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The success rate of design-build (D-B) implementation in Malaysia’s private construction projects is low compared to the nation’s public projects. Thus, the purpose of this paper is to investigate the critical success factors (CSFs) for D-B implementation in Malaysian public construction projects.

To achieve the research objectives, 111 questionnaire survey responses from construction-related professionals were collected and analysed using multivariate analysis, including t-test, analysis of variance (ANOVA) and factor analysis.

The results indicate that while the client’s briefing effectiveness remained the top CSF among many nations, the other top CSFs in Malaysia D-B construction projects vastly differed compared to those countries. Moreover, the underlying components for successful D-B projects in Malaysia include the project management team, leader competency and “stakeholder” management.

This is one of the first studies that identify the CSFs for D-B implementation in the Malaysian construction industry. The outcomes provide a valuable reference and resource for academic scholars and construction practitioners to increase D-B implementation in the Malaysian private sector.

Design-Build (DB) is known as the alternative for Design-Bid-Build in the Malaysian construction industry. For DB projects, it is critical to adopt effective decision support tool to ensure the execution of a systematic decision-making technique. This study aimed to examine the impact of a decision support tool for novice decision makers to reject or adopt DB for their construction projects.

Literature review and qualitative input from experts identified several key-selection factors pertaining to critical success factors and design-build drivers. This resulted in the development of Decision Support Tool for Design-Build (DST-DB). A quasi-experiment, which involved 382 novice decision makers in the construction industry, was conducted to test the DST-DB quantitatively. The participants were required to compare two construction projects using DST-DB and traditional decision-making methods. Multivariate analysis was performed to analyse all collected data.

The quasi-experiment data suggests that DST-DB enables significantly higher usability, likelihood, precision, confidence and satisfaction rate when compared to the traditional decision-making process. The pre- and post-surveys indicated that the DST-DB is effective in improving decision-making performance through selection factors of client-briefing, maximised resources and sharing expertise. The participants also agreed that DST-DB is easy to use and helps them to gain better understanding of the decision-making process for construction projects.

This research contributes to the existing body of knowledge through the impact of DST on the decisions of novices. The novice decision makers found that DST-DB is practically adaptable and comparatively effective for decision-making process than traditional decision-making methods. This contributes to the practical application of construction companies to provide DST-DB training to the fresh graduate employees to enhance their competencies in the decision-making process.

The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station.

The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced.

The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation.

The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

This study aims to study the mechanisms and conditions of users' intention to continue to use online health platforms from an information technology (IT) affordance perspective.

b This research proposes that a critical affordance effect on an online health platform, users' intention to continue the use of the platform, is affected by five platform affordances via two actualized affordances (i.e. perceived benefits (PBs) and online engagement (OE)). Perceived health threat moderates the effect generated by affordance actualization. A dataset involving 409 users from the “Ping An Health” platform was collected through an online survey and analyzed to validate the research hypotheses.

The data analysis results confirm that the proposed online health platform affordances affect users' PBs and OE, which influence users' intentions to continue using the platform. Perceived threats (perceived vulnerability (PVU) and perceived severity (PSE)) moderate the relationship between PBs and continuance intention (CI) and between OE and CI.

The research provides important recommendations for online health platform designers to develop IT affordances that can support users' needs for healthcare services.

Limited studies investigated why users continue participating in online diagnosis and treatment. This study provides a new perspective to expand the affordance framework by combining technology features and user health behavior. The study also emphasizes the importance of perceived threats in IT use.

The strength of printed parts by application of fused deposition modeling (FDM) has been broadly studied through experimental methods. However, constitutive behaviors of the printed parts in theory are still unclear. Therefore, this paper aims to focus on building an elasto-plastic model of the printed parts to reveal the constitutive behavior.

An elasto-plastic constitutive model that considers anisotropic characteristics is proposed. Tensile tests are performed for parameter identification by using different samples with varying printing angles. Finally, the constitutive model is completed and applied to the numerical analysis of a tensile procedure.

The experimental study indicated that the anisotropic characteristics are significant for elastic modulus and strength of printed parts. The polar anisotropic model is suitable for describing the anisotropic behavior of parts during the elastic deformation. The Hill model is suitable to describe the yield property. The elastic modulus and yield point of parts printed in any specific orientation can be calculated using the proposed constitutive model.

A theoretical model has been developed to describe the constitutive behavior of FDM printed part. This model can precisely describe the elastic behavior and yield point of parts printed with various orientations. This model can be applied to the finite element simulation of printed structures.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Presents over sixty abstracts summarising the 1999 Employment Research Unit annual conference held at the University of Cardiff. Explores the multiple impacts of globalization on work and employment in contemporary organizations. Covers the human resource management implications of organizational responses to globalization. Examines the theoretical, methodological, empirical and comparative issues pertaining to competitiveness and the management of human resources, the impact of organisational strategies and international production on the workplace, the organization of labour markets, human resource development, cultural change in organisations, trade union responses, and trans‐national corporations. Cites many case studies showing how globalization has brought a lot of opportunities together with much change both to the employee and the employer. Considers the threats to existing cultures, structures and systems.

Prior studies have extensively explored individual examples of unethical behavior in sales organizations but focused little on repeated violation (RV) of ethical codes, particularly when managers develop salesforces. Based on social learning theory (SLT), the authors propose a multilevel model of RV antecedents and suggest that organizational influence (social cues and modeling) and individual factors (observer characteristics and behavioral outcomes) affect RV, especially with increasing recruitment of salespeople.

Using data from a leading financial company in Taiwan, the authors analyzed 1,231 records of salespeople’s misbehavior through logistic regression and average marginal effects.

Modeling in the organization (i.e. peer misconduct), observer characteristics (i.e. experience concerning job tenure and prior violations) and behavioral outcomes (i.e. information concealment violations) were all found to affect the likelihood of RV, and the interactional effect of organizational size was confirmed.

This study contributes to ethical decision-making theory by explaining aspects of RV through SLT. Its multilevel model, integrated with organizational strategy theories, adds an SLT-focused paradigm into unethical behavior research by considering vicarious learning and self-learning, alongside the reciprocal determinism of cognition, behavior, and environment.

Managers should consider socially based patterns of violation when initiating a sales business plan. The chances of RV are increased by unethical models in the organization and offenders’ potential for violations, which is reinforced by social environment.

This study clarified the key drivers of RV decision-making using SLT and identified an effective sales development strategy to maintain an ethically responsible salesforce.

This paper aims to investigate investors' willingness to use robo-advisors from customers' perspectives and analyzes the factors that drive them to use robo-advisors, including perceived usefulness and emotional response.

The authors extend the Cognition-Affect-Conation (CAC) framework to the behavioral domain of robo-advisor users on financial technology platforms and conduct an empirical study based on 248 valid questionnaires.

The authors find two types of factors driving the willingness to use robo-advisors: perceived usefulness, trust and perceived risk as external driving forces and investor sentiment as an internal driving force. Trust has a significant positive effect on willingness to use, and arousal in emotional response plays a mediating role between perceived usefulness and willingness to use.

This research provides valuable insights for financial institutions to engage in robo-advisor innovation from customers' perspectives.