Investigating use continuance of data mining tools

While improving decisional quality is important to businesses, continued use of DMTs is a critical issue for managerial personnel. This problem mainly concerns the willingness of an individual to participate in the behavior. It can be further defined in a routine-based working behavior. This problem essentially involves three key issues, task fit, technology use, and habit. This study therefore integrates task-technology fit (TTF) model, expectation–confirmation mode (ECM), and habit, to examine the determinants of continued use of DMTs. Prior studies have focused on intention to use DMTs in the first time and only considered part of the three issues for identifying the determinants. 285 respondents from managerial personnel were collected to empirically evaluate this research model. The three issues are all important in influencing continuance use intention of DMTs. In particular, the task-technology fit indicates a direct effect on two factors of the technology use issue, user satisfaction and perceived usefulness, and an indirect effect on continuance use intention. User satisfaction and perceived usefulness, and habit are the key predictors of continuance use intention.     

An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust

Rapid advances in mobile technologies and devices have made mobile banking increasingly important in mobile commerce and financial services. Using innovation diffusion theory and knowledge-based trust literature, this study develops a research model to examine the effect of innovation attributes (perceived relative advantage, ease of use and compatibility) and knowledge-based trust (perceived competence, benevolence and integrity) on attitude and behavioral intention about adopting (or continuing to use) mobile banking across potential and repeat customers. Based on a survey of 368 participants (177 for potential customers and 191 for repeat customers), this study uses a structural equation modeling approach to investigate the research model. The results indicate that perceived relative advantage, ease of use, compatibility, competence and integrity significantly influence attitude, which in turn lead to behavioral intention to adopt (or continue-to-use) mobile banking. Additionally, by using multi-group analysis with t-statistics, the results found that the antecedents of attitude toward mobile banking differ between potential and repeat customers. The implications for research and practice and future research directions are discussed.     

An extension of the technology acceptance model in the big data analytics system implementation environment

Research on the adoption of systems for big data analytics has drawn enormous attention in Information Systems research. This study extends big data analytics adoption research by examining the effects of system characteristics on the attitude of managers towards the usage of big data analytics systems. A research model has been proposed in this study based on an extensive review of literature pertaining to the Technology Acceptance Model, with further validation by a survey of 150 big data analytics users. Results of this survey confirm that characteristics of the big data analytics system have significant direct and indirect effects on belief in the benefits of big data analytics systems and perceived usefulness, attitude and adoption. Moreover, there are mediation effects that exist among the system characteristics, benefits of big data analytics systems, perceived usefulness and the attitude towards using big data analytics system. This study expands the existing body of knowledge on the adoption of big data analytics systems, and benefits big data analytics providers and vendors while helping in the formulation of their business models.     

Technology readiness and the organizational journey towards AI adoption: An empirical study

Artificial Intelligence (AI) is viewed as having potential for significant economic and social impact. However, its history of boom and bust cycles can make potential adopters wary. A cross-sectional, qualitative study was carried out, with a purposive sample of AI experts from research, development and business functions, to gain a deeper understanding of the adoption process. Technology Readiness Levels were used as a benchmark against which the experts could align their experiences. A model of AI adoption is proposed which embeds an extended version of the People, Processes, Technology lens, incorporating Data. The model suggests that people, process and data readiness are required in addition to technology readiness to achieve long term operational success with AI. The findings further indicate that innovative organizations should build bridges between technical and business functions.     

Understanding the adoption of location-based recommendation agents among active users of social networking sites

Nowadays, using increasingly granular data, from real-time location information and detailed demographics to consumers-generated content on the social networking sites (SNSs), businesses are starting to offer precise location-based product recommendation services through mobile devices. Based on the technology acceptance model (TAM), this paper develops a theoretical model to examine the adoption intention of active SNS users toward location-based recommendation agents (LBRAs). The research model was tested by using the Partial Least Squares (PLS) technique. The results show that perceived usefulness, perceived control, and perceived institutional assurance are important in developing adoption intention. Perceived effort saving, special treatment, and social benefit have influences on the adoption intention through the mediating effect of perceived usefulness. Perceived accuracy has direct influence on adoption intention.     

Determinants of master data management adoption by local government organizations: An empirical study

Master Data Management (MDM) is an approach for effective management of shared master data across organizations. In the public sector, MDM initiatives have been developed; however, the adoption among local government remains slow and there has been little interest in MDM adoption in extant research. Building on a Technology-Organization-Environment (TOE) framework, a conceptual model which highlights a set of potential determinants affecting the adoption of MDM by local government was developed. To validate the model, data were collected via survey from 224 responses from Malaysian local government department units. Using SEM-PLS, the study confirmed that data quality and data governance are two determinants of MDM adoption specific to the context of Malaysian local government, and four other determinants – complexity, top management support, technological competence, and citizen demand – are found to have significant effects on MDM adoption by local government. Surprisingly, three determinants – relative advantage, data security, and government policy – are found to have non-significant relationships to the adoption of MDM by local government. In addition, top management support is revealed to be a cornerstone of MDM technological competence in local government. The study contributes to the theoretical, contextual, and practical knowledge of MDM and IT adoption in the context of local government.     

Analyzing ICT adoption and use effects on knowledge creation: An empirical investigation in SMEs

This paper investigates the influence of the adoption and use of information and communication technology (ICT) on organizational learning (OL). The focus is on knowledge, creation, as an articulated construct for the OL concept, and the SECI (Socialization, Externalization, Combination and Internalization) model is used as a reference for knowledge, creation. ICT use is seen here as consisting of three different orientations: informative, communicative and workflow. The results, based on a sample of around 300 Spanish small- and, medium-sized enterprises (SMEs), indicate that ICT has a significant positive influence on the, four processes for creating knowledge. ICT oriented to communication and workflow is found, to produce a significant positive impact on knowledge creation processes, except for, socialization process, while ICT use for information does not influence any of the processes for, creating knowledge and OL.     

多理论视角下企业云ERP系统转换意愿研究

随着云计算的不断发展,云企业信息系统(EIS)显示出其优势,愈来愈多企业愿意考虑从传统EIS转换到云EIS系统。然而,却很少研究探讨企业在EIS的转换议题,本研究整合信息系统成功模型和技术接受模型,发展一个多理论框架去探索企业向云ERP转换的意愿。我们从企业管理者收集了199份调查问卷,通过结构方程模型验证本研究模型与假设,结果发现有用性和易用性是影响转换意愿重要因素,易用性、信息质量和系统质量则正向影响认知有用性,这些结论,给未来转换意愿研究提供了参考,我们建议云服务供应商应重视系统本身的易用性和有用性,提高系统质量并关注信息质量,以帮助他们提供企业需求的产品,吸引更多企业从传统EIS转换到云EIS。     

移动数据业务消费者购买意愿的影响因素研究

摘要：本文围绕着移动数据业务市场消费者购买意愿的影响因素展开了研究,通过文献的回顾和理论演绎,提出了移动数据业务购买意愿的七大影响因素。之后,在借鉴已有成熟量表的基础上,结合实际设计了调查问卷,并对中国移动的三个品牌用户进行了大样本的分层抽样调查。通过结构化方程分析,本文发现社会影响因素、感知有用性和感知价格对购买意愿的影响最为突出,而感知安全性在中国移动数据业务市场上的作用并不显著。本文在总结以前学者有关TAM及数据业务领域的TAM模型的基础上,提出移动数据业务的消费者购买意愿影响因素研究模型。通过实证分析发现感知有用性和感知价格两个因素对移动数据业务消费者购买意愿的影响最大,而被外国学者验证过的对购买意愿显著影响的感知安全性在国内却影响不显著。此发现对于移动数据业务的开发及其推广具有重要的意义,运营商可以进一步了解消费者的需求和期望,从而使用恰当的营销手段推出消费者更愿意使用的业务。     

An empirical investigation of factors affecting ubiquitous computing use and U-business value

This research investigates the factors that influence the use of ubiquitous computing and U-business value. It considers system, information and service qualities as the major factors affecting the use of ubiquitous computing. System quality is measured by accessibility, stability and ease of use. Relevance, accuracy and timeliness are used to measure information quality. Reliability, quickness and secrecy are used to measure service quality. U-business value measures the value created from business operations, business processes, and customer relationships improved by the use of ubiquitous computing. Our results show that system accessibility, information accuracy and timeliness, and service quickness exert crucial influences on ubiquitous computing use. We also find that the use of ubiquitous computing creates value by enhancing business operations, business processes, and customer satisfaction. These findings suggest that information quality is relatively more important than system and service qualities for the creation of value in a ubiquitous computing environment. Our research model and empirical results provide valuable indicators for the direction of future research and also suggest managerial guidelines for the successful development and adoption of ubiquitous computing within an organization.     

浅谈税务数据挖掘与深度利用

中国入世对政府部门的职能提出了严峻挑战,实现税务信息化是税务部门急待解决的问题,而数据挖掘是实现信息化的必由之路。金税三期展开前后,税务部门都比较关注税务数据的深度利用和数据挖掘问题。本文浅谈对税务数据深度利用的理解,并在此基础上提出应该考虑的核心工作,最后介绍在税务数据利用平台建设方面的一些心得体会。     

基于数据挖掘的舆情监测系统设计

文章设计一种部署于互联网上的舆情监测应用系统,该系统能够对互联网上的网页、论坛、微博等多种信息媒介进行监测,并自动的采集各种页面上的数据。通过数据挖掘方法从互联网中不同的信息媒介中提取出有价值的信息,并对网络舆情的状况和发展趋势做出预测,实现对互联网上的网络舆情进行实时监测的应用目标。     

Understanding the dynamics of users’ belief in software application adoption

Research has identified numerous factors that influence initial technology adoption decisions. However, extant studies consider beliefs to be static rather than dynamic over the adoption time-span. Various models have been employed to identify adoption behavior, pre- and post-adoption, however, there is little research on the dynamics of users’ belief structures over time and the inter-relationships among them. This study aims to investigate the dynamic nature of users’ beliefs and the relationships among their dynamics, i.e., rates of change. We test our research model based on data obtained at three time-windows using a parallel-growth process model. The results reveal that self-efficacy, usefulness and intention to use are likely to be dynamic, and increase with time. The rate of change in self-efficacy influences the rate of change in usefulness, which in turn affects the rate of change in intention to use. This study theoretically contributes to expanding the extant cross-sectional TAM research to include time-phased TAM studies, and highlights the role of self-efficacy as an important determinant of the dynamics.     

Examining the influence of intermediaries in facilitating e-government adoption: An empirical investigation

The adoption and diffusion of electronic government is often impeded by many social and individual factors relating to citizens. In this respect, intermediaries have emerged as a new model for delivering e-government services to overcome such obstacles. This study aims to examine the role of intermediaries in facilitating e-government adoption and diffusion using a survey based empirical study of 502 participants in Madinah City in Saudi Arabia. An extended UTAUT model is used as the theoretical basis utilizing trust in the Internet and Intermediaries. The results of this study show that there are significant relationships among the factors that influence intention to use e-government, namely, performance expectancy, effort expectancy, and trust of intermediary. In addition, the findings show that there is a significant relationship between facilitating conditions and usage behavior proving that intermediaries can influence adoption of e-government services.     

An empirical study of the antecedents of data completeness in electronic medical records

There is a body of research that highlights the role of data management to improve the quality of data, which in return improves organizational performance. The literature in data management has indicated the five theoretical constructs used to understand the factors influencing data quality, including top management support, capability on the regulation and process management, business-IT alignment, staff participation, and integration of information systems. However, it is unclear how these theoretical constructs can be utilized to understand the antecedents of data completeness as a dimension of data quality. Following that stream of research, the current paper examines the factors influencing data completeness in electronic medical records (EMR). The scope of this study is by only surveying medical professionals at healthcare settings in northern Nevada. The empirical results reveal that resources should be added as one of the antecedents of data completeness in EMR.     

工作决策影响因素的实证研究

运用T检验、列联表分析和Eogistic回归分析等实证研究方法考察求职者工作决策的主要影响因素。结果发现，在员工-组织匹配、个人-工作匹配、主观感知到的组织配适度、主观感知到的工作配适度、性别、工作经历和潜在工作机会这些可能对工作决策产生影响的因素中，个人-工作匹配和有无工作经历对工作决策的预测效力不显著，员工-组织匹配和主观感知到的组织配适度及主观感知到的工作配适度均有积极影响，性别和潜在就业机会则有负面影响，即女性和自认为潜在工作机会比较小的求职者倾向于作出接受工作的决策。     

数据挖掘在客户关系管理中的应用研究

企业之间市场竞争的焦点从产品质量的竞争转移到客户资源的争夺,为了从客户数据中找出对企业有价值的信息,概述了数据挖掘技术的方法、工具和流程;总结了如何在CRM应用数据挖掘技术。     

合作制造企业间关系价值影响因素的实证分析

从战略的视角来分析影响合作制造企业关系价值,对完善企业合作制造理论体系具有重要的研究意义。因此,在概述了国内外有关学者对企业关系价值含义的基础上,从一个全新的角度出发,对合作制造企业的关系价值进行了界定。针对该研究对象自身的特点,深入分析了影响合作制造企业关系价值的各主要因素间的相互关系,并采用结构方程模型对其影响因素进行了实证分析。     

Determinants of mHealth success: An empirical investigation of the user perspective

Mobile health (mHealth) applications have become an important tool to support public health, especially in times of increased health awareness in the midst of the COVID-19 pandemic. However, there is still uncertainty about what factors determine successful mHealth services from the users’ perspective. Based on the results of a systematic literature review, a qualitative content analysis of available apps and semi-structured user and expert interviews, we derive a structural model with antecedents on user attitudes towards mHealth and user satisfaction with the mHealth application. These variables determine users’ intention to continue using the application and their intention to recommend it to others. For verification, we tested the model with a sample of 249 German mHealth users from the “MyFitnessPal” community using structural equation modelling and found that all derived path relations have significant coefficients.     

基于决策树方法的数据挖掘分析

介绍了数据挖掘与决策树算法的一些基本概念,然后对最经典也得到最广泛应用的ID3算法及其改进算法作了详细介绍,在最后给出了该算法的一些数据结构和实现代码。