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The purpose of this study is to understand the conditions in which subordinates, after making a mistake, are more likely to engage in feedback avoidance behaviour (FAB), a set of behaviours that could ultimately jeopardise patient safety in a health care context.

This study used a sample of 183 independent leader-subordinate dyads in the health care service sector. For this study, a multiple mediator model in which three types of conflict (task conflict, relationship conflict and process conflict) were tested and acted as mediating mechanisms that transmitted the effects of perceived dissimilarity to FAB.

The results supported the mediating role of two of the three forms of conflict and highlighted the consequences of dissimilarity between supervisors and subordinates in the healthcare setting.

One of the noteworthy limitations of this study was that this study used cross-sectional time-lagged data. Future research should use a more rigorous longitudinal approach such as a cross-lagged design (Whitman et al., 2012) to explore the dynamic nature of dyadic relationships over time.

An important implication of our study results suggests that health care leadership development training should provide opportunities to increase awareness of the tendency of leaders to treat subordinates perceived as dissimilar more negatively.

These results contribute to our understanding of the interpersonal processes between subordinates and their supervisors, which could have a significant impact on organisational outcomes in the health care setting.

This paper aims to examine the influences of the number of hotel management responses and especially the textual similarity in hotel management responses to online reviews on hotel online booking.

This study used the data from 437 hotels in New York City on Expedia. The data specifically include online reviews, management responses and real-time number of online hotel bookings, which were merged to create one dataset for this study. To calculate the management response similarity, three widely recognized text mining functions of calculating textual similarity were adopted in this model. Fixed-effect panel data model was then used to examine the influence of management response to consumer online reviews on online hotel booking volume.

The empirical results demonstrate that the number of management responses to consumer online reviews does not significantly affect hotel booking; compared to none or only one management response, or management responses with low similarity, management responses with high similarity can significantly reduce the hotel booking on Expedia.

This study suggests that the similarity of management responses influences customers’ hotel booking, and hotel managers should avoid providing too similar management responses.

First, this study, for the first time, proposes the concept of management response similarity and its measurement methods. Second, this study takes an initial attempt to empirically test the influence of response similarity on hotel booking by using secondary data online.

Software developers extensively use stack overflow (SO) for knowledge sharing on software development. Thus, software engineering researchers have started mining the structured/unstructured data present in certain software repositories including the Q&A software developer community SO, with the aim to improve software development. The purpose of this paper is show that how academics/practitioners can get benefit from the valuable user-generated content shared on various online social networks, specifically from Q&A community SO for software development.

A comprehensive literature review was conducted and 166 research papers on SO were categorized about software development from the inception of SO till June 2016.

Most of the studies revolve around a limited number of software development tasks; approximately 70 percent of the papers used millions of posts data, applied basic machine learning methods, and conducted investigations semi-automatically and quantitative studies. Thus, future research should focus on the overcoming existing identified challenges and gaps.

The work on SO is classified into two main categories; “SO design and usage” and “SO content applications.” These categories not only give insights to Q&A forum providers about the shortcomings in design and usage of such forums but also provide ways to overcome them in future. It also enables software developers to exploit such forums for the identified under-utilized tasks of software development.

The study is the first of its kind to explore the work on SO about software development and makes an original contribution by presenting a comprehensive review, design/usage shortcomings of Q&A sites, and future research challenges.

This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed.

The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe.

The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value.

The vessel carrying capacity is not considered in an explicit way.

This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously.

Counterfeiting is an increasing global problem, which affects a wide spectrum of industries – fashion, pharmaceutical, cosmetic, electronic, food processing etc. Globalisation, growth of the world commerce, new markets and technology development have contributed to the growth of the phenomenon of counterfeiting. Besides, counterfeiting has an unfavourable effect on legitimate manufacturers, consumers, as well as on national and international economy.

This chapter is aimed at presenting attitudes of consumers in Bosnia and Herzegovina toward counterfeit products. The intention was to examine whether and why consumers buy counterfeit products, which counterfeit products are purchased most frequently, consumers' attitudes toward counterfeit products and the degree of awareness of the risk of using counterfeit products.

Results of a research conducted on the sample of 427 respondents in Bosnia and Herzegovina reveal that 78.2% of them have bought a counterfeit product, while the most frequently purchased kinds of products include clothes and footwear. The results show that consumers typically buy counterfeit products over the internet or in the local marketplaces, and that the most frequent reasons for buying counterfeit products include lower prices, impossibility to buy the original product and the impossibility to recognise a counterfeit product. The research has also showed that most respondents agree that product counterfeiting affects both manufacturers and the national economy. It was also revealed that the respondents are aware of the risks that counterfeit products may cause.

The purpose of this paper is to advance a digital technology that is intended to bring about innovations on the existing textile patterns.

The pattern is deemed as a relation function between colors and positions which can be learnt by the artificial neural network (ANN). The outputs of the ANN are used for the reconstruction of the pattern and the innovation is performed by interceptors in the input/output layer. The ANN is carried out with one input layer, one output layer and several hidden layers, and the capacity of the architecture is adjusted by the scale of hidden layers to accommodate different function relations of the patterns. The training is conducted repeatedly on a sample set extracted from the pixels of the pattern image to minimize the error, and the chromatic outputs of the architecture are replaced to their origins so as to rebuild the pattern. Then, the interceptors are installed into the input and output layers to modulate the positions and the colors, and consequently the innovations are achieved on the geometric formation and color distribution of the pattern.

It has turned out that the precision of reconstruction is concerned with network scale, training epochs and color mode of the sample set. Four primary innovative effects including stripes, twisters, sandification and overprints have been qualified in terms of interceptors.

This study introduces ANN into textile pattern generation and provides a novel way to perform digital innovation of textile patterns.

The purpose of this paper is to develop an environmentally friendly dyeing process using brown pigment from chestnut shells (BPFCS). This material is obtained from foodstuff residues and can make a significant contribution to reusing a reproducible biomass resource, economizing petroleum, avoiding water pollution and protecting human health.

The brown pigment is extracted from the raw material and purified with solvents containing 30 and 100 per cent EtOH. It is then used to dye flax fabric in aqueous solution with added NaCl as a dye accelerator. The effects of dyeing conditions and fastness are investigated. The pigment, and the pristine and dyed fabrics are analysed by Fourier‐transform infrared spectroscopy (FT‐IR) and the fabric samples are observed using a scanning electron microscope (SEM). Fastness to washing, rubbing and light are also measured.

BPFCS show promising dyeability on cellulosic fibers. White flax fabric is successfully dyed with the pigment to a yellow‐brown colour. The base dyeing conditions are as follows: pigment concentration 16 g/l, NaCl concentration 10 g/l, liquor ratio 10:1, temperature 95°C, dyeing time 40 min. The dyed fabrics have lower fastness to washing and higher fastness to rubbing and light. A total of 4 per cent Al³⁺ or Fe²⁺ treatment of dyed fabric can improve fastness to washing, but decrease fastness to rubbing. The yellowish‐brown samples are transformed to brown or dark‐green after Al³⁺ or Fe²⁺ treatment, respectively. The pigment is a mixture with abundant hydroxyl groups.

The studies of dyeing conditions and fastness are carried out in detail as BPFCS used as a dye. However, a qualitative analysis of the pigment could not be performed due to the difficulty of separating the mixture. The BPFCS used in this paper can dye cellulosic fiber and can also be used to dye other fibers such as silk, wool and PET. Dyeing conditions for these other fibers need to be investigated.

BPFCS may play an important role in the dyeing industries because of its good dyeability, lack of toxicity and resistance to water, rubbing and light. The present work offers an environmentally friendly dye and a simple dyeing method.

At present, no report exists in the literature of work on dyeing flax fabric with BPFCS. This paper represents a preliminary study to determine the relationships of dyeing conditions to fastness and the role of mordant. BPFCS appears to be a new and practically useful natural dye.

China after 1949, especially since entering the 21st century, significant progress has been made in leadership research under Chinese context. However, so far there has been no systematic review and prospect of China's leadership research in the past 70 years. Therefore, with the help of scientific visualization software Citespace, this paper analyzes the research papers on leadership in the context of China from the top international journals of management science and applied psychology (1949–2018), supplemented and verified the previous research conclusions based on qualitative review, and quantitatively demonstrated the research evolution of leadership field.

Using a scientific visualization tool CiteSpace and 145 international leadership works, which were published in 64 top international journals and collected from the Web of Science database, and 852 domestic works which were published in 28 top domestic journals and collected from the CNKI database from 1949 to 2018, we draws keyword co-occurrence knowledge graph and keyword strategy map to visualize the landscape and evolution of leadership research and analyze the hot topics and research trends in the field of leadership.

The research found that: (1) Before 2002, there were only 7 articles published in 64 international top journal, mainly focusing on Western leadership theories such as transformational, cross-cultural comparison and the adaptability in Chinese context; (2) From 2003 to 2012, scholars had begun to introduce mainstream quantitative research paradigm in international academic community; (3) From 2013 to 2018, researches tended to be synchronized, with 461 and 99 papers published respectively. How emerging leaderships (such as ethical leadership) affect on various emerging outcome variables (such as creativity, voice behavior, unethical pro-organizational behavior etc.) is hot topic for future research.

Different from the previous qualitative reviews on organizational culture research, this paper, for the first time, uses bibliometric research methods to systematically analyze the evolution path of leadership research during the 70 years of China(1949–2018, and puts forward the future research prospects.

Digital-only fashion represents an ideal fusion of sustainability and fashionability, garnering growing interest among fashion professionals. However, there is a noticeable gap in research focusing on digital-only fashion acceptance among consumers. Hence, this study aims to empirically examine consumers’ motivations, evaluations and acceptance of digital-only fashion based on the Functional Theory of Attitudes.

A US-based research agency was hired to collect data, resulting in 247 completed survey responses. Data analysis was conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach.

Testing results highlight that consumer acceptance of digital-only fashion is directly influenced by both overall attitude and self-expressive attitude. Self-expression is particularly pivotal in digital-only fashion acceptance. Adorning avatars and dressing realistic on-screen bodies are distinct yet complementary aspects of using digital-only fashion. Consumers with positive environmental beliefs about digital-only fashion are concerned about how well digital-only fashion items allow them to express such beliefs.

This study innovatively applied the functional theory of attitudes to the emerging domain of digital-only fashion and identified consumers’ four functional attitudes toward digital-only fashion, along with the underlying motivations served by each functional attitude. Furthermore, this study provides valuable practical insights across the digital-only fashion value chain.