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The paper seeks to improve the understanding of knowledge identification and management in product design by studying designers' cognition and behavior.

Knowledge management becomes an essential process in product design. However, most organizations and designers do not understand what knowledge should and can be managed. Little research is focused on studying the cognitive and social psychological factors within knowledge activities. This paper is mainly focused on knowledge issues in product design. This study focuses on the internal human activities and explores knowledge management research utilizing a human factors perspective.

In this paper knowledge in product design is defined; knowledge in product design is identified and classified based on design decision‐making processes. Furthermore, how to improve the knowledge management process in collaborative decision making is presented.

This study uses an experimental approach and hopefully the research can therefore be generalized to other situations.

This study provides guidelines for information technology support for knowledge management in product design.

Knowledge used in product design is identified and classified. The paper explores knowledge management research by analyzing human activity, in combination with the study of management and engineering technologies.

The purpose of this research is to aim to improve the cognitive understanding of knowledge processing and provide a cognitive knowledge modeling method in product design.

In this paper, a cognitive model of knowledge processing is described. A cognitive knowledge modeling method is presented. Suggestions on cognitive support for knowledge based systems are provided.

There is often a fundamental mismatch between the way human process knowledge and the way it is processed by technology for supporting product design. It is necessary to develop tools, methods and technology which integrate seamlessly with the design process. This study focuses on the internal human activities and explores knowledge management research from a human factors perspective. Cognitive knowledge modeling will result in a natural integration of knowledge‐based systems into the design process.

This study uses an experimental approach and hopefully the research can therefore be generalized to other situations.

This study provides guidelines for cognitive support for knowledge‐based systems.

Cognitive knowledge processing is described and a cognitive knowledge modeling method is presented. The paper explores knowledge management research by analyzing human activities, in combination with the study of management and engineering technologies.

The process of knowledge transfer under the B-O-R-N Model is based on the concepts of knowledge transfer and change of knowledge patterns to create new knowledge. It stimulates learners to learn under the process of knowledge transfer during the learning with an aim to allow learners to achieve the learning outcomes.

This study examines learning according to the B-O-R-N manual to test the effectiveness of learners’ outcomes in the domains of knowledge and learning outcomes for cognitive skills. The teaching is provided by three teachers, and the opinions of 97 sample respondents are surveyed after learning according to the B-O-R-N Model.

The effectiveness of learning outcomes in the domains of knowledge and learning outcomes for cognitive skills of the learners who were taught by different teachers was similar: the learners’ scores exceeded the set-up criteria in all aspects. Also, the learners were satisfied with the activities in the B-O-R-N Model at the highest level, which demonstrated that the knowledge transfer during the learning activities was an important factor which affected the learning outcomes of the undergraduate computer learners effectively.

The knowledge management which happens during the B-O-R-N Model process is the creation of the new learning environment which allows learners to learn together and use mixed skills that can be applied in real situations. It encourages learners to have sustainable learning and the potential to develop themselves, resulting in the development of the economy and a knowledge-based society, as well as the enhancement of the country’s competitiveness.

Internet of Things (IoT) interconnects many heterogeneous devices to each other, collecting and processing large volumes of data for decision making without human intervention. However, the information security concern it brings has attracted quite a lot of attention, and, at this stage, the smart step would be to analyze the security issues of IoT platform and get to the state of readiness before embarking upon this attractive technology. The purpose of this paper is to address these issues.

IoT risk assessment through the application of the analytical hierarchy process (AHP), a favorite multi-criteria decision making technique, is proposed. The IoT risks are prioritized and ranked at different layers, before which a well-defined IoT risk taxonomy is defined comprising of 25 risks across six layers of the IoT model for developing control and mitigation plans for information security of IoT.

People and processes layer, network layer and applications layer are the top three critical layers with risks like the lack of awareness, malware injection, malicious code injection, denial of service and inefficient policies for IoT practice get the highest priority and rank. Pareto analysis of the overall risk factors revealed that the top ten factors contribute to 80 percent of the risks perceived by information security experts.

The study focuses only on certain predefined constructs or layers of the IoT model traced from legacy studies. It is essential to re-look these constructs on a timely basis to prolong the results’ validity. The study’s empirical scope is confined only to the risk perception of select IoT experts and does not encompass a broader segment of the IoT ecosystem. Therefore, the risks assessment may not be sweeping to a bigger audience.

The study implications are two-fold: one it consolidates the earlier siloed works to intensify the need for risk assessment in the IoT domain, and second the study brings yet another contextual avenue of extending the application AHP and Pareto principle combination. The paper also draws specific critical organizational interventions about IoT risks. A comprehensive approach to prioritizing and ranking IoT risks are present in this research paper.

The contribution of this study to the benchmarking of IoT risk assessment is two-fold. One, a comprehensive risk assessment taxonomy is proposed, and two, the risks are prioritized and ranked to give a convincing reference for the organizations while making information security plans for IoT technology.

This paper aims to investigate whether and how enterprise social media (ESM) affordances affect employee agility.

Adopting self-determination theory (SDT), this study examines a model in which the four ESM affordances (i.e. visibility, association, editability and persistence) impact employee agility through the three basic psychological needs satisfaction (i.e. perceived autonomy, perceived relatedness and perceived competence) of employees. Mplus 7.4 was used to analyze survey data gathered from 304 employees who used ESM in the workplace.

The authors’ findings show that all four ESM affordances contribute to perceived relatedness and perceived competence; visibility and association affordances also have positive impacts on perceived autonomy; and all three psychological needs satisfaction positively impact employee agility.

First, this study adapted SDT to explore how ESM influences employee agility. Second, this study enriches the relevant research on the antecedents of employee agility and also provides new evidence and theoretical support for employee agility. Third, this study effectively expands the antecedents and outcomes of employee basic psychological needs satisfaction in the domain of ESM and agility.