When more is too much: Operationalizing technology overload and exploring its impact on knowledge worker productivity

Individuals within organizations are beginning to make an important realization: more information technology (IT) usage in the workplace can, at times, lead to productivity losses. We conceptualize this frequently observed, but largely ignored phenomenon as technology overload, when additional technology tools begin to crowd out one’s productivity instead of enhancing it. We found support for three main factors contributing technology-based productivity losses through information overload, communication overload, and system feature overload. Interestingly, these factors are a function of the individuals who use the technology, not the technology itself. In this paper, we present the results from three studies that (1) develop and pre-test a scale measurement for technology overload and its distinct dimensions, (2) validate the instrument, and (3) explore the relationship between technology overload and knowledge worker productivity. Our findings demonstrate the relationship between information technology usage and knowledge worker productivity, and they suggest how tradeoffs can be managed to ameliorate technology overload.     

Ergonomics in bed design: the effect of spinal alignment on sleep parameters

This study combines concepts of bed design and sleep registrations to investigate how quality of spine support affects the manifestation of sleep in healthy subjects. Altogether, 17 normal sleepers (nine males, eight females; age 24.3±7.1 years) participated in an anthropometric screening, prior to the actual sleep experiments, during which personalised sleep system settings were determined according to individual body measures. Sleep systems (i.e. mattress and supporting structure) with an adjustable stiffness distribution were used. Subjects spent three nights of 8 h in bed in the sleep laboratory in a counterbalanced order (adaptation, personalised support and sagging support). During these nights, polysomnography was performed. Subjective sleep data were gathered by means of questionnaires. Results show that individual posture preferences are a determinant factor in the extent that subjects experience a negative effect while sleeping on a sagging sleep system. STATEMENT OF RELEVANCE: This study investigated how spine support affects sleep in healthy subjects, finding that the relationship between bedding and sleep quality is affected by individual anthropometry and sleep posture. In particular, results indicate that a sagging sleep system negatively affects sleep quality for people sleeping in a prone or lateral posture.     

The role of a location-based city exploration game in digital placemaking

ABSTRACT

Many digital technologies, such as social media, community systems, and public displays, have been studied to explore how people engage with each other in their community. Yet little is known about how one form of technology, location-based games (LBGs), can support urban residents in community awareness, city exploration, and placemaking as they navigate spaces and places in their cities. To explore this topic, we investigated the challenges urban residents faced in finding information about their community along a transit network. We then designed, developed, and evaluated an LBG called City Explorer that supports city exploration using gamification and the viewing and sharing of community information. We found that residents valued the fun, competition, and rewards afforded through play in public spaces, creating opportunities for placemaking through location services and knowledge sharing. Players also wanted additional knowledge about their transit commutes, including data about the frequency and routines of their transit rides. Collectively, such ridership data offers potential for smart city initiatives and illustrates that careful design considerations are required to balance people’s needs for play, personal data, privacy, and community information acquisition.     

浅谈面向物联网的信息存储技术

随着网络的飞速发展及普及,人们对互联网的使用已经相当的普遍.无线网络的应运而生,使得网络更加的机动灵活,更加方便快捷.我们都知道网络靠数据和信息来交流,各种数据和信息量非常大,这就需要更加强大的信息存储技术的支撑.同样,物联网也需要更加强大的信息存储技术来使得这项技术更加的成熟.本文通过对物联网信息存储技术的了解,来进一步探讨物联网信息存储技术的发展.     

Scalable context-dependent analysis of emergency egress models

Pervasive environments offer an increasing number of services to a large number of people moving within these environments, including timely information about where to go and when, and contextual information about the surrounding environment. This information may be conveyed to people through public displays or direct to a person’s mobile phone. People using these services interact with the system but they are also meeting other people and performing other activities as relevant opportunities arise. The design of such systems and the analysis of collective dynamic behaviour of people within them is a challenging problem. We present results on a novel usage of a scalable analysis technique in this context. We show the validity of an approach based on stochastic process-algebraic models by focussing on a representative example, i.e. emergency egress. The chosen case study has the advantage that detailed data is available from studies employing alternative analysis methods, making cross-methodology comparison possible. We also illustrate how realistic, context-dependent human behaviour, often observed in emergency egress, can naturally be embedded in the models, and how the effect of such behaviour on evacuation can be analysed in an efficient and scalable way. The proposed approach encompasses both the agent modelling viewpoint, as system behaviour emerges from specific (discrete) agent interaction, and the population viewpoint, when classes of homogeneous individuals are considered for a (continuous) approximation of overall system behaviour.     

Markerless cooperative augmented reality-based smart manufacturing double-check system: Case of safe PCBA inspection following automatic optical inspection

Augmented reality (AR) is a key technology anchored towards realizing Industry 4.0 smart manufacturing aims. In manufacturing inspection, AR has previously been employed to support operators in assessing thickness of manufactured parts, ship building, aircraft subassemblies and printed circuit board assemblies (PCBAs) with or without external markers in standalone head-mounted (HMD) or handheld systems. These AR systems often use optical see-through (OST) or video see-through (VST) technologies. Currently, cyber physical integration of processes in an industrial system synergizes production through increased efficiency and improved quality while facilitating customization. An operator manually double-checking/inspecting a product that has previously been automatically inspected can better rely on this existing defect location information once it is contextually and spatially overlaid within their field of view to intuitively and efficiently execute the task. Additional interactive information provided can quickly reorient a user, provide necessary contextual reference, and monitor progress of the task while alerting them of their safety. In this study, adopting an automatic optical inspection (AOI) wirelessly aided HMD-OST AR-based manual inspection system requiring no external markers for contextual registration is a promising direction towards smart and safe PCBA manufacturing in line with Industry 4.0. Animated rectangular bracket of high color contrast is employed to localize the spawned AOI defect point, an arrow overlaid with distance text provides user guidance, a contextual resizable image facilitates user double-checking and a progress bar tracks the inspection progress while monitoring tracking state. We evaluate the developed system's robustness, effectiveness of display technology used, suitability of contextual against static display modes, and display technology influence on various inspection attributes in a user study. Results demonstrate the system to be robust, OST-HMD outperforms handheld VST devices, contextual display mode to be significantly preferred to static mode, and display technology employed has no significant influence on the inspection attributes. Finally, registration precision results demonstrate usability of the system while superposition of distance to orientation information raises the inspection rate of PCBAs.     

Quality-optimized predictive analytics

On-line statistical and machine learning analytic tasks over large-scale contextual data streams coming from e.g., wireless sensor networks, Internet of Things environments, have gained high popularity nowadays due to their significance in knowledge extraction, regression and classification tasks, and, more generally, in making sense from large-scale streaming data. The quality of the received contextual information, however, impacts predictive analytics tasks especially when dealing with uncertain data, outliers data, and data containing missing values. Low quality of received contextual data significantly spoils the progressive inference and on-line statistical reasoning tasks, thus, bias is introduced in the induced knowledge, e.g., classification and decision making. To alleviate such situation, which is not so rare in real time contextual information processing systems, we propose a progressive time-optimized data quality-aware mechanism, which attempts to deliver contextual information of high quality to predictive analytics engines by progressively introducing a certain controlled delay. Such a mechanism progressively delivers high quality data as much as possible, thus eliminating possible biases in knowledge extraction and predictive analysis tasks. We propose an analytical model for this mechanism and show the benefits stem from this approach through comprehensive experimental evaluation and comparative assessment with quality-unaware methods over real sensory multivariate contextual data.     

基于双向注意力语境关联建模的论辩关系预测

在线讨论是当下公众表达意见和交流互动的主要方式之一. 参与者不仅发布评论来表述自己的观点, 还会回复已有的表述进行应答, 支持或反驳他人的观点. 识别表述-应答交互文本的论辩关系可以建模公众对话结构, 挖掘群体意见, 进而为企业产品营销、政府舆情监测等提供辅助. 现有的工作大多通过神经网络对交互文本的条件语义信息或者整...     

基于嵌入式微处理器的睡眠质量控制研究

分析了嵌入式睡眠质量控制研究的重要性。在不影响人们自然睡眠的基础上,采集人体的脉搏信号,挖掘其中与睡眠相关的信息,以嵌入式微处理器为核心设计系统监控硬件。利用虚拟仪器(LabVIEW)技术搭建脉搏信号显示平台,实现了脉搏信号的数据采集、波形显示、波形回放等功能,同时给出了软件设计流程图,以此构造睡眠质量控制系统,合理引导人们的睡眠。     

Facilitating implementation of total quality management through information technology

There is growing interest in the service industries in the adoption of quality management programs to improve their operational efficiency and market competitiveness. Deming’s total quality management (TQM) philosophy is one of the well-known ones. The TQM emphasizes continuous improvement through statistical control and the continuous training of people in the principles of quality management. One of the main implementation issues is the large volume of data that must be statistically analysed. Although recent researches have reported on how TQM is applied in various industries, few have discussed the importance of information technology in ensuring a successful TQM program. This paper reports on the application of information technology in the TQM process and how it can support management decisions. A case example is included to support these views.     

Information technology adoption and continuance: A longitudinal study of individuals’ behavioral intentions

Extant research on information technology (IT) adoption and continuance has not adequately modeled the times of adoption by individuals. This study argues that individuals adopt an innovation at different times and are likely to be influenced by different factors over time. The theoretical models are empirically validated using data gathered at three points in time through surveys of 132 users of a new innovation. The results indicate that the innovation attributes and individual characteristics influence individuals’ intentions to adopt the innovation during the early stage, and the innovation attributes and contextual factors impact the individuals’ intentions during the later stage.     

Awareness marks: adaptive services through user interactions with augmented objects

The ambient intelligence paradigm involves one important challenge: to be adaptive to users and context through simple and natural interactions. To meet this goal, it is important to associate data with relevant everyday objects in the environment, including users themselves, and to enable interaction mechanisms between these objects. Following this premise, in this paper, we present a conceptual model to link contextual information with augmented elements acquired from user interactions in an implicit and transparent way. In this way, it is possible to personalize and enhance offered services in order to facilitate daily user activities. We call this contextual data “awareness marks”, and these awareness marks make it possible to offer novel services adapted from past events that were captured as they happened. Moreover, we have developed and evaluated a set of prototypes using Near Field Communication technology, which follows the presented model.     

CA-FCM: Towards a formal representation of expert’s causal judgements over construction project changes

Aimed at improving the proactive benefits of Fuzzy Cognitive Mapping (FCM) for predicting construction project changes, this paper presents CA-FCM: a Context-aware Fuzzy Cognitive Mapping approach. CA-FCM’s main functionality is to imitate the intuitive causal judgements of project experts over change causation in different contextual settings. Invoking the logical inference capabilities of semantic web tools, a hybrid inference mechanism is embedded within the proposed framework which enables establishing contextual connections between prospective causal factors through a semi-automated process of generating relevant causal statements. Hence, CA-FCM can assist decision-makers with (1) a shared sense-making of the domain concepts which would significantly facilitate the manual construction of FCM scenarios, (2) providing contextualized recommendations of causal information required for developing FCM scenarios, (3) dynamic modelling of causal inferences, imitating expert reasoning on change causation and propagation. Towards providing a detailed delineation of CA-FCM’s effectiveness on providing assistance in planning for project changes, a partial implementation of the proposed framework was conducted within a real case scenario.     

基于数据仓库的质量管理决策支持系统研究

针对目前应用ERP系统实现质量管理时存在的数据缺乏组织性、利用率低、数据冗余的问题,引进数据仓库的概念,给出了其概念、性质、物理结构、逻辑结构。对以ERP为基础的质量管理信息系统做出了详细分析,并将数据仓库技术应用到质量管理信息系统中,提出了质量管理决策支持系统的体系结构和开发的关键技术,以快速准确获取历史数据中有价值信息,来指导企业的生产决策,提高质量管理水平,从而提高企业的经营管理水平和经济效益。     

Using decision tree modelling to support Peircian abduction in IS research: a systematic approach for generating and evaluating hypotheses for systematic theory development

Since their early development, computers have had a profound impact on how we conduct modern scientific research. The disciplines of mathematics and operations research are perhaps the earliest to be dramatically transformed by information technology. However, over the years, computing technologies have provided many new opportunities for information processing, problem solving and knowledge creation. In this paper, we explore the potential of data mining technology for providing support for systematic theory testing based on Peirce's theory of abduction. We propose a data mining approach to abducting and evaluating hypotheses based on Peirce's scientific method. We believe that this approach could assist scientist to more efficiently explore alternative hypotheses for existing theories. We demonstrate our approach with empirical observations collected using instruments from the well known user performance area of information systems research.     

AIoT-enabled smart surveillance for personal data digitalization: Contextual personalization-privacy paradox in smart home

Artificial intelligence of things technology provides smart surveillance capability for personal data digitalization. It will invade individuals’ information, physical, and social spaces and raise contextual privacy concerns while providing personalized services, which has not been explored in previous research. We theorize three types of smart surveillance and identify three subdimensions of contextual personalization and privacy concerns. Grounded in surveillance theory and personalization-privacy paradox, we examined the different trade-offs of contextual personalization and privacy concerns underlying the three types of smart surveillance on users’ behavioral intention in smart home context. The results also indicated that transparency can lessen the trade-off effects.     

Creating business value with process mining

Information systems research has a long-standing interest in how organizations gain value through information technology. In this article, we investigate a business process intelligence (BPI) technology that is receiving increasing interest in research and practice: process mining. Process mining uses digital trace data to visualize and measure the performance of business processes in order to inform managerial actions. While process mining has received tremendous uptake in practice, it is unknown how organizations use it to generate business value. We present the results of a multiple case study with key stakeholders from eight internationally operating companies. We identify key features of process mining – data & connectivity, process visualization, and process analytics – and show how they translate into a set of affordances that enable value creation. Specifically, process mining affords (1) perceiving end-to-end process visualizations and performance indicators, (2) sense-making of process-related information, (3) data-driven decision making, and (4) implementing interventions. Value is realized, in turn, in the form of process efficiency, monetary gains, and non-monetary gains, such as customer satisfaction. Our findings have implications for the discourse on IT value creation as we show how process mining constitutes a new class of business intelligence & analytics (BI&A) technology, that enables behavioral visibility and allows organizations to make evidence-based decisions about their business processes.     

Is the contextual information relevant in text clustering by compression?

Usually, when analyzing data that have not been processed or filtered yet, it can be observed that not all the data have equal importance. Thus, it is common to find relevant data surrounded by non relevant one. This occurs when analyzing textual information due to its intrinsic nature: texts contain words that provide a lot of information about the subject matter, whereas they contain other words with a little meaning or relevance. We believe that although in principle the non-relevant words are not as important as the relevant ones, the former constitute the substrate that supports the last. Since this substrate is the context that surrounds the relevant information, we call it the contextual information. In this paper, we analyze the relevance that the contextual information has in textual data, in a clustering by compression scenario. We generate the contextual information applying a distortion technique previously developed by the authors. One of the main characteristics of this technique is that it maintains the contextual information. In this paper we compare this technique with three new distortion techniques that destroy the contextual information in different ways. The experimental results support our hypothesis that the contextual information is relevant at least in the area of text clustering by compression.     

基于领域知识图谱的应急处置预案动态融合

随着与社区矫正对象有关的突发事件情况的日益复杂,从已有应急预案库中匹配得到的单一固定方案无法通过动态注入数据为不同的异常情景制定智能化应急处置预案,难以满足应急决策所需.为了提高社区服刑监管质量以及信息化监管水平,本文针对异常情景数据的多源异构、复杂关联和动态演化等特点,对多源异构数据进行联合挖掘,构建司法领域知识图谱(KGjudicial)与犯罪事理图谱(ELGcrime),为智能化应急预案的动态生成提供数据基础与辅助决策支持.此外,针对跨区域、多部门应急协同处置的实际业务需求,本文探究多部门信息协同方法以及应急处置预案的动态对接机制.结合司法领域知识图谱与犯罪事理图谱提出多部门应急处置预案融合技术,实现司法行政跨区域联合执法,提高社区服刑监管质量,节约社区矫正对象管理成本,为司法行政多部门的应急处置提供技术支持,维护社会长治久安.