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About 70% of all aircraft accidents are caused by human–machine interaction, thus identifying and quantifying performance shaping factors is a significant challenge in the study of human reliability. An information flow field model of human–machine interaction is put forward to help better pinpoint the factors influencing performance and to make up for the lack of a model of information flow and feedback processes in the aircraft cockpit. To enhance the efficacy of the human–machine interaction, this paper aims to examine the important coupling factors in the system using the findings of the simulation.

The performance-shaping factors were retrieved from the model, which was created to thoroughly describe the information flow. The coupling degree between the performance shaping factors was calculated, and simulation and sensitivity analysis are based on system dynamics.

The results show that the efficacy of human–computer interaction is significantly influenced by individual important factors and coupling factors. To decrease the frequency of accidents after seven hours, attention should be paid to these factors.

The novelty of this work lies in proposing a theoretical model of cockpit information flow and using system dynamics to analyse the effect of the factors in the human–machine loop on human–machine efficacy.

Occupant feedback is crucial for healthy, comfortable and productive offices. Existing facility management (FM) systems are limited in effective use of occupant feedback, as they fail to collect the vital contextual information (e.g. related building element, space) associated with the feedback. The purpose of this study is to formalise the contextual information requirements for structured collection of occupant feedback for rapid diagnosis and resolution of problems and integrating occupant feedback with building information modelling (BIM) for making use of its visualisation and analysis capabilities, and eventually for effective use of occupant feedback in FM operations.

A mixed-methods approach was conducted in four steps: (1) identifying occupant feedback types (e.g. echo in meeting room) in office buildings, (2) examining the current practice in collecting and processing occupant feedback via use cases, (3) determining the contextual information requirements via expert interviews and (4) validation of the information requirements via a BIM-integrated prototype.

The findings present the contextual information requirements for 107 occupant feedback types grouped under thermal comfort, indoor air quality, acoustic comfort, visual comfort, building design and facility services.

Feedback-specific contextual information items enable structured data collection and help to avoid missing data and minimise the time lost in manual data entry and recursive interaction with the occupants during FM operations.

The contextual information requirements determined are expected to enhance occupant satisfaction and FM performance in office buildings by better use of the occupant feedback and integration into BIM-enabled FM and can be extended to other building types in future studies by using the proposed methodology.

Building information modeling (BIM) is a growing technology and methodology for project design in the construction industry. However, when the project design team designs with BIM in a free-form manner (without a qualified instructor), it is not clear how behavior or trust might develop among project team members, nor if there are variables that might influence the improvement of such collaboration.

A sample of 92 responses was obtained from managers of project design firms in the architecture, engineering and construction (AEC) sector. The questionnaire data were analyzed using partial least square structural equation modeling (PLS-SEM).

This paper provides an explanation, from a happiness management perspective, to reflect on the importance of establishing policies to enhance effective communication between project team members in BIM design, as it improves trust between team members and their collaborators, developing the overall satisfaction of all the agents involved in the project.

The researchers suggest that there is a gap in the literature on how effective communication influences the implementation of BIM methodology.

Properly allocating an organization's activities within a building is vital to reducing the relational complexity arising from process–environment interactions. Multiple relationships are mapped, and certain interferences are only identified after these have been processed. The method/software employed for this task is Mapping Activity Environment Allocation (MAEA). However, data input and interpretation of results depend on the usability conditions of the organization's agents. This paper presents MAEA's usability test results.

Test sessions and interviews were carried out with seven agents registered at a University Hospital. Participants were instructed to think aloud during its use, and immediately afterward, responded to semi-structured interviews. Test sessions were audio recorded and screen captured.

Participants found the software easy to use and pointed out valuable implications for professional and academic use. In addition to relationship, priority and parallelism data, customized visualizations were created, including organizational charts, flowcharts and activity flow routes on the floor plan.

MAEA's simplicity allows non-designers to conduct evidence-based assessments and decisions. It allows designers to test their proposals during the programming and outline proposal stages.

A more detailed definition of design requirements from the beginning increases the conditions to successfully achieve project goals.

The ability to map the allocation of activity-spaces in the pre-design phase of building architecture allows for early identification of interactions, aiding in the development of more robust project requirements during programming.

Building information modelling (BIM) claims to be spearheading the modern technological revolution in the global construction industry. While scholars have emphasised the cruciality of BIM, associated costs have been identified as one of the major barriers to successful BIM implementation, as is the case in Sri Lanka. Besides, lean principles (LPs) are known for increasing efficiency, quality and eliminating waste, thereby reducing overall costs. Hence, this research aims at addressing the BIM implementation barrier associated with costs by applying suitable LP, enhancing overall value by minimising value-insignificant activities.

The study adopted a qualitative research approach. 10 experts with expertise in both BIM and LP were targeted for the primary data collection through semi-structured interviews. The collected data were analysed using manual content analysis.

Research findings discovered the cost centres that can be applied to the LPs and the effective LPs that can be applied with the cost centres of BIM implementation. The theoretical implication of the study is to provide insights into a potential application of LP for BIM cost centres, whereas practical consequences include the identification of LP's potential to minimise BIM cost centres, ergo, achieving a successful BIM implementation.

This study will be the first of its kind in the Sri Lankan construction industry, intending to apply LP with BIM implementation cost centres to achieve a successful implementation. This research also has paved the way forward for further research on the application of both the BIM and LP concepts for similar construction industries in developing countries across the world and in addressing other BIM implementation barriers.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

Recent studies on the securities market’s differential pricing of earnings components have shown that cash flow from operations is more highly valued than total accruals and that moderate cash flow from operations has higher valuation than extreme total accruals. An interesting question that follows is whether these findings hold regarding the differential valuations of cash flow and current accruals. This study aims to extend prior research by addressing this issue in two ways. First, the authors examine the incremental information content of cash flow from operations beyond working capital from operations. Second, the authors assess the effect of extreme working capital from operations on the incremental information content of cash flow from operations. This study aims to extend prior research by addressing this issue in two ways.

This study adopts market-based accounting research to test its hypotheses and to achieve its objectives. Specifically, this study uses statistical associations between accounting data and stock returns to examine the incremental information content (value relevance) of cash flow and working capital from operations and the effect of extreme working capital from operations on the incremental information content of cash flow.

The results show that cash flow from operations is not more highly valued than current accruals (both being valued equivalently). However, moderate cash flow from operations has higher valuation than extreme current accruals (each is valued differently). Overall, these research findings indicate that cash flow becomes more important for valuation as accruals get “extreme”.

As accruals are unlikely to persist to be permanent across the years, these results can be interpreted as indicating that cash flow and accruals information are used jointly by investors, with one being more important than the other depending on the relative “extremeness” of each. Therefore, both are of value to the investor and both should be reported.

The paper contributes to the UK research on determining the preferred level of disaggregation of earnings components, i.e. operating cash flow, current accruals and non-current accruals. This would help investors to improve their investment and credit decisions.

User discontinuance on short-video platform has become increasingly prevalent in recent years. Short-video discontinuance refers to reduced use, controlled use or suspended use of the short-video platform. In this study, we examined factors associated with discontinuance behavior on short-video platform.

From the perspective of stressor–strain–outcome (SSO), we put forward a theoretical model integrating perceived information overload and perceived system feature overload (stressors), dissatisfaction (psychological strain), flow experience and regret to explain discontinuance behavior on short-video platform (behavioral outcome). We collected 482 survey data from Douyin users in China, and empirically examined the proposed research model via Partial least squares structural equation modeling (PLS-SEM) technique.

Our results demonstrated that perceived system feature overload exerts a positive effect on perceived information overload. Perceived system feature overload has a stronger influence on dissatisfaction than perceived information overload. Regret increases user dissatisfaction, while flow experience decreases user dissatisfaction. We also discovered that dissatisfaction and regret have significant positive effects on discontinuance behavior. Interestingly, flow exerts no significant influence on discontinuance behavior.

This study enriches the body of knowledge on social media discontinuance by revealing the interaction and effects of flow experience, dissatisfaction and regret on discontinuance. This study also extends the understanding on the complex role of flow experience in leading to social media discontinuance. Additionally, this study deepens the research on the interaction between perceived system feature overload and perceived information overload as well as their different influences on negative emotion.

This study aims to investigate the impact of digital transformation on supply chain resilience. Additionally, the paper examines the mediating effect of supply chain process integration as well as the moderating effect of environmental uncertainty in the relationship between digital transformation and supply chain resilience.

Drawing on digital empowerment theory, this study proposes a theoretical model. Using survey data collected from 216 enterprises in China, the study employs structural equation modeling to validate the theoretical model.

The results reveal that digital transformation has a significant impact on supply chain resilience. Three dimensions of supply chain process integration, namely, information flow integration, physical flow integration, and financial flow integration mediate the relationship between digital transformation and supply chain resilience. In addition, environmental uncertainty including market uncertainty and technology uncertainty positively moderates the relationship between digital transformation and supply chain resilience.

First, this paper provides empirical evidence on both the direct and indirect effects of digital transformation on supply chain resilience. Second, this paper enriches the understanding of how supply chain integration impacts supply chain resilience in the digital transformation era by adopting a more granular perspective of process integration rather than broad external and internal integrations. Furthermore, this paper extends the knowledge of the role of external environment in digital transformation and supply chain risk management by examining the moderating effects of market uncertainty and technology uncertainty.