Exploring barriers to knowledge flow at different knowledge management maturity stages

A significant amount of work has been done to better understand the barriers to knowledge flow and develop models of KM maturity; this was intended to help in assessing the progress of KM initiatives in the firm. However, to date there has been no comprehensive research that considers both these issues at the same time, and thus it is still necessary to explore the evolution of barriers to knowledge flow when the level of KM maturity is changing. We reviewed the progress of KM initiatives in recent years, categorized the barriers to knowledge flow according to the cultural historical activity theory (CHAT), and used one of the existing models of KM maturity (the Knowledge Navigator Model—KNM), to address gaps in the current literature. As part of our exploratory study, a longitudinal survey, involving constant observation, development and use of questionnaires and qualitative interviews with managers of seven firms were conducted. We selected the firms so they covered a wide range of KM maturity levels; triangulation was adopted to enhance the quality of the process. The major findings indicated that: (1) barriers to knowledge flow were inherently different at different KM maturity levels; and (2) various changes in the barriers to knowledge flow were associated with the maturity of the KM.     

Introducing hypertext in primary health care: a study on the feasibility of decision support for practitioners

A study on the feasibility of the introduction of hypertext systems for communication of medical knowledge in primary care is described. Shortliffe's constraints on areas for application of decision support are evaluated (i.e., theoretical barriers, observable and recognized needs among users, sources of usable knowledge, available system development method). Considering the barriers derived from the knowledge types and forms used by practitioners, hypertext was found suitable as support at 'breakdowns' in practice routines, to generate 'alarms', as well as for continued medical education. A survey of the a priori acceptance of decision support systems by general practitioners showed that 84% would use the computer support if it was available today and that full-text databases, such as hypertext, were given highest priority for introduction. Local specialist physicians were identified as knowledge sources for therapy advice. Implementation of prototype systems envisioned use of hypertext in primary care as the introduction of a communication medium for co-operative health care decision making. A model for the introduction into the work environment is described.     

正则化方法及非刚体匹配在医学动态图象分析中的应用

为了给医生利用医学图象进行诊断和分析心血管疾病提供一个有效的工具和途径，利用计算机视觉中的正则化方法，结合心脏和心血管动态特征的临床知识，对两种医学动态图象(超声心动图和心血管造影图)进行了定量的运动分析，并完成了一套应用软件．实验结果证明，该方法明显优于以往的图象分析方法。     

Are norms enough? The role of collaborative norms in promoting organizational knowledge seeking

Knowledge sharing, which is critical for the strategic utilization of knowledge resources for the benefit of an organization, can only take place when both knowledge contribution and knowledge seeking exist. However, most previous research has focused on only one side of this process – knowledge contribution motivations. This is despite the fact that various barriers to knowledge seeking and reuse exist, such as the effort required to seek relevant knowledge and the cost of future obligation. In overcoming such barriers, norms related to collaboration are considered to be important. However, little is known of how these norms operate in conjunction with other antecedents to influence individuals' knowledge seeking behavior. Addressing the knowledge gap, this study explores how collaborative norms in an organization impact knowledge seeking with regard to a common knowledge management system type – the electronic knowledge repository (EKR). For this purpose, we have developed a model and tested it through a survey of EKR users in knowledge-intensive organizations. Our results indicate that collaborative norms positively impact individuals' knowledge seeking behavior through EKRs, both directly and through reducing the negative effect of future obligation on seeking. However, collaborative norms could also undermine the positive impact of perceived usefulness on knowledge seeking behavior. We identify other antecedents of knowledge seeking such as knowledge growth, resource-facilitating conditions, and self-efficacy. Implications for research and knowledge sharing practice are discussed.     

Global social knowledge management – Understanding barriers for global workers utilizing social software

Utilizing social software as a part of a global knowledge management strategy has raised increasing interest in enterprises as well as in the educational domain. Rather than being proactive, organizations tend to face barriers related to knowledge management after the problems occur. When dealing with social technologies in a distributed setting, organizations and individuals face a variety of barriers currently unrecognized in knowledge management literature. Within the study, we analyze knowledge management literature extending the body of knowledge with barrier analysis regarding global challenges as well as social software. Our focus is especially on knowledge exchange and globally distributed collaboration activities in organizations. We argue for contextualized understanding of the barriers, recognizing the challenges studied in similar activities. The paper concludes with a synthesis of these interrelated components, proposing a Global Social Knowledge Management-barrier framework that demonstrates the wide spectrum of possible challenges in globally distributed, social software supported knowledge management activities.     

Reducing the Health and Digital Divides: A Model for Using Community‐Based Participatory Research Approach to E‐Health Interventions in Low‐Income Hispanic Communities

Low‐income Hispanics are the most digitally underserved population in the U.S. This article examines the potential of community‐based participatory research approach to e‐health to decrease the disparities in access to technology and health information in low‐income Hispanic communities. To demonstrate this framework, we describe the process of designing a community‐based e‐health intervention to increase knowledge and parental self‐efficacy in coping with young children's mental health problems including mental health service utilization. Our model incorporates utilizing promotoras de salud (lay community health educators) and community media principles to create the content of e‐health interventions and train community members in using the technology. This case study illustrates the processes involved in using this approach, barriers for participatory e‐health interventions in bridging the Digital Divide, and lessons learned.     

A review of medical error reporting system design considerations and a proposed cross-level systems research framework

OBJECTIVE: To review the literature on medical error reporting systems, identify gaps in the literature, and present an integrative cross-level systems model of reporting to address the gaps and to serve as a framework for understanding and guiding reporting system design and research. BACKGROUND: Medical errors are thought to be a leading cause of death among adults in the United States. However, no review exists summarizing what is known about the barriers and facilitators for successful reporting systems, and no integrated model exists to guide further research into and development of medical error reporting systems. METHOD: Relevant literature was identified using online databases; references in relevant articles were searched for additional relevant articles. RESULTS: The literature review identified components of medical error reporting systems, error reporting system design choices, barriers and incentives for reporting, and suggestions for successful reporting system design. Little theory was found to guide the published research. An integrative cross-level model of medical error reporting system design was developed and is proposed as a framework for understanding the medical error reporting literature, addressing existing limitations, and guiding future design and research. CONCLUSION: The medical error reporting research provides some guidance for designing and implementing successful reporting systems. The proposed cross-level systems model provides a way to understand this existing research. However, additional research is needed on reporting and related safety actions. The proposed model provides a framework for such future research. APPLICATION: This work can be used to guide the design, implementation, and study of medical error reporting systems.     

Development of a method for evaluating accessibility of medical equipment for patients with disabilities

ObjectiveThe purpose of this study was to develop a method for evaluating accessibility of medical equipment for patients with disabilities.MethodsThe researchers reviewed videotapes of patient-participants with various physical and sensory disabilities using different types of medical equipment. For each of 11 videotapes, four observers independently identified and documented access and safety barriers, such as physical, sensory, cognitive, and environmental barriers. Inter-observer variability for identifying barrier presence was assessed with kappa statistics for pairs of observers.ResultsA list of 10 access and safety barriers was developed through an iterative consensus process, which identified design features of medical equipment that presented difficulties for participants with disabilities. The list is useful for identifying and categorizing accessibility problems found in equipment. While reliability of barrier identification was substantial or moderate for some barriers, reconciliation of barrier events identified by multiple video observers is recommended for optimal results.     

A collaborative methodology for tacit knowledge management: Application to scientific research

Tacit knowledge, which refers to the know-how, is critical to understand and reuse since it is located in the human heads. It represents the foremost element for human and team evaluation. Seeking for tacit knowledge is achieved only by communicating with the concerned persons, which makes losing it axiomatic if people leave their work without documenting their know-how. Thus, providing a collaborative environment based on a common conceptualization of the domain to formalize the experts’ knowledge and to share their outcomes is required. However, some barriers pertaining to cultural and social factors such as personality traits impede capturing the conceptual model. To cope with these issues, we have proposed a generic two-step methodology that copes with human barriers when capturing the domain experts’ tacit knowledge, their skills, and seeds terms in order to converge to a common knowledge representation. Considering the scientific research management as a use case, we followed the proposed methodology to formalize our scientific research knowledge in the context of network and communication research field. Based on the generated ontology, we have developed a semantic web platform that allows collaboratively annotating experts’ knowledge in a computer interpretable format that can be shared and reused by human and machines. Our evaluation is based on end users’ quality of experience and feedbacks.     

Assessing users'' product-specific knowledge for personalization in electronic commerce

While many electronic commerce (EC) companies are adopting one-to-one marketing approaches using various personalization technologies to make their products and services unique for the purpose of attracting and retaining customers and improving their completion edges in the EC ecosystem, which, nevertheless, has low entrance barriers for new players to join and further intensify the competition, none or few of them consider a fundamental issue—the user's product-specific knowledge. Our research proposed to add this new domain of the customer's knowledge on appropriate target products into the personalization process as a part of the overall EC strategy for businesses. In this paper, we present our initial design for assessing the user's product-specific knowledge using the proposed innovative method for detecting it directly in a non-intrusive way without asking users to answer or fill out any types of questionnaires. Our method is based on customer's on-line navigation behaviors by analyzing their navigation patterns through pre-trained artificial neural networks. An empirical study designed for a case of EC store selling digital cameras was conducted in our research to prove the concept, and a good preliminary result was derived from the study.

For the purpose of comparing the performances between the conventional approach of using questionnaire and the proposed innovative approach of navigation pattern mining, a questionnaire based approach for evaluating the user's product-specific knowledge was designed and incorporated into our knowledge level assessment system (KLAS). Our study result shows that although the pure questionnaire-based KLAS is intrusive and may not be accepted by some users, for those users willing to complete the questionnaire, the proposed navigation pattern approach can be combined with the questionnaire-based approach to create a hybrid KLAS which has a significantly improved accuracy rate in detecting the customer's product knowledge level.     

Information Extraction and Knowledge Acquisition from Texts Using Bilingual Question–Answering

A novel approach is introduced in this paper for the implementation of a question–answering based tool for the extraction of information and knowledge from texts. This effort resulted in the computer implementation of a system answering bilingual questions directly from a text using Natural Language Processing. The system uses domain knowledge concerning categories of actions and implicit semantic relations. The present state of the art in information extraction is based on the template approach which relies on a predefined user model. The model guides the extraction of information and the instantiation of a template that is similar to a frame or set of attribute value pairs as the result of the extraction process. Our question–answering based approach aims to create flexible information extraction tools accepting natural language questions and generating answers that contain information extracted from text either directly or after applying deductive inference. Our approach also addresses the problem of implicit semantic relations occurring either in the questions or in the texts from which information is extracted. These relations are made explicit with the use of domain knowledge. Examples of application of our methods are presented in this paper concerning four domains of quite different nature. These domains are: oceanography, medical physiology, aspirin pharmacology and ancient Greek law. Questions are expressed both in Greek and English. Another important point of our method is to process text directly avoiding any kind of formal representation when inference is required for the extraction of facts not mentioned explicitly in the text. This idea of using text as knowledge base was first presented in Kontos [7] and further elaborated in [9,11,12] as the ARISTA method. This is a new method for knowledge acquisition from texts that is based on using natural language itself for knowledge representation.     

Domains and context: First steps towards managing diversity in knowledge

Despite the progress made, one of the main barriers towards the use of semantics is the lack of background knowledge. Dealing with this problem has turned out to be a very difficult task because on the one hand the background knowledge should be very large and virtually unbound and, on the other hand, it should be context sensitive and able to capture the diversity of the world, for instance in terms of language and knowledge. Our proposed solution consists in addressing the problem in three steps: (1) create an extensible diversity-aware knowledge base providing a continuously growing quantity of properly organized knowledge; (2) given the problem, build at run-time the proper context within which perform the reasoning; (3) solve the problem. Our work is based on two key ideas. The first is that of using domains, i.e. a general semantic-aware methodology and technique for structuring the background knowledge. The second is that of building the context of reasoning by a suitable combination of domains. Our goal in this paper is to introduce the overall approach, show how it can be applied to an important use case, i.e. the matching of classifications, and describe our first steps towards the construction of a large scale diversity-aware knowledge base.     

Acceptance of Health-Related ICT among Elderly People Living in the Community: A Systematic Review of Qualitative Evidence

There are a growing number of seniors and a growing need for health-related ICT (Information and Communication Technology) solutions to allow seniors to live independently in their own homes and communities. We need to have a better understanding of how and why seniors use or do not use health-related ICT in such settings so we can improve our solutions. In order to synthesize existing knowledge, we did a systematic literature review using Scopus and PubMed. We searched for both review articles and primary qualitative studies. Eleven review articles and 31 primary research articles were included in the study. We structured our findings using the UTAUT2 acceptance model developed by Venkatesh et al. Our findings show that seniors want health-related ICT that gives them independence, safety, and security, allows them to socialize and manage their own health, and helps them in their daily activities. They need to easily get help if they have problems using services, get tailored training, and get help during use. Lack of privacy and safety and stigma are some of the reported barriers. Health-related ICT at home is different than both consumer and institutional ICT. We need more research in order to develop a specialized and operationalized acceptance model for health-related ICT use among seniors. Our mapping to UTAUT2 is a step in this direction and suggests a possible specialization of this model.     

An organizational learning perspective on the assimilation of electronic medical records among small physician practices

Small physician practices play an essential role in the healthcare delivery system but are least likely to adopt health information technologies such as electronic medical records (EMRs). Factors contributing to low adoption include investment cost, productivity loss, and lack of financial incentives. However, these factors do not explain why some small practices, which face similar challenges nonetheless assimilate EMRs, while others do not. We investigated the assimilation of EMRs from the theoretic perspective of organizational learning in a survey of small physician practices and evaluated whether characteristics associated with organizational learning barriers are related to EMR assimilation. We found that learning-related scale, related knowledge, and diversity were positively associated with small physician practices' stage of assimilation of EMR technology. Our findings suggest that some small practices are able to overcome the substantial learning barriers presented by EMRs but that others will require support to develop sufficient learning capacity. We consider implications for practice from this research and areas requiring further research.     

An analysis of the results of the inductive formation of diagnostic medical knowledge databases

This paper proposes a problem-oriented method for the objective formation of easily interpretable knowledge databases for intelligent systems. We describe the InForMedKB software complex, which is designed for the inductive formation of medical diagnostics knowledge databases; it was used to perform the proposed method. Expert analysis of the results of using the developed software complex, viz., the inductively formed Acute Appendicitis database of medical diagnostic knowledge for a mathematical dependence model with parameters, which is near real-life ontology of medical diagnostics, is given.     

New Visual Invariants for Terrain Navigation Without 3D Reconstruction

For autonomous vehicles to achieve terrain navigation, obstacles must be discriminated from terrain before any path planning and obstacle avoidance activity is undertaken. In this paper, a novel approach to obstacle detection has been developed. The method finds obstacles in the 2D image space, as opposed to 3D reconstructed space, using optical flow. Our method assumes that both nonobstacle terrain regions, as well as regions with obstacles, will be visible in the imagery. Therefore, our goal is to discriminate between terrain regions with obstacles and terrain regions without obstacles. Our method uses new visual linear invariants based on optical flow. Employing the linear invariance property, obstacles can be directly detected by using reference flow lines obtained from measured optical flow. The main features of this approach are: (1) 2D visual information (i.e., optical flow) is directly used to detect obstacles; no range, 3D motion, or 3D scene geometry is recovered; (2) knowledge about the camera-to-ground coordinate transformation is not required; (3) knowledge about vehicle (or camera) motion is not required; (4) the method is valid for the vehicle (or camera) undergoing general six-degree-of-freedom motion; (5) the error sources involved are reduced to a minimum, because the only information required is one component of optical flow. Numerous experiments using both synthetic and real image data are presented. Our methods are demonstrated in both ground and air vehicle scenarios.     

Engineering microfluidic papers: effect of fiber source and paper sheet properties on capillary-driven fluid flow

In the present study, we introduce a novel approach to control and modulate fluid transport inside microfluidic papers using lab-engineered paper sheets. Lab-sheets consisting of different fiber sources (eucalyptus sulfate and cotton linters pulp) and varying porosities were designed and further modified with small millimeter-scaled channels using hydrophobic barriers consisting of fiber-attached, hydrophobic polymers. The capillary-driven transport of an aqueous solution was monitored visually, and the influence of parameters such as fiber source, paper grammage, and channel width on the flow rates through the channel was investigated. The experimental results were compared with those obtained with commercially available filter papers. Our findings suggest that accurate control of fluid transport processes with standard filter papers is complex. Additionally, if the channel width is smaller than the mean fiber length, flow rates become dependent on the geometric parameters of the channel because of the formation of dead-end pores at the hydrophobic barriers. Finally, control of the paper sheets porosity, by varying the fiber density of the lab-made paper, affords the fabrication of chemically identical sheets whereby capillary flow is largely influenced and can be modulated accordingly by simple papermaking processes.     

Mining knowledge demands from information flow

Among a collaborative team, members usually come from diverse disciplines, and their demands for knowledge are also different from each other. Information flow is a type of collaborative process, which exists behind every collaborative team. This paper is concerned with how to obtain team members’ knowledge demands from the information flow. Firstly, the knowledge demands model is defined. Based on the model of knowledge demands and information filtering technologies, some approaches for mining demands from information flow are proposed. This study on the knowledge demand mining can pave the way for developing knowledge recommender systems, which can recommend proper knowledge to proper team members with a collaborative team.     

A practical data-flow verification scheme for business processes

Data in business processes becomes more and more important. Current standard languages for process modeling like BPMN 2.0 which include the data flow reflect this. Ensuring the correctness of the data flow in processes is challenging. Model checking, i.e., verifying properties of process models, is a well-known technique to this end. An important part of model checking is the construction of the state space of the model. However, state-space explosion typically is in the way of an effective verification. We study how to overcome this problem in our context by means of reduction. More specifically, we propose a reduction on the level of the process model. To our knowledge, this is new for the data-flow analysis of processes. The core of our approach are so-called regions of the process model that are relevant for the verification of properties describing the data flow. Non-relevant regions are candidates for reduction of the process model, yielding a smaller state space. Our evaluation shows that our approach works well on industrial process models.