Understanding post‐adoption IS usage stages: an empirical assessment of self‐service information systems

Organisations have invested in self‐service information systems (IS) to provide a direct interface for service delivery. Enriching the usage of these systems can provide organisations with immense benefits. However, limited research has been directed towards understanding post‐adoption IS usage behaviour in general and specifically in the context of self‐service IS. This study proposes post‐adoption IS usage behaviour as a broader concept constituting feature level usage of IS, integration of IS in the work system and exploration of new uses of IS. We evaluate how the new conceptualisation can be used to classify users at different stages of self‐service IS usage. Further, we examine user perceptions that differentiate among the users situated at different self‐service IS usage stages. Data were collected in the context of a self‐service Web‐based IS to validate the post‐adoption IS usage constructs and to examine the proposed thesis. The newly developed conceptual structure and measures for post‐adoption IS usage behaviour exhibit strong psychometric properties. The analysis shows three distinct post‐adoption IS usage stages and highlights that usefulness, user‐initiated learning, ease of use, satisfaction and voluntariness of use differentiate users at the different stages of post‐adoption IS usage. The results show that these variables aggregate into value confirmation and learning orientation as two higher‐level concepts. Further, we evaluate the predictive efficacy of the research model in classifying users into different post‐adoption self‐service IS usage stages. Implications are drawn for future research.     

鹤岗市区水资源开发利用状况及潜力分析

在对鹤岗市区现状用水及近10 a用水情况调查分析基础上,对该区水资源开发利用状况、开发利用程度、潜力进行分析计算,并提出水资源开发利用存在的问题。     

灌区用水管理信息化建设的信息传输途径

信息传输技术的飞速发展为灌区信息化建设提供了坚实的基础,根据灌区信息采集及传输的实际需求,建议在进行需求分析的基础上,依据信息点的类别,选择不同的网络传输方式,同时应尽可能利用现有的社会或自有通讯资源,以减少通讯基础设施的投资和管理维护升级费用,有利于灌区信息化的可持续发展。     

Sequence-based clustering for Web usage mining: A new experimental framework and ANN-enhanced K-means algorithm

We develop a general sequence-based clustering method by proposing new sequence representation schemes in association with Markov models. The resulting sequence representations allow for calculation of vector-based distances (dissimilarities) between Web user sessions and thus can be used as inputs of various clustering algorithms. We develop an evaluation framework in which the performances of the algorithms are compared in terms of whether the clusters (groups of Web users who follow the same Markov process) are correctly identified using a replicated clustering approach. A series of experiments is conducted to investigate whether clustering performance is affected by different sequence representations and different distance measures as well as by other factors such as number of actual Web user clusters, number of Web pages, similarity between clusters, minimum session length, number of user sessions, and number of clusters to form. A new, fuzzy ART-enhanced K-means algorithm is also developed and its superior performance is demonstrated.     

Explaining IS continuance in environments where usage is mandatory

Several research efforts over the last decade have attempted to explain user acceptance in mandated environments. This research is an attempt in the same direction. It addresses users’ satisfaction in mandated environments to further contribute to our understanding of how we can manage mandated use of information systems (IS) effectively beyond initial adoption. To better explain users’ IS continuance a revised post-acceptance model is proposed and empirically tested using the structural equation modelling technique. The results demonstrate the reliability and validity of the proposed measurement model and further demonstrate that confirmed expectations and ease of use perceptions explain 61% of the users’ satisfaction in this setting. Our findings have important implications for the management of users in mandated environments as well as for further research in the area of mandated use. To that end, we offer directions for future research.     

基于上下文感知的移动Web服务

移动Web服务的目的是随时、随地为资源有限的任何移动设备提供信息服务。该文以一个移动旅游者娱乐系统为例,阐述移动Web应用服务系统的体系结构、主要组件对象之间的交互及用户个性化服务的实现。讨论上下文管理机制的功能、模型和相关实现技术,介绍其接口与WSDL的实现。     

■ukasiewicz命题逻辑系统中有限命题集的约简理论

在n值■ukasiewicz命题逻辑中提出了命题集Γ的约简理论,引入由命题集Γ所诱导的形式背景的概念,从Γ及其子集的关系出发给出了n值命题逻辑中有限命题集Γ约简的判定定理以及求Γ约简的方法。说明了无穷值■ukasiewicz命题逻辑中命题集Γ的约简可转化为n值情形。     

普适计算环境下上下文信息推理的研究

从各种低层上下文信息得到对人们更加有用的高层上下文信息即上下文推理是当前研究的热点.针对该问题,采用描述逻辑,研究基于本体模型的上下文推理方法.首先简要介绍基于本体的上下文模型,该模型增加了对上下文特性的建模,然后分别研究基于本体的推理、基于规则的推理及不一致性验证3种推理方式,借助Jena框架的推理接口实现,推理功能全面,通用性强,基本满足了普适计算系统中上下文推理的需求,最后给出了推理的可用性.     

基于文档与搜索结果上下文的查询扩展方法

在查询扩展方法中,如果通过查询结果中关键词的上下文来计算候选关键词的权重,将权重大的词作为查询扩展词,其候选关键词来源于文档中关键词的上下文,这种方法存在主题漂移的问题。为了解决这个问题,提出一种将初始查询结果过滤,只选择与源文档语境相似的搜索结果,来帮助选择查询扩展词的方法。实验结果表明该方法能获得更合适的查询扩展词。     

一种基于使用差异的词语领域性分析方法

领域知识的表达形式最终体现在词汇的领域性上,因此对领域词及其部件的领域度分析是一个关键。该文在分词的基础上,对各个领域语料进行分析,利用词语之间的关系,引入链接分析方法分析词语在各个领域中的使用重要性,并通过词语在各个领域中的使用差异性计算其领域度,从而达到领域分析的目的,获取某个领域的领域部件词。该文采用以上方法在军事、娱乐等领域进行了实验,实验结果表明该方法相对于当前常用的tf×idf方法和Bootstrapping方法,可以更有效地进行领域分析获取领域部件词。