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The purpose of this research is to identify motivators (i.e. self-efficacy, perceived behavioural control and perceived benefits) and inhibitors (i.e. perceived cost and anxiety) that affect behavioural intentions to book hotel rooms using smartphones.

Utilising survey data collected from online consumers who have booked hotels in London, two stages of structural equation modelling were applied to estimate the proposed model.

The results of this research indicate that perceived behavioural control appears to be the core motivator for the use of smartphones to book a hotel with perceived benefits, whereas anxiety plays a negative role in leading to mobile booking behaviours. It is also identified that self-efficacy indirectly influences intentions to reserve hotel accommodation.

This study suggests that hospitality marketers should simplify the mobile purchasing process to enhance self-confidence in controlling the system during transactions, educate current and potential online consumers to become aware of the competitive benefits of using smartphones and create alliances with credit card companies to relieve anxiety when users are asked to provide personal or banking information.

In light of the substantial literature regarding the adoption of technology in terms of user experience (i.e. TAM), this study integrates two theoretical foundations of understanding consumer behaviours (i.e. a concept of consumer values and theory of planned behaviour) to assess motivators and inhibitors in behaviours related to booking hotel accommodation via smartphones.

This paper aims to present a one-shot gesture recognition approach which can be a high-efficient communication channel in human–robot collaboration systems.

This paper applies dynamic time warping (DTW) to align two gesture sequences in temporal domain with a novel frame-wise distance measure which matches local features in spatial domain. Furthermore, a novel and robust bidirectional attention region extraction method is proposed to retain information in both movement and hold phase of a gesture.

The proposed approach is capable of providing efficient one-shot gesture recognition without elaborately designed features. The experiments on a social robot (JiaJia) demonstrate that the proposed approach can be used in a human–robot collaboration system flexibly.

According to previous literature, there are no similar solutions that can achieve an efficient gesture recognition with simple local feature descriptor and combine the advantages of local features with DTW.

Health-related online fake news (HOFN) has become a major social problem. HOFN can lead to the spread of ineffective and even harmful remedies. The study aims to understand Internet users' responses to HOFN during the coronavirus (COVID-19) pandemic using the protective action decision model (PADM).

The authors collected pandemic severity data (regional number of confirmed cases) from government websites of the USA and China (Studies 1 and 2), search behavior from Google and Baidu search engines (Studies 1 and 2) and data regarding trust in two online fake news stories from two national surveys (Studies 2 and 3). All data were analyzed using a multi-level linear model.

The research detected negative time-lagged relationships between pandemic severity and regional HOFN search behavior by three actual fake news stories from the USA and China (Study 1). Importantly, trust in HOFN served as a mediator in the time-lagged relationship between pandemic severity and search behavior (Study 2). Additionally, the relationship between pandemic severity and trust in HOFN varied according to individuals' perceived control (Study 3).

The authors' results underscore the important role of PADM in understanding Internet users' trust in and search for HOFN. When people trust HOFN, they may seek more information to implement further protective actions. Importantly, it appears that trust in HOFN varies with environmental cues (regional pandemic severity) and with individuals' perceived control, providing insight into developing coping strategies during a pandemic.

The purpose of constructing the technology/function matrix is to analyze the patents in the target domain. The extraction of technology words is an important part of the construction of technology/function matrix. This algorithm is used to solve the problem of low efficiency of traditional Chinese process patents technology words extraction.

The authors propose a Chinese process patents technology words extraction method based on the improved term frequency–inverse document frequency (TF-IDF) algorithm to help technicians obtain the technology words in the target domain. According to the characteristics of Chinese process patents technology words, the TF value of candidate technology words is divided into four parts, and the corpus of IDF value calculation of candidate technology words is selected.

Through the test of Chinese process patents in the domain of path planning, this study shows that the method is feasible and practical. It can help users quickly and accurately obtain the technology words of Chinese process patents in the target domain.

With the increasing number of patents on the network-based patent information platform, patent analysis of massive Chinese process patents has become a research focus. The method proposed in this paper can facilitate users to extract technology words from massive Chinese process patents for patent analysis.

This paper aims to improve the efficiency of Chinese process patents technology words extraction. The authors hope that the proposed method can reduce the labor and time cost of Chinese process patents technology words extraction.

The construction industry has experienced an irreversible digital transformation to smart construction. Many countries have published supporting policies to encourage the development of smart construction. However, there is no universally valid approach. This paper thus aims to evaluate smart construction policies issued by 24 pilot cities in China and identify applicable policy tools and their impact.

This paper collected 33 governmental documents on smart construction through the official websites in China. Different policy tools were classified into supply-side, demand-side and environment-side categories. The supporting policies of smart construction development in pilot cities were quantitatively evaluated by using a policy modeling consistency index (PMC-index) model.

Supply-type and environment-type policy instruments were used more frequently than demand-type policies in 24 pilot cities. Most of the 24 pilot cities had an evaluation of PMC-index over 8, realizing the consistency of smart construction policies. Eight pilot cities had an evaluation of PMC-index of 6–7.99, realizing acceptable consistency. Only Foshan City has an evaluation of PMC-index below 4, which may reflect a poor consistency of policy implementation. The paper proposes consistencies of smart construction policies of 24 pilot cities and valid policy instruments, including the presale of commercial residential buildings, additional bonus points in the tendering process and cooperating with multiple departments when promoting smart construction.

This paper contributes to expanding policy evaluation studies in the smart construction field and provides concrete suggestions for policymakers to formulate more effective and specific policies and strategies for the development of smart construction.

In the present era of Industry 4.0, the manufacturing automation is moving toward mass production and mass customization through human–robot collaboration. The purpose of this paper is to describe various human–robot collaborative (HRC) techniques and their applicability for various manufacturing methods along with key challenges.

Numerous recent relevant research literature has been analyzed, and various human–robot interaction methods have been identified, and detailed discussions are made on one- and two-way human–robot collaboration.

The challenges in implementing human–robot collaboration for various manufacturing process and the challenges in one- and two-way collaboration between human and robot are found and discussed.

The authors have attempted to classify the HRC techniques and demonstrated the challenges in different modes.

The purpose of this paper is to review maintenance practices, tools and parameters for marine mechanical systems that can be classified as plant, machinery and equipment (PME). It provides an insight for the maintenance crew on which maintenance parameters and practices are critical for a given PME systems.

The review paper characterizes the various maintenance parameters and maintenance practices used onshore and offshore for PME and identifies the possible gaps.

A variety of maintenance techniques are being used in the marine industry such as corrective maintenance, preventive maintenance and condition-based maintenance. As marine vehicles (MV) get older, the most important maintenance parameters become maintenance costs, reliability and safety. Maintenance models that have been developed in line with marine mechanical systems have been validated using a single system, whose outcome could be different if another PME system is used for validation.

There is a limited literature on MV maintenance parameters and maintenance characterization regarding mechanical systems. The maintenance practices or strategies of marine mechanical systems should be based on maintenance parameters that suit the marine industry for a given PME.

Based on the available literature, the paper provides a variety of maintenance framework, parameters and practices for marine mechanical systems. The paper further gives an insight on what maintenance parameters, strategies and platforms are given preference in the shipping industry.