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This study aims to evaluate the efficiency of metal electrode and electrolytes on the electroflocculation of indigo wastewater, produced by printing and dyeing factory, and to optimize the treatment system.

For effective purging, various types of metal electrodes (graphite, pure aluminum and stainless steel) and supporting electrolytes (sodium chloride and sodium sulfate) were selected for electroflocculation experiments. The decolorization rate and chemical oxygen demand (COD) removal rate were characterized.

The treatment effects of stainless steel and aluminum were similar, but the dissolution loss of aluminum and the production of flocs greatly limit its application. Electrolytes gave obvious effects to these systems. Sodium sulfate was better than sodium chloride, the decolorization rate was increased by 3.31%, the removal rate of COD in the solution was increased by 28.65% and the weight of flocculation precipitation was reduced by 0.214 g.

The electrochemical treatment system was constructed to compare and analyze the influence of experimental parameters and to provide a reference for the actual treatment of indigo wastewater.

Electrochemical flocculation can remove the insoluble indigo solids and it plays a key role in wastewater treatment.

It is novel to optimize the combination of electrode and electrolyte to improve the efficiency of electroflocculation, which can be widely used in the actual wastewater treatment process.

This study aims to explore suitable anode materials used in the electrochemical system for indigo dyeing wastewater, to achieve optimal treatment performances.

The single factor experiment was used to explore the optimum process parameters for electrochemical decolorization of indigo dyeing wastewater by changing the applied voltage, electrolysis time and electrolyte concentration. At the voltage of 9 V, the morphology of flocs with different electrolytic times was observed and the effect of electrolyte concentration on decolorization rate in two electrolyte systems was also investigated. Further analysis of chemical oxygen demand (COD) removal rate, anode weight loss and sediment quantity after electrochemical treatment of indigo dyeing wastewater were carried out.

Comprehensive considering the decolorization degree and COD removal rate of the wastewater, the aluminum electrode showed the best treatment effect among several common anode materials. With aluminum electrode as an anode, under conditions of applied voltage of 9 V, electrolysis time of 40 min and sodium sulfate concentration of 6 g/L, the decolorization percentage obtained was of 94.59% and the COD removal rate reached at 84.53%.

In the electrochemical treatment of indigo dyeing wastewater, the aluminum electrode was found as an ideal anode material, which provided a reference for the choice of anodes. The electrodes used in this study were homogenous material and the composite material anode needed to be further researched.

It provided an effective and practical anode material choice for electrochemical degradation of indigo dyeing wastewater.

Combined with the influence of applied voltage, electrolysis time and electrolyte concentration and anode materials on decolorization degree and COD removal rate of indigo dyeing wastewater, providing a better electrochemical treatment system for dyehouse effluent.

This research explores mitigating carbon emissions and integrating sustainability in e-commerce logistics by optimizing the multi-depot pollution routing problem with time windows (MDPRPTW). A proposed model contrasts non-collaborative and collaborative decision-making for order assignment among logistics service providers (LSPs), incorporating low-carbon considerations.

The model is substantiated using improved adaptive large neighborhood search (IALNS), tabu search (TS) and oriented ant colony algorithm (OACA) within the context of e-commerce logistics. For model validation, a normal distribution is employed to generate random demand and inputs, derived from the location and requirements files of LSPs.

This research validates the efficacy of e-commerce logistics optimization and IALNS, TS and OACA algorithms, especially when demand follows a normal distribution. It establishes that cooperation among LSPs can substantially reduce carbon emissions and costs, emphasizing the importance of integrating sustainability in e-commerce logistics optimization.

This paper proposes a meta-heuristic algorithm to solve the NP-hard problem. Methodologies such as reinforcement learning can be investigated in future work.

This research can help logistics managers understand the status of sustainable and cost-effective logistics operations and provide a basis for optimal decision-making.

This paper describes the complexity of the MDPRPTW model, which addresses both carbon emissions and cost reduction. Detailed information about the algorithm, methodology and computational studies is investigated. The research problem encompasses various practical aspects related to routing optimization in e-commerce logistics, aiming for sustainable development.

Drawing on the resource-based view (RBV) and structure–conduct–performance (SCP) paradigm perspectives, this study aims to investigate the influence of the innovation and technical capabilities of exporting organisations on their export performance moderate by competitive intensity.

Primary data were collected from 162 Chinese manufacturer–exporter companies operating across China. The conceptual framework of this study, which incorporated the impact of RBV and SCP paradigm determinants on export performance through the interaction effect of competitive intensity, was tested using structural equation modelling (Smart-PLS).

Results show that the technical and innovation capabilities can increase its export success in international markets. Furthermore, this research finds that competitive intensity moderates the positive relationship between technical capability and export performance but not the relationship between innovation capability and export performance.

This study presents a holistic assessment of the export performance of manufacturer–exporter enterprises by accounting for the overlooked effect of organisational capabilities through the moderating function of competitive intensity. This study has far-reaching consequences for export academics and practitioners, including the fundamental concept of an internationalizing small- and medium-sized enterprises, especially the manufacturers.

Following the positive call for a special issue on Architectural Pedagogies and Sustainable Development Goals (SDGs), the purpose of this overview article is to contextualise reflections on nine selected articles, within recent efforts made by professional organisations, which aspire to blend sustainable development into the collective psyche of both academics and future professionals.

This article adopts four lines of inquiry by capturing key insights on the place of sustainable design knowledge in architectural education validation and accreditation at both national and global scales; presenting analytical narratives on the recent global efforts that embrace excellence in architectural pedagogy through addressing SDGs; elucidating the two knowledge spaces, centred on pedagogy and sustainability, which are strengthened and supported by Archnet-IJAR, and offering reflections on the nine articles published in this special issue that aims at integration of the two knowledge spaces.

Contextualisation and reflective narratives offer insights into current efforts and demonstrate a clear commitment of professional organisations to embed values relevant to SDGs. Efforts of the Education Commission of the International Union of Architects and the UNESCO-UIA Validation Council of Architectural Education appear to have advanced significantly over recent years with a clear prospect for a sustainable future. The nine articles published in this special issue respond clearly to the goal of Quality Education (SDG4), but not all of them have addressed the goals related to Good Health and Well-being (SDG3) and Sustainable Cities and Communities (SDG11), and their place in architectural pedagogy. However, they take a step further to address aspects of climate change, globalisation, sustainable architecture and urbanism, social sustainability, global north/global south dialectics and decolonisation.

The findings offer opportunities to recognise efforts by professional organisations, map key pedagogical experiments into these efforts, while providing lessons learned from best practices aiming to effectively integrate SDGs into architectural pedagogy.

No serious effort has been made to articulate the integration of SDGs into architectural education at the level of research or design studio pedagogical practice. Addressing architectural pedagogies and sustainable development is predicated on the fact that there is very little written or known on integrating SDGs into architectural education and design pedagogy. Understanding, appreciating, and sharing various efforts and approaches to incorporate SDGs into architectural pedagogy is a key step towards a sustainable future.

As the new frontier in online healthcare innovation, mobile health consultation (MHC) is transforming how traditional healthcare is delivered. Despite being known on a large scale for its benefits, MHC still faces consumer resistance. MHC is a technology-enabled service, so an in-depth analysis of consumer resistance from the perspective of technology is crucial to enhance service adoption. This study sought to determine the mechanism by which two information technology (IT)-specific traits – IT affordance and IT identity – influence consumer resistance to MHC during consumer–platform interactions.

We used the Credamo platform to gather data from 786 users with medical consulting experience to validate the resulting relationships.

Based on partial least squares structural equation modeling, three of the six IT affordances (visibility, searching and guidance shopping) exerted a significant positive influence on IT identity, while trigger attending and association affordance had no significant effect on IT identity. Persistence affordance was negatively associated with IT identity, and IT identity negatively influenced consumer resistance to MHC.

Academically, this empirical paper primarily contributes to the MHC literature and the theory of IT affordance and IT identity. Practically, several valuable guidance for MHC platforms is provided.

The uncertainty of remanufacturing parts is a key factor affecting the quality of remanufactured products. Therefore, the purpose of this paper is to measure the uncertainty of remanufactured parts and study the coupling mechanism of reassembly quality.

First, uncertainty of remanufactured parts is analyzed, and the uncertainty measure model for remanufacturing parts based on entropy is constructed. Second, the nonlinear mapping model between the uncertainty and reassembly quality were studied using Gauss-Newton iterative method to reveal the coupling mechanism between uncertainty of remanufacturing parts and reassembly quality. Finally, the model is verified in the reassembly process of remanufacturing cylinder head.

The method can guide reassembly operations to improve the reassembly quality with uncertainty of remanufactured parts.

This study provides practical implications by developing a multivariate nonlinear mapping model for reassembly quality based on entropy to determine the uncertainty factors that affect the reassembly quality significantly and then correct the reassembly operation to better optimize the allocation of remanufacturing production resources. The study also theoretically contributes to reveal the coupling mechanism of reassembly quality with the uncertainty of remanufactured parts.

This meta-analytical review aims to clarify the relationships between three bundles of human resource management (HRM) practices—competency-enhancing, motivation-enhancing and opportunity-enhancing—and organizational innovation by addressing two questions: (a) Which types of HRM bundles are most strongly related to different forms of innovation (i.e. process and product innovation)? And (b) Which mechanism provides a stronger explanation for the positive effects of HRM bundles on innovation?

Based on data from 103 studies, a meta-analysis was conducted to quantitatively summarize existing HRM–innovation studies at the organizational level.

The results showed that the competency-enhancing bundle was more positively related to product innovation than the motivation-enhancing and opportunity-enhancing bundles. The opportunity-enhancing bundle was most strongly associated with process innovation. The authors further found that knowledge management capability (KMC) and employee motivation mediated the positive relationship between the three HRM bundles and innovation outcomes. In comparing the two mechanisms, this review suggests that KMC better explains both the impact of the competency-enhancing HRM bundle on product innovation and the effect of the opportunity-enhancing bundle on process innovation.

Based on behavioral and knowledge management perspectives, this study takes a sub-bundle approach to providing an integrative review by comparing the direct effects and mediating paths of HRM bundles on product and process innovation.

Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been conducted on the multi-class sentiment analysis of tweets. The purpose of this paper is to consider the popularity of emojis on Twitter and investigate the feasibility of an emoji training heuristic for multi-class sentiment classification of tweets. Tweets from the “2016 Orlando nightclub shooting” were used as a source of study. Besides, this study also aims to demonstrate how mapping can contribute to interpreting sentiments.

The authors presented a methodological framework to collect, pre-process, analyse and map public Twitter postings related to the shooting. The authors designed and implemented an emoji training heuristic, which automatically prepares the training data set, a feature needed in Big Data research. The authors improved upon the previous framework by advancing the pre-processing techniques, enhancing feature engineering and optimising the classification models. The authors constructed the sentiment model with a logistic regression classifier and selected features. Finally, the authors presented how to visualise citizen sentiments on maps dynamically using Mapbox.

The sentiment model constructed with the automatically annotated training sets using an emoji approach and selected features performs well in classifying tweets into five different sentiment classes, with a macro-averaged F-measure of 0.635, a macro-averaged accuracy of 0.689 and the MAEM of 0.530. Compared to those experimental results in related works, the results are satisfactory, indicating the model is effective and the proposed emoji training heuristic is useful and feasible in multi-class TSA. The maps authors created, provide a much easier-to-understand visual representation of the data, and make it more efficient to monitor citizen sentiments and distributions.

This work appears to be the first to conduct multi-class sentiment classification on Twitter with automatic annotation of training sets using emojis. Little attention has been paid to applying TSA to monitor the public’s attitudes towards terror attacks and country’s gun policies, the authors consider this work to be a pioneering work. Besides, the authors have introduced a new data set of 2016 Orlando Shooting tweets, which will be made available for other researchers to mine the public’s political opinions about gun policies.

In accordance with Bagozzi’s self-regulation theory, the aim of this paper is to explore the enablers and inhibitors of continuance intention from the perspective of bullet curtain, a new form of commentary on online video websites.

A total of 350 questionnaires were collected for the final analysis (covering 101 questionnaires for the pilot test) from China’s bullet curtain website. To analyze the model, the authors adopted SmartPLS 3.2, a structural equation modeling software.

As the results suggest, there is a positive correlation between satisfaction and continuance intention and a negative association between social network fatigue and continuance intention. In addition, synchronicity between the comments and video content, a dimension of synchronicity proposed in this study, improves the satisfaction. Furthermore, information overload significantly intensify social network fatigue.

The results help bullet curtain providers offer better interactive environment and improve websites’ functions to stimulate users.

By combining positive effect and negative effect of commentary, this study investigates Bagozzi’s theory in a context of bullet curtain. Besides, combinations of these factors help to gain insights in how the bullet curtain works in online video websites. These offer useful guidelines for managers to optimize a better system.