431 resultados para customer churn


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This paper presents and discusses organisational barriers and opportunities arising from the dissemination of design led innovation within a leading Australian airport corporation. This research is part of a greater action research program which aims to integrate design as a strategic capability through design led innovation within Australian businesses. Findings reveal that there is an opportunity to employ the theoretical framework and tools of design led innovation in practice to build collaborative idea generation by involving customers and stakeholders within the proposal of new to world propositions. The iterative gathering of deep customer insights also provided an opportunity to leverage a greater understanding of stakeholders and customers in strengthening continuing business partnerships through co-design. Challenges to the design led approach include resistance to the exploratory nature of gathering deep customer insights, the testing of long held assumptions and market data, and the disruption of an organisational mindset geared toward risk aversion instilled within the aviation industry. The implication from these findings is that design led innovation can provide the critical platform to allow for a business to grow and sustain internal design capabilities necessary to challenge prevailing assumptions about how its business model operates to deliver value to customers and stakeholders alike. The platform of design led innovation also provides an avenue to support a cultural transformation towards anticipating future needs necessary for establishing a position of leadership within the broader economic environment.

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The mining equipment technology services sector is driven by a reactive and user-centered design approach, with a technological focus on incremental new product development. As Australia moves out of its sustained mining boom, companies need to rethink their strategic position, to become agile to stay relevant in an enigmatic market. This paper reports on the first five months on an embedded case study within an Australian, family-owned mining manufacturer. The first author is currently engaged in a longitudinal design led innovation project, as a catalyst to guide the company’s journey to design integration. The results find that design led innovation could act as a channel for highlighting and exploring company disconnections with the marketplace and offer a customer-centric catalyst for internal change. Data collected for this study is from 12 analysed semistructured interviews, a focus group and a reflective journal, over a five-month period. This paper explores limitations to design integration, and highlights opportunities to explore and leverage entrepreneurial characteristics to stay agile, broaden innovation and future-proof through the next commodity cycle in the mining industry.

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Whether by using electronic banking, by using credit cards, or by synchronising a mobile telephone via Bluetooth to an in-car system, humans are a critical part in many cryptographic protocols daily. We reduced the gap that exists between the theory and the reality of the security of these cryptographic protocols involving humans, by creating tools and techniques for proofs and implementations of human-followable security. After three human research studies, we present a model for capturing human recognition; we provide a tool for generating values called Computer-HUman Recognisable Nonces (CHURNs); and we provide a model for capturing human perceptible freshness.

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This thesis examines Customer Relationship Management and how the capabilities of an organisation to innovate can be enhanced via its implementation in a Knowledge Based Firm. The research identifies current customer knowledge components within an organisation and identifies for future use, CRM components for implementation within a Knowledge Based Firm. Opinions from a panel of experts' are identified for best practice customer relationship strategy, the most important CRM processes and identification of customer knowledge components that will form the basis of implementing a successful CRM to gain a competitive advantage through enhancing the innovative capability for a Knowledge Based Firm.

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Purpose The social marketing literature tends to focus on upstream marketing (policy) and downstream (individual behaviour change) and has a limited view on midstream (working with partners and community groups) social marketing. The paper proposes midstream social marketing should also include an understanding of how services and service employees influence and support individual behaviour change goals. The paper presents four key services marketing principles - derived from services theory and thinking - which the paper believes to be essential for implementing effective midstream social marketing. Design/methodology/approach This is a conceptual paper that uses service theory and case-examples to show how service thinking can be used as a midstream social marketing approach. Findings For effective uptake and impact of social marketing services amongst people and populations, social marketers need to design programs that consider the service experience, the service employee, service quality/customer value and the active role of the customer in value creation. Research limitations/implications Services marketing is a well-established sub-discipline of marketing which, until recently, has not interacted with social marketing. The extension and application of services theory for social marketing can enrich and propel the social marketing discipline forward. Further research is recommended to evaluate how service principles can be applied in practice. Social implications Given that social marketing services tend not to be accessed in sufficient numbers by the people who most need them, social marketers need to think beyond the technical, cognitive, and organisational-focused goals when designing social services. Originality/value This paper identifies key service theories that social marketers should understand and use and is thus a source of fresh ideas for theory and practice.

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Purpose The purpose of this paper is to investigate the role of multiple actors in the value creation process for a preventative health service, and observe the subsequent impact on key service outcomes of satisfaction and customer behaviour intentions to use a preventative health service again in the future. Design/methodology/approach An online self-completion survey of Australian women (n=797) was conducted to test the proposed framework in the context of a free, government-provided breastscreening service. Data were analysed using Structural Equation Modelling (SEM). Findings The findings indicate that functional and emotional value are created from organisational and customer resources. These findings indicate that health service providers and customers are jointly responsible for the successful creation of value, leading to desirable outcomes for all stakeholders. Practical implications The results highlight to health professionals the aspects of service that can be managed in order to create value with target audiences. The findings also indicate the importance of the resources provided by users in the creation of value, signifying the importance of customer education and management. Originality/value This study provides a significant contribution to social marketing through the provision of an empirically validated model of value creation in a preventative health service. The model demonstrates how the creation and provision of value can lead to the achievement of desirable social behaviours - a key aim of social marketing.

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Because of increased competition between healthcare providers, higher customer expectations, stringent checks on insurance payments and new government regulations, it has become vital for healthcare organisations to enhance the quality of the care they provide, to increase efficiency, and to improve the cost effectiveness of their services. Consequently, a number of quality management concepts and tools are employed in the healthcare domain to achieve the most efficient ways of using time, manpower, space and other resources. Emergency departments are designed to provide a high-quality medical service with immediate availability of resources to those in need of emergency care. The challenge of maintaining a smooth flow of patients in emergency departments is a global problem. This study attempts to improve the patient flow in emergency departments by considering Lean techniques and Six Sigma methodology in a comprehensive conceptual framework. The proposed research will develop a systematic approach through integration of Lean techniques with Six Sigma methodology to improve patient flow in emergency departments. The results reported in this paper are based on a standard questionnaire survey of 350 patients in the Emergency Department of Aseer Central Hospital in Saudi Arabia. The results of the study led us to determine the most significant variables affecting patient satisfaction with patient flow, including waiting time during patient treatment in the emergency department; effectiveness of the system when dealing with the patient’s complaints; and the layout of the emergency department. The proposed model will be developed within a performance evaluation metric based on these critical variables, to be evaluated in future work within fuzzy logic for continuous quality improvement.

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Consumer awareness and usage of Unit Price (UP) information continues to hold academic interest. Originally designed as a device to enable shoppers to make comparisons between grocery products, it is argued consumers still lack a sufficient understanding of the device. Previous research has tended to focus on product choice, effect of time, and structural changes to price presentation. No studies have tested the effect of UP consumer education on grocery shopping expenditure. Supported by distributed learning theories, this is the first study to condition participants over a twenty week period, to comprehend and employ UP information while shopping. A 3x5 mixed factorial design was employed to collect data from 357 shoppers. A 3 (Control, Massed, Spaced) x 5 (Time Point: Week 0, 5, 10, 15 and 20) mixed factorial analysis of variance (ANOVA) was performed to analyse the data. Preliminary results revealed that the three groups differed in their average expenditure over the twenty weeks. The Control group remained stable across the five time points. Results indicated that both intensive (Massed) and less intensive (Spaced) exposure to UP information achieved similar results, with both group reducing average expenditure similarly by Week 5. These patterns held for twenty weeks, with conditioned groups reducing their grocery expenditure by over 10%. This research has academic value as a test of applied learning theories. We argue, retailers can attain considerable market advantages as efforts to enhance customers’ knowledge, through consumer education campaigns, can have a positive and strong impact on customer trust and goodwill toward the organisation. Hence, major practical implications for both regulators and retailers exist.

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Software as a Service (SaaS) is anticipated to provide significant benefits to small and medium enterprises (SMEs) due to ease of access to high-end applications, 7*24 availability, utility pricing, etc. However, underlying SaaS is the assumption that SMEs will directly interact with the SaaS vendor and use a self-service model. In practice, we see the rise of SaaS intermediaries who support SMEs with using SaaS. This paper reports on an empirical study of the role of intermediaries in terms of how they support SMEs in sourcing and leveraging SaaS for their business. The knowledge contributions of this paper are: (1) the identification and description of the role of SaaS intermediaries and (2) the specification of different roles of SaaS intermediaries, in particular a more basic role with technology orientation and operational alignment perspective and (3) a more added value role with customer orientation and strategic alignment perspective.

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Airport efficiency is important because it has a direct impact on customer safety and satisfaction and therefore the financial performance and sustainability of airports, airlines, and affiliated service providers. This is especially so in a world characterized by an increasing volume of both domestic and international air travel, price and other forms of competition between rival airports, airport hubs and airlines, and rapid and sometimes unexpected changes in airline routes and carriers. It also reflects expansion in the number of airports handling regional, national, and international traffic and the growth of complementary airport facilities including industrial, commercial, and retail premises. This has fostered a steadily increasing volume of research aimed at modeling and providing best-practice measures and estimates of airport efficiency using mathematical and econometric frontiers. The purpose of this chapter is to review these various methods as they apply to airports throughout the world. Apart from discussing the strengths and weaknesses of the different approaches and their key findings, the paper also examines the steps faced by researchers as they move through the modeling process in defining airport inputs and outputs and the purported efficiency drivers. Accordingly, the chapter provides guidance to those conducting empirical research on airport efficiency and serves as an aid for aviation regulators and airport operators among others interpreting airport efficiency research outcomes.

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In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

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A new community and communication type of social networks - online dating - are gaining momentum. With many people joining in the dating network, users become overwhelmed by choices for an ideal partner. A solution to this problem is providing users with partners recommendation based on their interests and activities. Traditional recommendation methods ignore the users’ needs and provide recommendations equally to all users. In this paper, we propose a recommendation approach that employs different recommendation strategies to different groups of members. A segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs. Then a targeted recommendation strategy is applied to each identified segment. Empirical results show that the proposed approach outperforms several existing recommendation methods.

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Contemporary online environments suffer from a regulatory gap; that is there are few options for participants between customer service departments and potentially expensive court cases in foreign jurisdictions. Whatever form of regulation ultimately fills that gap will be charged with determining whether specific behavior, within a specific environment, is fair or foul; whether it’s cheating or not. However, cheating is a term that, despite substantial academic study, remains problematic. Is anything the developer doesn’t want you to do cheating? Is it only if your actions breach the formal terms of service? What about the community norms, do they matter at all? All of these remain largely unresolved questions, due to the lack of public determination of cases in such environments, which have mostly been settled prior to legal action. In this paper, I propose a re-branding of participant activity in such environments into developer-sanctioned, advantage play, and cheating. Advantage play, ultimately, is activity within the environment in which the player is able to turn the mechanics of the environment to their advantage without breaching the rules of the environment. Such a definition, and the term itself, is based on the usage of the term within the gambling industry, in which advantage play is considered betting with the advantage in the players’ favor rather than that of the house. Through examples from both the gambling industry and the Massively Multiplayer Role-Playing Game Eve Online, I consider the problems in defining cheating, suggest how the term ‘advantage play’ may be useful in understanding participants behavior in contemporary environments, and ultimately consider the use of such terminology in dispute resolution models which may overcome this regulatory gap.

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The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

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Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.