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The purpose of this paper is to purify the wastewater in the garment industry.

The preparation of the calcium alginate (CA)/activated carbon (AC) composite membrane was achieved by vacuum freeze-drying and the cross-linking reaction between sodium alginate and CaCl₂. Effective parameters in the methylene blue (MB) adsorption such as temperature, dose, contact time and pH were discussed. The adsorption properties of the composite membrane were investigated by isotherm, kinetics and thermodynamic analysis. The adsorption equilibrium data were described by the adsorption isotherm Langmuir model and the Freundlich model. The pseudo-first-order, pseudo-second-order and intra-particle diffusion equations were selected to evaluate the kinetics. The thermodynamic study described that the adsorption reaction was spontaneous and exothermic.

The AC/CA membrane is an efficient and powerful adsorbent to remove MB in printing and dyeing wastewater, and provides a new idea for the selection of adsorption materials for industrial printing and dyeing wastewater.

The composite membrane research on CA and AC can provide new ideas for the research of these kinds of materials.

The paper contributes to its wider and convenientapplication in wastewater treatment.

Studies on the combination of CA and AC into adsorption membranes and for the removal of dyes from printing and dyeing wastewater have not been reported. A novel composite material is provided for treatment dyeing wastewater in garment production. The composite membrane research on CA and AC can provide new ideas for the research of these kinds of materials and contribute to its wider and convenient application in wastewater treatment.

The purpose of this paper is to systematically synthesize the extant literature of knowledge sharing (KS) and knowledge transfer (KT) in the small and medium enterprise (SME) context and to contribute with predictions of emerging themes.

Applied is a systematic literature review using three bibliometric techniques: (1) textual analysis for keywords and abstracts to identify the research hotspots, (2) co-citation analysis of references to identify the evolution of KS and KT in SME and (3) bibliographic coupling analysis of documents to synthesize antecedents and outcomes.

A conceptual map emerges from the review to reveal the antecedents of KS and KT at the individual, group and organizational levels. The analysis shows the strategic importance of KS and KT for the SME context. Specific findings include: (1) KS and KT are involved in enhancing SMEs strategic focus for human resources, including organizational learning, customer relations, creativity, higher profit and positive effects on operational processes and decision-making. (2) Innovation, trust and performance are identified as central human factors linked to KS and KT in SMEs. (3) Human resource (HR) management research could contribute to KS and KT in the SME domain by exploring KS- and KT-based practices, linking the emergence of innovation and innovative behaviors to these practices, leading to a better understanding of strategies that enable the long-term storage and retrieval of tacit and explicit knowledge as organizational memory in the SME context.

This paper is one of the first to systematically review KS and KT in SMEs and propose a concept map. The research adds value to the growing literature of KS and KT and exposes the need for more specific activities to support SME managers, as well as HR managers, who need to facilitate KS and KT in SMEs.

This paper aims to give a brief review on behavioral economics and behavioral finance and discusses some of the previous research on agents' utility functions, applicable risk measures, diversification strategies and portfolio optimization.

The authors also cover related disciplines such as trading rules, contagion and various econometric aspects.

While scholars could first develop theoretical models in behavioral economics and behavioral finance, they subsequently may develop corresponding statistical and econometric models, this finally includes simulation studies to examine whether the estimators or statistics have good power and size. This all helps us to better understand financial and economic decision-making from a descriptive standpoint.

The research paper is original.

The purpose of this paper is to investigate the fatigue performance of a welded detail from a composite steel-concrete railway twin girder bridge caused by a passenger train circulating at varying speeds, by identifying the dynamic amplification scenarios induced by resonance. For this purpose, the hotspot stress method is used, instead of the traditional nominal stress methods.

This paper assesses the fatigue behavior of a welded connection considering critical stress concentration locations (hotspot). Finite element analysis (FEA) is applied, utilizing both a global and a local submodel, made compatible by displacements field interpolation. The dynamic response is obtained through the modal superposition method. Stress cycles are extracted with the rainflow counting method and the fatigue damage is calculated with Palmgren-Miner’s rule. The feasibility of five submodels with different mesh densities, i.e. 1, 2, 4, 8 and 20 mm is verified.

An increase in the fatigue damage due to the resonance effect was found for the train traveling at a speed of 225 km/h. A good agreement between the computed fatigue damage for the submodels is achieved. However, a non-monotonic hotspot stress/fatigue damage vs mesh density convergence was observed with a peak observed for the 4 mm model, which endorses the mesh sensitivity that could occur when using the surface stress extrapolation detailed rules specified in the standards for the hotspot stress method.

Advanced dynamic analyses are proposed to obtain local stresses in order to apply a local method for the fatigue assessment of a bridge’s structure subjected to high-speed railway traffic on the basis of the mode superposition technique resulting in much less computing times.

The purpose of this paper is to explore two identified knowledge gaps: first, the identification and analysis of online searching trends for Financial Technology (FinTech)-related jobs and education information in UK, and second to assess the current strength of the FinTech-related job distribution in terms of job titles and locations in UK, job market in UK and what is required to help it to grow.

Two sets of data were used in this study in order to fill the two identified knowledge gaps. First, six years’ worth of data, for the period from September 2012 to August 2018 was collected from Google Trends. This was in the form of search term keyword text. The hypothesis was designed correspondingly, and the results were reviewed and evaluated using a relevant statistical tool. Second, relevant data were extracted from the “Indeed” website (www.indeed.co.uk) by means of a simple VBA programme written in Excel. In total, the textual data for 500 job advertisements, including the keyword “FinTech”, were downloaded from that website.

The authors found that there was a continuously increasing trend in the use of the keyword “fintech” under the category “Jobs and Education” in online searching from September 2012 to August 2018. The authors demonstrated that this trend was statistically significant. In contrast, the trends for searches using both “finance” and “accounting” were slightly decreased over the same period. Furthermore, the authors identified the geographic distribution of the fintech-related jobs in the UK. In regard to job titles, the authors discovered that “manager” was the most frequently searched term, followed by “developer” and “engineer”.

Educators could use this research as a reference in the development of the portfolio of their courses. In addition, the findings from this study could also enable potential participators to reflect on their career development. It is worth noting that the motivations for carrying out an internet search are complex, and each of these needs to be understood. There are many factors that would affect how an information seeker would behave with the obtained information. More work is still needed in order to encourage more people to enter to the FinTech sector.

In the planning stage prior to launching a new course educators often need to justify the market need: this analysis could provide a supporting rationale and enable a new course to launch more quickly. Consequently, the pipeline of talent supply to the sector would also be benefitted. The authors believe this is the first time that a study like this had been conducted to explore specifically the availability and opportunities for FinTech education and retraining in UK. The authors anticipate that this study will become the primary reference for researchers, educators and policy makers engaged in future research or practical applications on related topics.

Given the rapid growth of the Chinese cruise market, several Chinese cities are attempting to become a hub for cruise ships. The aim of this study is to evaluate the competitiveness of those cities with regard to hosting cruises. It employs a cloud model that transforms the qualitative description of competitive indicators into quantitative measurement and assesses the competitive advantage and specialization of the top homeports in China. Questionnaires are delivered to experts from eight cruise ports in China and the cloud model based on 14 evaluation factors is used to analyze the competitiveness of the ports under investigation. The result shows that the city’s scale, population, and development have been the main factors for assessing the competitiveness of port cities. The research provides insight about the Chinese cruise port cities’ competitiveness, which is particularly useful for future development decision and marketing strategies of ports and prospective destinations.

Manufacturing small and medium-sized enterprises (SMEs) are heading towards smart manufacturing despite growing challenges caused by globalisation and rapid technological advancement. These SMEs, particularly textile SMEs of Bangladesh, also face challenges in implementing sustainability and organisational ambidexterity (OA) due to resource constraints and limitations of conventional leadership styles. Adopting paradoxical leadership (PL) and entrepreneurial bricolage (EB) is important to overcome the challenges. However, these dynamics are less explored in academia, especially in the Bangladeshi textile SMEs context. Hence, the purpose of this study is to investigate the influence of the adoption of smart technologies (ASTs), PL and OA, EB on sustainable performance (SP) of textile SMEs in Bangladesh.

A cross-sectional and primary quantitative survey was conducted. Data from 361 textile SMEs were collected using a structured self-administrated questionnaire and analysed by partial least square structural equation modelling (PLS-SEM).

The statistical outcome confirms that ASTs and PL significantly influence SP and OA. OA plays a significant mediating role for PL and is insignificant for ASTs, and EB significantly moderates among ASTs, PL and SP.

As this study is cross-sectional and focussed on a single city (Dhaka, Bangladesh), conducting longitudinal studies and considering other parts of the country can provide exciting findings.

This research provides valuable insights for policymakers, management and textile SMEs in developing and developed countries. By adopting unique and innovative OA, PL and EB approaches, manufacturing SMEs, especially textile companies, can be more sustainable.

This study has a novel, pioneering contribution, as it empirically validates the role of multiple constructs such as AST, PL, OA and EB towards SP in the context of textile SMEs in a developing country like Bangladesh.

The unitized curtain wall system (UCWS), a symbol of modern architecture, is gaining popularity among prefabricated components. Previous studies have focused on both construction technology advances and material selection strategies to facilitate the UCWS. However, the topic of client satisfaction, which drives industry development by targeting clients' demands, has gone unnoticed. Therefore, the current study aims to investigate client satisfaction with UCWS products in Hong Kong by finding its influential factors.

A systematic review was employed to first identify the influential factors. A semi-structured interview was employed to validate the reliability of the extracted factors. The machine learning algorithm Extreme Gradient Boosting (XGBoost) and the Pearson correlation were then employed to rank the importance and correlation of factors based on the 1–5 Likert scale scores obtained through a questionnaire survey.

The findings revealed that “reduction in construction time” and “reduction in construction waste” are the most important factors and have a strong positive influence on client satisfaction.

Unlike previous studies, the present study focused on a novel research topic and introduces an objective analysis process using machine learning algorithms. The findings contribute to narrowing the knowledge gap regarding client preference for UCWS products from both individual and collaborative perspectives, providing decision-makers with an objective, quantitative and thorough reference before making investments in the curtain wall management development.

The purpose of this paper is to develop a conceptual model for smartphone brand switching behavior, based on the consumption value theory (functional value, emotional value, social value and epistemic value) and the cognition affect behavior (CAB) model. Two paths – product consumption values and retail service relational benefits – were considered as the cognitive elements to predict brand commitment (affect) and smartphone brand switching behavior. In addition, switching cost was used to measure the moderating effect on the relationship between brand commitment and smartphone brand switching behavior.

This research examined whether product consumption value and cognitive benefits related to retail services will enhance brand commitment and then further decrease smartphone brand switching behavior. Switching cost was predicted as a moderator in the model. An investigation of consumers who own a particular brand of smartphone (e.g. the top five smartphone brands: Samsung, Apple, HTC, Sony and Asus) was conducted, and 565 valid responses were collected for the structural equation modeling analysis.

The results demonstrated that emotional value, social value, epistemic value and confidence benefits increased consumer brand commitment and predicted less smartphone brand switching behavior. In addition, switching cost played a significant moderator role in the relationship between brand commitment and brand switching behavior.

A multiple cognitive paths design, with a consumption values aspect and a relational benefits aspect, can elaborate consumer perceptions of product values and service benefits simultaneously, which can lead to a better understanding of the whole picture of the brand services and the key reasons why consumers commit to a brand. Administrators of brand vendors are suggested to improve product innovation and the professionalism of sales services in order to facilitate consumer consumption values, increase their degree of confidence in members of sales staff and, in the meantime, help these administrators gain an understanding of the real reasons for brand switching so as to provide solutions leading to the maintenance of consumer brand commitment through products or services. This is, in turn, likely to increase continued usage intention and reduce the possibility of brand switching.

This study extended the consumption value theory and the CAB model to show that product consumption value and cognitive benefits related to retail services can enhance brand commitment and further decrease smartphone brand switching behavior. The results indicated that brand retailer managers should regularly conduct activities to connect with their customers to induce consumption values and relational benefits and, consequently, increase brand commitment and prevent customer switching behavior.