133 resultados para customer acquisition


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This paper sets out to investigate differences between intrapreneurs and entrepreneurs with regards to their resource utilisation behaviours through social capital and bricolage. In particular we were interested in those entrepreneurs who start their business while still being employed, as it allows us to compare how intrapreneurs and entrepreneurs make use of social capital within their employer. Our findings challenge some existing wisdoms in that it seems intrapreneurs make more use of social capital external to their employer than entrepreneurs, while the use of social capital internal to the company is similar to the use by entrepreneurs. Yet, internal organizational social capital seems to have a positive effect on performance for intrapreneurial efforts only, while external social capital is not related to performance. This suggests both intrapreneurs and entrepreneurs may benefit from reconsidering the focus they place on respectively external and internal organizational social capital. Bricolage behaviours were extremely prevalent amongst both intrapreneurs and entrepreneurs as well as being the strongest predictor of performance. This strong effect on performance for intrapreneurial ventures may suggest that bricolage behaviours need to be rethought when it comes to intrapreneurs.

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Successful identification and exploitation of opportunities has been an area of interest to many entrepreneurship researchers. Since Shane and Venkataraman’s seminal work (e.g. Shane and Venkataraman, 2000; Shane, 2000), several scholars have theorised on how firms identify, nurture and develop opportunities. The majority of this literature has been devoted to understanding how entrepreneurs search for new applications of their technological base or discover opportunities based on prior knowledge (Zahra, 2008; Sarasvathy et al., 2003). In particular, knowledge about potential customer needs and problems that may present opportunities is vital (Webb et al., 2010). Whereas the role of prior knowledge of customer problems (Shane, 2003; Shepherd and DeTienne, 2005) and positioning oneself in a so-called knowledge corridor (Fiet, 1996) has been researched, the role of opportunity characteristics and their interaction with customer-related mechanisms that facilitate and hinder opportunity identification has received scant attention.

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Nowadays, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes. A use case study is also presented in this paper to show the advantages of using OLAP and data cubes to analyze costumers’ opinions.

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What opportunities does a channel like Twitter offer to libraries, beyond the realm of marketing? We would like to highlight three roles for Twitter in the academic library environment: Twitter as a service delivery and service recovery channel; Twitter as a community builder; Twitter as a site for information experience.

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In a commercial environment, it is advantageous to know how long it takes customers to move between different regions, how long they spend in each region, and where they are likely to go as they move from one location to another. Presently, these measures can only be determined manually, or through the use of hardware tags (i.e. RFID). Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. They include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. While these traits cannot provide robust authentication, they can be used to provide identification at long range, and aid in object tracking and detection in disjoint camera networks. In this chapter we propose using colour, height and luggage soft biometrics to determine operational statistics relating to how people move through a space. A novel average soft biometric is used to locate people who look distinct, and these people are then detected at various locations within a disjoint camera network to gradually obtain operational statistics

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Studies of orthographic skills transfer between languages focus mostly on working memory (WM) ability in alphabetic first language (L1) speakers when learning another, often alphabetically congruent, language. We report two studies that, instead, explored the transferability of L1 orthographic processing skills in WM in logographic-L1 and alphabetic-L1 speakers. English-French bilingual and English monolingual (alphabetic-L1) speakers, and Chinese-English (logographic-L1) speakers, learned a set of artificial logographs and associated meanings (Study 1). The logographs were used in WM tasks with and without concurrent articulatory or visuo-spatial suppression. The logographic-L1 bilinguals were markedly less affected by articulatory suppression than alphabetic-L1 monolinguals (who did not differ from their bilingual peers). Bilinguals overall were less affected by spatial interference, reflecting superior phonological processing skills or, conceivably, greater executive control. A comparison of span sizes for meaningful and meaningless logographs (Study 2) replicated these findings. However, the logographic-L1 bilinguals’ spans in L1 were measurably greater than those of their alphabetic-L1 (bilingual and monolingual) peers; a finding unaccounted for by faster articulation rates or differences in general intelligence. The overall pattern of results suggests an advantage (possibly perceptual) for logographic-L1 speakers, over and above the bilingual advantage also seen elsewhere in third language (L3) acquisition.

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While frontline employees (FLEs) are known to bend the rules or act in non-conforming ways for customers, the phenomenon of FLEs over-servicing customers is not well understood. This paper proposes a behavioural concept termed customer-oriented deviance (COD) and a conceptual model of its key drivers. Using a qualitative study involving 22 in-depth interviews with FLEs, the analysis reveals three categories of COD behaviours: deviant service adaptation (DSA), deviant service communication (DSC), and deviant use of resources (DUR). The drivers of COD are categorised as individual (risk-taking, service aptitude, and pro-social moral values), situational (resource availability, social capita with customers, legitimacy of customer problems, and avoidance of hassles), and organisational (unconducive service climate and anticipated rewards). This paper contributes to understanding how and why FLEs over-service customers and extends current research by exploring multiple categories of behaviours within a services marketing context.

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In this issue of the Journal, the articles presented to the readers cover the breadth and depth of project management research and practice by addressing the relationship between project strategy and managing projects (Patanakul and Shenhar, “What Project Strategy Really Is: The Fundamental Building Block in Strategic Project Management”), on the need to align corporate strategy with program management (Ritson, Johansen, and Osborne, “Successful Programs Wanted: Exploring the Impact of Alignment”), identifying metrics to measure program success across project contexts (Shao, Müller, and Turner, “Measuring Program Success”), managing individual projects by identifying major risks in customer relationship management (CRM) implementation projects (Papadopoulos, Ojiako, Chipulu, and Lee, “The Criticality of Risk Factors in Customer Relationship Management Projects”), application of earned value management (EVM) to aerospace projects (Kwak and Anbari, “History, Practices, and Future of Earned Value Management in Government: Perspectives From NASA”), and capturing tacit knowledge of construction project professionals to determine the optimal construction site layout (Abdul-Rahman, Wang, and Siong, “Knowledge Acquisition Using Psychotherapy Technique for Critical Factors Influencing Construction Project Layout Planning”)...

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Each year, organizations in Australian mining industry (asset intensive industry) spend substantial amount of capital (A$86 billion in 2009-10) (Statistics, 2011) in acquiring engineering assets. Engineering assets are put to use in operations to generate value. Different functions (departments) of an organization have different expectations and requirements from each of the engineering asset e.g. return on investment, reliability, efficiency, maintainability, low cost of running the asset, low or nil environmental impact and easy of disposal, potential salvage value etc. Assets are acquired from suppliers or built by service providers and or internally. The process of acquiring assets is supported by procurement function. One of the most costly mistakes that organizations can make is acquiring the inappropriate or non-conforming assets that do not fit the purpose. The root cause of acquiring non confirming assets belongs to incorrect acquisition decision and the process of making decisions. It is very important that an asset acquisition decision is based on inputs and multi-criteria of each function within the organization which has direct or indirect impact on the acquisition, utilization, maintenance and disposal of the asset. Literature review shows that currently there is no comprehensive process framework and tool available to evaluate the inclusiveness and breadth of asset acquisition decisions that are taken in the Mining Organizations. This thesis discusses various such criteria and inputs that need to be considered and evaluated from various functions within the organization while making the asset acquisition decision. Criteria from functions such as finance, production, maintenance, logistics, procurement, asset management, environment health and safety, material management, training and development etc. need to be considered to make an effective and coherent asset acquisition decision. The thesis also discusses a tool that is developed to be used in the multi-criteria and cross functional acquisition decision making. The development of multi-criteria and cross functional inputs based decision framework and tool which utilizes that framework to formulate cross functional and integrated asset acquisition decisions are the contribution of this research.

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The majority of distribution utilities do not have accurate information on the constituents of their loads. This information is very useful in managing and planning the network, adequately and economically. Customer loads are normally categorized in three main sectors: 1) residential; 2) industrial; and 3) commercial. In this paper, penalized least-squares regression and Euclidean distance methods are developed for this application to identify and quantify the makeup of a feeder load with unknown sectors/subsectors. This process is done on a monthly basis to account for seasonal and other load changes. The error between the actual and estimated load profiles are used as a benchmark of accuracy. This approach has shown to be accurate in identifying customer types in unknown load profiles, and is used in cross-validation of the results and initial assumptions.

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As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.

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Convergence of pervasive technologies, techno-centric customers and the emergence of digitized channels, overabundance of user friendly retail applications are having a profound impact on retail experience, leading to the advent of ‘everywhere retailing’. With the rapid uptake of digital complimentary assets and smart mobile applications are revolutionizing the relationship of retailers with their customers and suppliers. Retail firms are increasingly investing substantial resources on dynamic Customer Relationship Management systems (D-CRM / U-CRM) to better engage with customers to sense and respond quickly (Agility of the firm) to their demands. However, unlike traditional CRM systems, engagement with U-CRM systems requires that firms be hyper sensitive to volatile customer needs and wants. Following the notions of firm agility, this study attempts to develop a framework to understand such unforeseen benefits and issues of U-CRM. This research-in-progress paper reports an a-priory framework including 62 U-CRM benefits derived through an archival analysis of literature.

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This paper provides a commentary on the contribution by Dr Chow who questioned whether the functions of learning are general across all categories of tasks or whether there are some task-particular aspects to the functions of learning in relation to task type. Specifically, they queried whether principles and practice for the acquisition of sport skills are different than what they are for musical, industrial, military and human factors skills. In this commentary we argue that ecological dynamics contains general principles of motor learning that can be instantiated in specific performance contexts to underpin learning design. In this proposal, we highlight the importance of conducting skill acquisition research in sport, rather than relying on empirical outcomes of research from a variety of different performance contexts. Here we discuss how task constraints of different performance contexts (sport, industry, military, music) provide different specific information sources that individuals use to couple their actions when performing and acquiring skills. We conclude by suggesting that his relationship between performance task constraints and learning processes might help explain the traditional emphasis on performance curves and performance outcomes to infer motor learning.