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The comfort and fit of clothes are affected by fabric properties, dressed ease and environmental conditions, in which dressed ease is influenced by the interaction among complex shapes of human body, style design and fabric mechanical properties.

In this study, the dressed ease distribution at waist section, which is related to body surface convex angle, was investigated using 3D scanning. A series of surface convex angles on bust and back were formed after adjusting the mannequin. The mannequin was scanned by TC2 separately in garments with eight different ease allowances. Then the dressed ease distributions at waist under different convex angles of body surface have been acquired by calculating the distance between waist points and dressed surfaces along normal directions.

The results showed that the body surface convex angle was weakly related to the dressed ease when the garments’ bust ease allowance was below 4 cm. When the garments’ bust ease allowance was within 6–12 cm, the body convex angle had a great impact on the dressed waist ease distribution in the condition of 26º–33º bust convex angle and 13.96º–17.96º back slope angle. For slack garments with more than 16 cm ease allowance, the dressed waist ease distribution did not relate to the bust convex angle, while it strongly related to the bust convex angle between 13.96º and 17.96º. The regression model was statistically significant between the dressed ease value and the body surface convex angle.

According to the dressed waist ease distribution of different body surface convex angles, this paper gives an application of pattern modification in order to optimize the waist fit. The results can provide guidance for the optimization of different body shapes. At the same time, the application of gap data to 3D virtual fitting can greatly improve the authenticity of virtual simulation effect.

The purpose of this study is to investigate how and why formal mentoring support reduces newcomers' intention to leave from the perspective of uncertainty reduction theory.

Time-lagged data were collected from two sources, mentors and newcomers, and 193 paired data sets were included in the analysis.

The results showed that formal mentoring support was positively related to newcomers' person–organisation fit (P–O fit) and person–job fit (P–J fit). In addition, P–O fit and P–J fit mediated the relationship between formal mentoring support and newcomers' intention to leave. Moreover, newcomers' uncertainty avoidance orientation strengthened the relationship between formal mentoring support and perception of fit, and it strengthened the indirect effect between formal mentoring support and newcomer's intention to leave, via the perception of fit.

This study enhances our understanding of the underlying mechanism between formal mentoring support and newcomers' intention to leave. Moreover, it demonstrates that uncertainty avoidance orientation is an important boundary condition during the process of organisational socialisation. The findings also contribute to the organisational socialisation and the mentoring literature by providing evidence from a blue-collar sample.

The rise of artificial intelligence (AI) and differing attitudes towards its adoption in the building and environment (B&E) industry has an impact upon whether companies can meet changing demand and remain relevant and competitive. The emergence of Industry 4.0 technologies, coupled with the repercussions of COVID-19, increases the urgency and opportunities offered that companies must react to, as disruptive technologies impact how project management (PM) professionals work and necessitate acquisition of new skills. This paper attempts to identify the drivers of and barriers to, as well as the general perception and receptiveness of local PM professionals towards, AI adoption in PM and thereby propose potential strategies and recommendations to drive AI adoption in PM.

This study employs both quantitative and qualitative approaches to examine the findings gathered. A survey questionnaire was used as the primary method of gathering quantitative data from 60 local PM professionals. Statistical tests were performed to analyse the data. To substantiate and validate the findings, in-depth interviews with several experienced industry professionals were performed.

It is found that top drivers include support from top management and leadership, organisational readiness and the need for greater work productivity and efficiency. Top barriers were found to be the high cost of AI implementation and maintenance and the lack of top-down support and skilled employees trained in AI. These findings could be attributed to the present state of AI technologies being new and considerably underutilised in the industry. Hence, substantial top-down support with the right availability of resources and readiness, both in terms of cost and skilled employees, is paramount to kick-start AI implementation in PM.

Little research has been done on the use of AI in PM locally. AI's potential to improve the productivity and efficiency of PM processes in the B&E industry cannot be overlooked. An understanding of the drivers of, barriers to and attitudes towards AI adoption can facilitate more intentional and directed oversight of AI's strategic roll-out at both the governmental and corporate levels and thus mitigate potential challenges that may hinder the implementation process in the future.

Marketing scholars have begun to look at negative emotions that young consumers could develop toward brands, such as brand hate. Brand hate has experienced exponential growth during the past decades in the cosmetic industry. In this frame, the purpose of this paper is to identify the weight of each of the five key drivers of brand hate and to analyze if these weights are the same (or not) for drugstore and luxury make-up brands regarding.

To carry on this paper, brand haters in the make-up industry were contacted with the help of cosmetic influencers. Participants of the online questionnaire (N = 162) were existing young makeup consumers. They were divided into drugstore and luxury makeup brand haters by classifying their identified hated brands into either group.

The authors’ results showed, first, that experiential, identity, moral, deficit-value and advertising avoidance all had a positive effect on brand hate, being identity avoidance the strongest one. Second, drugstore and luxury makeup brand haters do not differ, as far as no differences were identified in the strength of each avoidance type on brand hate.

There is a gap in the literature related to the absence of work investigating brand hate in the make-up industry; moreover, studies measure whether brand hate drivers are the same (or not) for luxury brands and drugstore brands that compete in the same arena. In this framework, this research will provide a specific industry context involving young consumer opinions. Research into consumer–brand relationships has been largely focused on the positive forms, while the negative forms are still a relatively newer area of academic interest. Even more, brand hate has been investigated from a multidimensional approach linking proposals from different authors has been tested.

This research aims to provide a conceptual framework with the scope to assist in establishing sustainable supply chain clusters (SCCs) by providing an instrument for organisations to enhance the three sustainability dimensions in a dynamic environment.

This research proposes a conceptual framework to enhance sustainability and organisational performance through three theoretical lenses: the system theory, extended resource-based view and the dynamic capabilities (DCs) theory. This approach is carried out through a comprehensive review of the existing literature on SCCs.

Four main propositions are formulated and demonstrated using the developed framework, which expands the discussion about SCCs and their key characteristics in a dynamic environment. This is particularly relevant as it allows empirical testing of the theories in an SCC context.

It can be noted that more extensive research is needed to further understand the issues faced in establishing sustainable clusters. Drawing on the theoretical lenses to establish the framework helps to enhance the understanding and operational capabilities of sustainable SCCs during and after disruptions, such as the global disruption created by COVID-19.

This research paves the way to help organisations improve their adaptability to the dynamic business environment by emphasizing the importance of clustering and linking it to sustainability through DCs to establish a sustainable cluster.

This research aims to guide organisations' use of SCCs as tools to enhance sustainability in a dynamic environment, given that the relationship amongst supply chain cluster design characteristics (SCCDCs), DCs and sustainability remains unexplored. The combination of the three theoretical lenses in developing the proposed framework will assist in further understanding the applicability of these theories when they are considered together.

This paper aims to investigate if and to what extent environmental, social and governance (ESG) practices are influenced by innovation, measured by investment in research and development (R&D) and the number of patents developed by companies.

To test this hypothesis, the authors estimated a regression model for the panel data considering a time horizon of eight years. The analysis was conducted on a sample of listed firms operating in the industrial sector in France, Germany, Italy, Spain, the UK and the USA.

The empirical analysis shows that there is a positive and significant relationship between ESG practices and innovation. Companies investing more in R&D and patents have better ESG performance.

This study contributes to the existing literature by improving the understanding of the importance of innovation in improving ESG practices for firms in the industrial sector. Furthermore, it provides empirical evidence of the ability of innovation to be a valuable tool for sustainable industry development through R&D investment and patent development.

This paper aims to analyze the application of remotely piloted aircraft (RPA) for remote oil spill sensing.

This paper is an analysis of RPA strong points.

To increase the accuracy and eliminate potentially false contamination detection, which can be caused by external factors, an oil thickness measurement algorithm is used with the help of the multispectral imaging that provides high accuracy and is versatile for any areas of water and various meteorological and atmospheric conditions.

SWOT analysis of implementation of RPA for remote sensing of oil spills.

The use of RPA will improve the remote sensing of oil spills.

The concept of oil spills monitoring needs to be developed for quality data collection, oil pollution control and emergency response.

The research covers the development of a method and design of a device intended for taking samples and determining the presence of oil contamination in an aquatorium area; the procedure includes taking a sample from the water surface, preparing it for transportation and delivering the sample to a designated location by using the RPA. The objective is to carry out the analysis of remote oil spill sensing using RPA. The RPA provides a reliable sensing of oil pollution with significant advantages over other existing methods. The objective is to analyze the use of RPA employing all of their strong points. In this paper, technical aspects of sensors are analyzed, as well as their advantages and limitations.

The purpose of this paper is to present a quantitative analysis of the Library and Information Science (LIS) scholarly literature published worldwide.

The ISI Web of Science database was used as a source for extracting the data of published documents during the period 2003–2017. The analysis of the published literature was based on the following indicators: research productivity of each county, annual publications, annual citations, highly cited articles, highly cited LIS journals, most productive institutions in the field of LIS and most prolific authors. The types of documents included in this study were research articles, conference proceeding papers, book reviews and editorials.

The findings revealed that the USA had the highest overall output of LIS scholarly publications. The year 2016 was identified as the most productive year for the number of publications, whereas 2017 was identified as the most productive year for the number of citations. “Impact of data sources on citation counts and rankings of LIS faculty: Web of Science versus Scopus and Google Scholar” was the most highly cited article. The Journal of Medical Library Association was the most highly cited journal in LIS. Indiana University from the USA was the most productive LIS research institution. Mike Thelwall, from the UK, is identified as the most prolific author in LIS.

The study will be of interest for those researchers, who intend to conduct bibliometric research studies in LIS.

In today’s Taiwan, sha-cha sauce is an indispensable ingredient for beef hot pot and stir-fried dishes. The purpose of this paper contextualizes the history of sha-cha sauce in Tainan, the oldest city in Taiwan, and argues that sha-cha sauce, introduced by Chaoshan immigrants, has contributed to new styles and habits of beef consumption tastes and habits in the post-1949 Tainan and beyond.

This paper uses documentary materials, oral interviews and diaries to explore the relationship between beef consumption and sha-cha sauce. It begins with an historical overview of Taiwan’s beef consumption during the Japanese colonial era (1895-1945). Then, it focuses on two Chaoshan business enterprises: the Bull-Head, which makes the world’s largest “canned sha-cha sauce,” and the Xiao Haozhou, a Tainan restaurant specializing in sha-cha beef hot pot. Finally, this study analyzes Xinrong Wu, a Tainan gentry whose diary entries from 1933 to 1967 documented the changing dietary habits of beef consumption among Taiwanese.

The Chaoshan migrants played an important role in introducing the sha-cha sauce to postcolonial Tainan, and this input bolstered the beef consumption among Taiwanese. The production of sha-cha provided a reliable source of income for these migrants in Tainan, and major businesses like the Bull-Head became the international brands of Taiwanese food products.

The study, though limited to Tainan, reveals the symbiosis between popularization of sha-cha sauce and widespread beef consumption in Taiwan.

This study helps researchers examine the connection between Chinese migrations and food culture.

This paper is an original scholarly investigation of the relationship between food diet and Chaoshan migration in postcolonial Tainan.

Whilst professional learning communities (PLCs) have been widely explored at the school level, they have received less attention at the departmental level. The study takes the variance between departments and the role of departmental teacher leaders into consideration, and the relationships amongst departmental-level PLC dimensions, two types of teacher leadership (TL) and individual teacher self-efficacy are investigated.

The sample consisted of 907 teachers from 81 departments in Chinese schools. The associations between the studied variables were explored through a multi-level analysis approach.

The results show that two specific characteristics of departmental PLCs, namely reflective dialogue (RD) and collective responsibility (CR), exhibit a positive correlation with individual teacher self-efficacy. Additionally, the findings indicate that teacher transformational leadership significantly predicts teacher self-efficacy, whereas teacher instructional leadership (IL) does not emerge as a significant predictor. These findings may be attributed to the contextual factors of Chinese teachers' collective work and the practice of teacher leaders.

This research contributes to the existing literature by addressing the variance between departments and uncovering the impacts of departmental PLC dimensions on individual teachers. Furthermore, two TL styles at the departmental level are differentiated, and their distinct influences on teacher self-efficacy are further analysed.