap by exploring profitable customer management in the retail banking sector. Several topics are covered, including marketing metrics and accountability; challenges in the implementation of profitable customer management approaches in practice; analytic versus heuristic (‘rule of thumb’) decision making; and the modification of costly customer behavior in order to increase customer profitability, customer lifetime value (CLV), and customer equity, i.e. the financial value of the customer base. The thesis critically reviews the concept of customer equity and proposes a Customer Equity Scorecard, providing a starting point for a constructive dialog between marketing and finance concerning the development of appropriate metrics to measure marketing outcomes. Since customer management and measurement issues go hand in hand, profitable customer management is contingent on both marketing management skills and financial measurement skills. A clear gap between marketing theory and practice regarding profitable customer management is also identified. The findings show that key customer management aspects that have been proposed within the literature on profitable customer management for many years, are not being actively applied by the banks included in the research. Instead, several areas of customer management decision making are found to be influenced by heuristics. This dilemma for marketing accountability is addressed by emphasizing that CLV and customer equity, which are aggregate metrics, only provide certain indications regarding the relative value of customers and the approximate value of the customer base (or groups of customers), respectively. The value created by marketing manifests itself in the effect of marketing actions on customer perceptions, behavior, and ultimately the components of CLV, namely revenues, costs, risk, and retention, as well as additional components of customer equity, such as customer acquisition. The thesis also points out that although costs are a crucial component of CLV, they have largely been neglected in prior CRM research. Cost-cutting has often been viewed negatively in customer-focused marketing literature on service quality and customer profitability, but the case studies in this thesis demonstrate that reduced costs do not necessarily have to lead to lower service quality, customer retention, and customer-related revenues. Consequently, this thesis provides an expanded foundation upon which marketers can stake their claim for accountability. By focusing on the range of drivers and all of the components of CLV and customer equity, marketing has the potential to provide specific evidence concerning how various activities have affected the drivers and components of CLV within different groups of customers, and the implications for customer equity on a customer base level.

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Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.