Search results

Workers' unsafe behavior is the main cause of construction safety accidents, thereby highlighting the critical importance of behavior-based management. To compensate for the limitations of computer vision in tackling knowledge-intensive issues, semantic-based methods have gained increasing attention in the field of construction safety management. Knowledge graph provides an efficient and visualized method for the identification of various unsafe behaviors.

This study proposes an unsafe behavior identification framework by integrating computer vision and knowledge graph–based reasoning. An enhanced ontology model anchors our framework, with image features from YOLOv5, COCO Panoptic Segmentation and DeepSORT integrated into the graph database, culminating in a structured knowledge graph. An inference module is also developed, enabling automated the extraction of unsafe behavior knowledge through rule-based reasoning.

A case application is implemented to demonstrate the feasibility and effectiveness of the proposed method. Results show that the method can identify various unsafe behaviors from images of construction sites and provide mitigation recommendations for safety managers by automated reasoning, thus supporting on-site safety management and safety education.

Existing studies focus on spatial relationships, often neglecting the diversified spatiotemporal information in images. Besides, previous research in construction safety only partially automated knowledge graph construction and reasoning processes. In contrast, this study constructs an enhanced knowledge graph integrating static and dynamic data, coupled with an inference module for fully automated knowledge-based unsafe behavior identification. It can help managers grasp the workers’ behavior dynamics and timely implement measures to correct violations.

This study aims to explore the link between prevalent risk factors for early childhood diarrhea, including hygiene, feeding, weaning practices and maternal education and the occurrence and severity of early childhood diarrhea in Saudi Arabia.

A case-control study was conducted, involving 98 mothers from the Eastern Region of Saudi Arabia (51 cases and 47 controls). Data were collected from both hospital and community sources. The collected data were statistically analyzed and depicted using descriptive statistics and frequency tables.

Demographic data revealed that 60% of mothers were housewives, 75% had normal deliveries and all babies were full term. In the study cohort, 44% of children aged one to two years. Four domains were compared: diarrheal management, hygiene, weaning and feeding practices. Diarrheal management was suboptimal in some cases: 29% increased fluid intake, 10% maintained adequate food intake, 50% sought medical advice, 58% were familiar with oral rehydration solutions and only 37% used them. Hygiene practices were deficient, with 35% using wipes or sanitizers, 64% handwashing before feeding and 52% adhering to the recommended 10-s duration. Controls exhibited better hygiene practices. Weaning practices were generally similar, with no significant differences between the two groups.

To the best of the authors’ knowledge, this is the first study to collectively report on the risk factors linked to early childhood diarrhea in Saudi Arabia. This study yields significant insights, highlighting the crucial role of managing diarrhea, educating mothers and implementing proper household practices in impacting the occurrence and severity of this perilous ailment.

This study aimed to explore the impact of Artificial Intelligence (AI) characteristics, namely Perceived Animacy (PAN), perceived intelligence (PIN), and perceived anthropomorphism (PAI), on user satisfaction (ESA) and continuous intentions (CIN) by integrating Expectation Confirmation Theory (ECT), with a particular focus on Generation Y and Z.

Using a quantitative method, the study collected 495 data from Gen Y (204) and Z (291) respondents who were users of digital banking apps through structured questionnaires that were analysed using PLS-SEM. The latter helped investigate the driving forces of AI characteristics and user behavioural intentions as well as reveal generation-specific features of digital banking engagement.

The study revealed that PAN and PIN have significant positive effects on the anthropomorphic perceptions of digital banking apps, which in turn increases perceived usefulness, satisfaction, and continuous intentions. In particular, the influence of these AI attributes varies across generations; Gen Y’s loyalty is mostly based on the benefits derived from AI features, whereas Gen Z places a greater value on the anthropomorphic factor of AI. This marked a generational shift in the demand for digital banking services.

The specificity of Indian Gen Y and Z users defines the scope of this study, suggesting that demographic and geographical boundaries can be broadened in future AI-related banking research.

The results have important implications for bank executive officers and policymakers in developing AI-supported digital banking interfaces that appeal to the unique tastes of millennial customers, thus emphasising the importance of personalising AI functionalities to enhance user participation and loyalty.

This study enriches the digital banking literature by combining AI attributes with ECT, offering a granular understanding of AI’s role in modulating young consumers' satisfaction and continuance intentions. It underscores the strategic imperative of AI in cultivating compelling and loyalty-inducing digital banking environments tailored to the evolving expectations of Generations Y and Z.

This study builds on a conceptual model by integrating AI features – Perceived intelligence (PIN) and anthropomorphism (PAN) – while extending expectation confirmation theory (ECT) factors – interaction quality (IQU), confirmation (CON), and customer experience (CSE) – to evaluate the continued intention to use (CIU) of AI-enabled digital banking services.

Data were collected through an online questionnaire administered to 390 digital banking customers in India. The data were further analysed, and the presented hypotheses were evaluated using partial least squares structural equation modelling (PLS-SEM).

The research indicates that perceived intelligence and anthropomorphism predict interaction quality. Interaction quality significantly impacts expectation confirmation, consumer experience, and the continuous intention to use digital banking services powered by AI technology. AI design will become a fundamental factor; thus, all interactions should be user-friendly, efficient, and reliable, and the successful implementation of AI in digital banking will largely depend on AI features.

This study is the first to demonstrate the effectiveness of an AI-ECT model for AI-enabled Indian digital banks. The user continuance intention to use digital banking in the context of AI has not yet been studied. These findings further enrich the literature on AI, digital banking, and information systems by focusing on the AI's Intelligence and Anthropomorphism variables in digital banks.

Social group system and social tagging system, which leverage the psychological mechanisms underlying group influence and social tags to drive consumer behaviors, have been prevalent in the social commerce platform. However, limited studies have examined how the affordances of social group system and social tagging system influence consumers’ social shopping behavior. The purpose of this study is to examine the formation of social shopping behavior in the social commerce platform.

Combining affordance theory with dual-congruity theory, we develop a model to examine how the affordances of social group system and social tagging system influence consumers’ social shopping behavior through the underlying self-congruity and functional-congruity processes. We empirically validate the research model using a multimethod approach, including an instrument development study and a field survey study.

Our empirical findings show that social support positively influences relational identity, while it has a nonsignificant effect on social identity. Social interactivity positively influences relational identity and social identity. Furthermore, social tagging quality and social endorser credibility positively affect perceived diagnosticity and perceived serendipity. Finally, relational identity, social identity, perceived diagnosticity and perceived serendipity collectively determine consumers’ social shopping intention.

This study contributes to the theoretical understanding of social shopping in social commerce and offers practical implications for designing an effective social group system and social tagging system to boost product sales.

This study aimed to examine the research hotspots and evolution paths in the field of health information behavior (HIB) in China and abroad, and conduct comparative analysis to better understand its development trajectory globally.

A keyword search of the relevant literature included in the China National Knowledge Infrastructure (CNKI) database and Web of Science (WoS) core collection database was conducted, using the visualized analysis tool CiteSpace V for bibliometric analyses.

The common research hotspots in China and abroad can be divided into related research on HIB, research on its influencing factors and health information research. Among these, health information-seeking behavior has been the focus of domestic and foreign scholars. From the subdivision perspective, the focus of Chinese and foreign research hotspots differs. In terms of evolutionary path, the initial stage of HIB research in China and abroad revolves around health information and health information-seeking behavior, followed by the influencing factors of HIB; however, the research breakthrough point is the reverse. Then, domestic and foreign research was conducted on different types of HIBs. Regarding the selection of research objects, Chinese and foreign research objects were increasingly diversified.

This study also has several limitations. First, the literature sample only selected the literature in the WoS and CNKI databases, and there may be many HIB-related works published in other databases. Therefore, future research should include other databases. Second, in terms of language, this study selected only Chinese and English literature, but in many countries, important research results on certain topics are usually published in native language, and future research should expand the language selection. Third, this study only conducted national and institutional collaboration network analysis, keyword co-occurrence analysis, cluster analysis and timeline chart analysis.

The implication of practice can be divided into the following three points. (1) Analyzing the domestic and foreign literature on HIB and identifying highly cooperative institutions and countries in the field of HIB can reveal the research situation of HIB and help researchers establish new research networks in the future. (2) Analyzing the research hotspots and evolutionary paths of HIB at home and abroad is helpful for quickly understanding the development context of this field and grasping the emerging research directions such as HIB of people in close contact with patients, health information exchange behavior, health information avoidance behavior and health information discontinuation behavior, which can help researchers to explore the future research direction in this field, so as to determine the topic and fill the research gap. (3) Combining the analysis of HIB-related research at home and abroad is helpful for professionals to understand the characteristics and rules of HIB of users, consumers and other groups to further optimize and improve health information services.

Comparing and summarizing the research status of HIB in China and globally, and presenting the findings visually, will help researchers better grasp the research overview and hotspot changes in this field, as well as provide a follow-up reference.

This study aims to compares the effects of different human-like appearances (low vs. medium vs. high) of service robots (SRs) on consumer trust in service robots (CTSR), examines the mediating role of perceived warmth (WA) and perceived competence (CO) and demonstrates the moderating role of culture and service setting.

The research design includes three scenario-based experiments (Chinese hotel setting, American hotel setting, Chinese hospital setting).

Study 1 found SR’s human-like appearance can arouse perceived anthropomorphism (PA), which positively affects CTSR through parallel mediators (WA and CO). Study 2 revealed consumers from Chinese (vs. American) culture had higher CTSR. Study 3 showed consumers had higher WA and CO for SRs in the credence (vs. experience) service setting. The authors also had an exploratory analysis of the uncanny valley phenomenon.

The findings have practical implications for promoting the diffusion of SRs in the hospitality industry. Managers can increase CTSR by augmenting the anthropomorphic design of SRs; however, they must consider the differences in this effect across all service recipients (consumers from different cultures) and service settings.

The authors introduce WA and CO as mediators between PA and CTSR and set the culture and service setting as moderators.

Aluminum alloy is considered an ideal material in aerospace, automobile and other fields because of its lightweight, high specific strength and easy processing. However, low hardness and strength of the surface of aluminum alloys are the main factors that limit their applications. The purpose of this study is to obtain a composite coating with high hardness and lubricating properties by applying GO–PVA over MAO coating.

A pulsed bipolar power supply was used as power supply to prepare the micro-arc oxidation (MAO) coating on 6061 aluminum sample. Then a graphene oxide-polyvinyl alcohol (GO–PVA) composite coating was prepared on MAO coating for subsequent experiments. Samples were characterized by Fourier infrared spectroscopy, X-ray diffraction, Raman spectroscopy and thermogravimetric analysis. The friction test is carried out by the relative movement of the copper ball and the aluminum disk on the friction tester.

Results showed that the friction coefficient of MAO samples was reduced by 80% after treated with GO–PVA composite film.

This research has made a certain contribution to the surface hardness and tribological issues involved in the lightweight design of aluminum alloys.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0427/

The aim of this research was to investigate fans’ responses toward a sponsor that has had a long-standing sponsorship deal with a club and decided also to sponsor the club’s rival.

A long-term sponsorship deal between a retsina wine company and a popular football club and a newly established deal between the company and the main rival club were selected as the research setting. Data were collected from a total sample of 302 participants, fans of the two teams, using an online survey and PLS-SEM was employed to test the relationships of the proposed structural model.

The results provided evidence for the importance of the inclusion of perceptions of fit for both teams to the model as it impacted the responses in the joint sponsorship. Team identification emerged significant for improving fans perceptions of fit between the sponsor and their favorite club but also led fans of the long-term sponsored club to feel betrayed from the sponsor. The sense of betrayal impacted the level of fit, the rejection of sponsorship but did not emerge significant for driving negative responses toward the sponsor’s brand. The same held for the rejection of the joint sponsorship.

This is the very first study that incorporated the effects of the perceptions of fit of two rival clubs to test the effect of sponsorship for a sponsor brand of a deal that includes a longtime sponsored football club and its rival as a newly sponsored one. It is also one of the first attempts that explores relationships between perceptions of fit, sense of betrayal and rejection of a joint sport sponsorship in a rivalry context, highlighting the importance of preventing fans' betrayal.

This study aims to explore the impact of athlete brand image on fans’ social media engagement, purchase intentions, and also examines the mediating role of emotional attachment on these relationships, as well as the moderating role of perceived price value between emotional attachment and purchase intentions.

The data are based on an online survey conducted in China (N = 572). The PLS-SEM (partial least squares structural equation model) and regression-based estimation method (PROCESS) are employed to test the hypotheses.

The results indicate a positive relationship between athletes’ athletic performance and fans’ social media engagement as well as purchase intentions. The impact of athletes’ attractive appearance and marketable lifestyle on fans’ purchase intentions is sequentially mediated by emotional attachment and social media engagement. Moreover, the mediation effect of athletes’ off-field image and purchase intentions is contingent upon fans’ perceived price value.

Athletes and marketers could integrate and leverage both the on-field and off-field attributes to cultivate emotional connections with fans. Sports organizations and managers need to pay attention to fans’ social media engagement and provide content that increases engagement and converts into transactional behavioural intentions.

The study provides empirical evidence of the mediating role of emotional attachment between athlete brand image and fans’ purchase intentions. The explanatory mechanisms involving emotional attachment and social media engagement (non-transactional behavioural intentions) are anticipated to be a noteworthy addition to the traditional fan transactional behavioural intentions framework. Moreover, the research introduces and confirms perceived price value as a crucial moderating factor influencing the relationship between emotional attachment and purchase intentions.