Critical success factors for the successful customer relationship management: a conceptual case study

Customer Relationship Management (CRM) technology have integrated the latest information technology, including: internet and E-commerce, multi-media technology, data warehousing data mining and artificial intelligence. This is all about the value of customer relationship management. It congregate the scattering data through the process of analysis, it provide a comprehensive and holistic view of certain individual customers. Customer Relationship Management originated and prevailed among western companies, it has already spread in many East Asian countries, such as: Japan, Korean, India and China etc. In order to improve the existing CRM implementation process and enhance the success rate of the CRM implementation, we present the most important Critical Success Factors for the CRM implementation through literature reviews, the chosen CSFs were based on previous studies in the CRM implementation field, focus on the identification of CRM projects, whether they have achieved success or subject to obscure deficiency. Subsequently, the literature study will provide us a group of CSFs which considered to be a comprehensive summarization of those most important factors for CRM implementation projects. It is a challenging work, still some points are summarized

Critical Success Factors in Data Mining Projects.

The increasing awareness of data mining technology, along with the attendant increase in the capturing, warehousing, and utilization of historical data to support evidence-based decision making, is leading many organizations to recognize that the effective use of data is the key element in the next generation of client-server enterprise information technology. The concept of data mining is gaining acceptance in business as a means of seeking higher profits and lower costs. To deploy data mining projects successfully, organizations need to know the key factors for successful data mining. Implementing emerging information systems (IS) can be risky if the critical success factors (CSFs) have been researched insufficiently or documented inadequately. While numerous studies have listed the advantages and described the data mining process, there is little research on the success factors of data mining. This dissertation identifies CSFs in data mining projects. Chapter 1 introduces the history of the data mining process and states the problems, purposes, and significances of this dissertation. Chapter 2 reviews the literature, discusses general concepts of data mining and data mining project contexts, and reviews general concepts of CSF methodologies. It also describes the identification process for the various CSFs used to develop the research framework. Chapter 3 describes the research framework and methodology, detailing how the CSFs were identified and validated from more than 1,300 articles published on data mining and related topics. The validated CSFs, organized into a research framework using 7 factors, generate the research questions and hypotheses. Chapter 4 presents analysis and results, along with the chain of evidence for each research question, the quantitative instrument and survey results. In addition, it discusses how the data were collected and analyzed to answer the research questions. Chapter 5 concludes with a summary of the findings, describing assumptions and limitations and suggesting future research

Global Management Effectiveness Study: Integrated Social and Ecological Report for Non-node and Node Sites

The purpose of this study is to provide a critical assessment of the implementation, impact, and performance of Marine Managed Area (MMA) projects to serve as a basis for improved planning and implementation of new MMA projects worldwide. The specific objectives of the study are (1) to determine the socioeconomic, governance and ecological effects of MMAs; (2) to determine the critical factors influencing MMA effects, as well as the impact of the timing of those factors on the effects of the MMA; and (3) to provide tools for predicting MMA effects based on ecological, socioeconomic and governance variable

Commodities and Linkages: Meeting the Policy Challenge

The results of detailed empirical enquiry into the nature and determinants of the breadth and depth of linkages in and out of the commodities sector in eight SSA countries (Angola, Botswana, Gabon, Ghana, Nigeria, South Africa Tanzania, and Zambia) and six sectors (copper, diamonds, gold, oil and gas, mining services and timber) has shown extensive scope for industrial development (MMCP DP 13, 2011). A primary conclusion of this research was that policy in both the private and public realm was a prime factor holding back the development of linkages. Addressing this problem requires the closing of three sets of misalignments between policy and practice – within the corporate sector, within the public sector, and between the public sector and other stakeholders involved in linkage development. In addition, specific policies need to be developed, monitored and implemented in relation to the three contextual drivers of linkages from the commodity sector – skills and capabilities, infrastructure and policies towards ownership

Data-Driven Application Maintenance: Views from the Trenches

In this paper we present our experience during design, development, and pilot deployments of a data-driven machine learning based application maintenance solution. We implemented a proof of concept to address a spectrum of interrelated problems encountered in application maintenance projects including duplicate incident ticket identification, assignee recommendation, theme mining, and mapping of incidents to business processes. In the context of IT services, these problems are frequently encountered, yet there is a gap in bringing automation and optimization. Despite long-standing research around mining and analysis of software repositories, such research outputs are not adopted well in practice due to the constraints these solutions impose on the users. We discuss need for designing pragmatic solutions with low barriers to adoption and addressing right level of complexity of problems with respect to underlying business constraints and nature of data.Comment: Earlier version of paper appearing in proceedings of the 4th International Workshop on Software Engineering Research and Industrial Practice (SER&IP), IEEE Press, pp. 48-54, 201

The necessities for building a model to evaluate Business Intelligence projects- Literature Review

In recent years Business Intelligence (BI) systems have consistently been rated as one of the highest priorities of Information Systems (IS) and business leaders. BI allows firms to apply information for supporting their processes and decisions by combining its capabilities in both of organizational and technical issues. Many of companies are being spent a significant portion of its IT budgets on business intelligence and related technology. Evaluation of BI readiness is vital because it serves two important goals. First, it shows gaps areas where company is not ready to proceed with its BI efforts. By identifying BI readiness gaps, we can avoid wasting time and resources. Second, the evaluation guides us what we need to close the gaps and implement BI with a high probability of success. This paper proposes to present an overview of BI and necessities for evaluation of readiness. Key words: Business intelligence, Evaluation, Success, ReadinessComment: International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.2, April 201

Beyond Surveys: Analyzing Software Development Artifacts to Assess Teaching Efforts

This Innovative Practice Full Paper presents an approach of using software development artifacts to gauge student behavior and the effectiveness of changes to curriculum design. There is an ongoing need to adapt university courses to changing requirements and shifts in industry. As an educator it is therefore vital to have access to methods, with which to ascertain the effects of curriculum design changes. In this paper, we present our approach of analyzing software repositories in order to gauge student behavior during project work. We evaluate this approach in a case study of a university undergraduate software development course teaching agile development methodologies. Surveys revealed positive attitudes towards the course and the change of employed development methodology from Scrum to Kanban. However, surveys were not usable to ascertain the degree to which students had adapted their workflows and whether they had done so in accordance with course goals. Therefore, we analyzed students' software repository data, which represents information that can be collected by educators to reveal insights into learning successes and detailed student behavior. We analyze the software repositories created during the last five courses, and evaluate differences in workflows between Kanban and Scrum usage

Shared Value in Chile: Increasing Private Sector Competitiveness by Solving Social Problems

Over the last few decades, Chile has experienced rapid and sustained economic, social, and institutional development. Crucial challenges remain, however, in the form of social inequity, lack of opportunity, mistrust, and social unrest. The Chilean private sector is at an inflection point in its relationship with society. The corporate sector has both contributed to and benefited from the growth and development of the last decades, but remaining social challenges pose significant constraints to the continued growth of the private sector. High levels of mistrust regarding the role of business in society reflect a widespread belief that profit making activities are merely a demonstration of corporate greed. The Chilean private sector faces a frequently antagonistic relationship with government and civil society that will likely worsen unless companies are able to find ways to authentically link their businesses to efforts to solve Chile's social problems. On the other hand, if government and civil society conclude that the private sector has no contribution to make to the country's social and economic development strategy, Chile will squander an important engine for creating shared prosperity. The good news is that there does not need to be a trade-off between private sector competitiveness and greater prosperity for all Chileans. Shared value, a concept explained in Harvard Professor Michael Porter and Mark Kramer's Harvard Business Review articles, suggests an approach for companies to increase their competitiveness and profitability by helping to solve social problems. The public sector and civil society can increase the social benefits from shared value by thoughtfully partnering with the private secto