Search results

This research focuses on developing a dual-nozzle slurry-based extrusion 3D printer capable of fabricating intricate zirconia structures. The designed 3D printer combines material extrusion and photopolymerization technologies to improve material diversity, precision and cost-effectiveness.

The 3D printer design incorporates ultraviolet curing to instantly cure extruded zirconia slurry thereby, eliminating the need for a step-wise curing procedure. Printing parameters were optimized to achieve high-quality prints, and supports made of polyethylene terephthalate glycol were used for intricate geometries. The printability and mechanical properties were evaluated for two different zirconia slurry compositions: 70 / 30 and 80 / 20 powder-to-resin weight percentages. The printed green body was subjected to a two-phase sintering process.

The 3D printer fabricated structures with features subtending angles greater than 50 degrees and a filling density above 80% without any supports. Shrinkage analysis showed the 80 / 20 composition resulted in higher density parts, with shrinkage ratios of 25.23%, 26.23% and 27.26% along the X, Y and Z axes, respectively. The sintered objects displayed hardness (1525 HV) and flexural strength (117 MPa), with minimal porosity.

This study demonstrates the development of a cost-effective dual-nozzle 3D printer that can effectively fabricate functional parts with complex material compositions and geometries that can cater to the futuristic requirements of high-end industries.

Body language is an integral part of interpersonal communication and exchange, which can convey rich emotions, intentions and information. However, how anchor’s body language works in live-streaming e-commerce (LSE) has yet to receive adequate attention. Based on dual systems theory of decision-making, this paper aims to explore the impact of anchor’s body language on the performance of LSE from the perspective of customer engagement behavior and to examine the moderating role of anchor’s relational social interaction.

The authors confirmed the theoretical model through empirical analysis of structured data from 1,415 actual livestreaming rooms from Douyin, as well as unstructured data of 418,939 min of video and audio, 1,985,473 words of text and 423,302 keyframe images.

The study found that anchor’s body language has a significant positive effect on the performance of LSE, and customer engagement behavior plays a partially mediating role. The moderating effect suggests that anchor’s relational social interaction and body language have substitution effects in enhancing customer engagement behavior and the performance of LSE, which reveals the substitution relationship between anchor’s verbal and nonverbal interactions in LSE.

This study is one of the earlier literature focusing on anchor’s body language, and the findings provide practical references for enhancing customer engagement behavior and achieving performance growth in LSE.

The purpose of this paper is to examine the influence of intelligent manufacturing on audit quality and its underlying mechanism as well as the variation in this influence across different types of organizations.

This research utilizes a difference-in-differences (DID) method to examine how enterprises that apply intelligent manufacturing choose auditors and impact their audit work. The study is based on 15,228 observations of Chinese-listed A-shares from 2011 to 2020.

(1) There is a strong correlation between intelligent manufacturing and audit quality. (2) This positive correlation is statistically significant only in state-owned enterprises (SOEs), those that have steady institutional investors and where the roles of the CEO and chairman are distinct. (3) Enterprises that have implemented intelligent manufacturing are more inclined to employ auditors who possess extensive industry expertise. The auditor's industry expertise plays a crucial role in ensuring audit quality. (4) The adoption of intelligent manufacturing also leads to higher audit fees and longer audit delay periods.

This paper validates the beneficial impact of intelligent manufacturing on improving corporate governance. In addition, it is recommended that managers prioritize the involvement of skilled auditors with specialized knowledge in the industry to ensure the high audit quality and the transparency of information in intelligent manufacturing enterprises.

This study builds upon previous research that has shown the importance of artificial intelligence in enhancing audit procedures. It contributes to the existing body of knowledge by examining how enterprise intelligent manufacturing systems (IMS) enhance audit quality. Additionally, this study provides valuable information on how to improve audit quality in the field of intelligent manufacturing by strategically selecting auditors based on resource dependency theory.

This paper aims to validates a framework using the Uses and Gratifications Theory (UGT) to study the effect of values, i.e. Functional Value (FV), Social Value (SV), Emotional Value (EV) and Monetary Value (MV), on the Patronage Intention (PI) of Social Network Users (SNU’s) with mediating role of Perceived Usefulness (PU).

A survey method was used to collect responses from 302 SNUs, and the variance-based structural equation method was used to understand the relationships among the constructs.

The results found a significant positive effect of FV and EV on Perceived Usefulness (PU) and MV and PU on Patronage intention (PI) of SNUs. Further, PU partially mediated the relationship of EV with PI.

This study used the UGT to understand the effect of values on the PI of SNUs. This research study contributes to the existing social networks/social media literature.

Despite increasing awareness among fashion consumers about the positive environmental and societal impacts of sustainable fashion as a viable alternative to fast fashion, their actual adoption behavior often diverges. This study aims to empirically investigate consumers’ resistance barriers to sustainable fashion clothing.

This study utilizes innovation resistance theory to examine the barriers to consumer intention to buy sustainable clothing. The study collected a large sample (N = 745) of fashion consumers from the USA and India to test a research model.

The study finds that value, social risk, tradition and image barriers significantly reduce consumers’ intentions to buy sustainable fashion clothing. Additionally, the findings highlight that environmental concern moderates the relationship between social risk barriers and buying intentions.

The study findings contribute to the existing sustainable fashion literature by highlighting the main barriers for sustainable clothing consumption and emphasizing the crucial role of social elements, economic values and the image of sustainable fashion products in shaping consumer behavior within the fashion landscape.

This study aims to investigate the mechanism of the influence of paradoxical thinking (PT), which characterizes the ability of college students to balance and integrate the conflict between hedonic and normative goals, on their campus low-carbon behaviors.

The conceptual model of “PT − Paradoxical salience (climate change concern, CCC) − Paradoxical acceptance (support for low-carbon behavioral norms, SN) − paradoxical resolution (campus low-carbon intentions and behaviors, CLCIs and CLCBs)” was developed. Then, it was tested by PLS-SEM using survey data obtained from 501 Chinese college students, and the relative importance of each factor of CLCBs was determined by the importance-performance map analysis method. Finally, a mechanistic difference analysis was conducted.

PT, CCC and SN have the potential to influence the CLCBs of college students, with each of the three factors showing approximately 40% room for improvement in their impact. There exists an influential pathway of “PT → CCC → SN → CLCIs → CLCBs.” Notably, PT exhibits a stronger direct influence on college students’ private-sphere CLCBs compared to the public-sphere CLCBs.

Colleges should integrate the development of PT into the foundational framework of the entire education for sustainable development curriculum, while emphasizing the provision of opportunities for training in PT through pedagogical methods, and PT training can be integrated across various social levels.

This study offers a paradox theoretical framework for comprehending and elucidating the decision-making process underlying personal low-carbon behaviors, and advances the quantitative research of microindividual paradox processing by effectively conceptualizing and measuring paradoxical salience and acceptance.

Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial for measuring the development progress and guiding continual improvements of HSM-GI. Since this process of HSM-GI can be regarded as complex and interactive, a holistic picture is often required to describe the interrelations of its antecedents and consequences. In this respect, this study aims to construct a causality network indicator system and proposes a synergy evaluation method for HSM-GI.

Firstly, based on the Driver force-State-Response (DSR) causal-effect framework, this study constructs a holistic indicator system to analyze the interactions between environmental and human concerns of HSM-GI. Secondly, owing to the imprecision of human cognition and synergy interaction in the evaluation process, a flexible hesitant fuzzy (HF) superiority-inferiority synergetic evaluation method is presented. This method quantifies the strengths of causal relationships and expresses the incentives and constraints attitudes of humans. Finally, the proposed framework is applied to six HSMs in the electronic technology industry.

The driving force and state of the HSM-GI system exhibit an upward trend, while the response continues to decline due to changing market demands. The order and synergy degree have shown an increasing trend during 2021–2023, particularly significant for BOE and Haier Smart Home. HSM-GI systems with higher scores mostly have functional coordination and a coherent synergy structure.

This study demonstrates the proposed approach’s applicability and assists policymakers in formulating targeted strategies for green innovation systems.

This paper aims to provide a full introduction, new classification, comparison and investigation of the challenges as well as applications of layerless 3D printing, which is one of the industry 4.0 pioneers.

Given the significance and novelty of uniform 3D printing, more than 250 publications were collected and reviewed in an unbiased and clear manner.

As a result, the majority of uniform parts printed in polymer form are known up to this point. In a novel division for better researchers’ comprehension, uniform printing systems were classified into three categories: oxygen inhibition (OI), liquid lubrication (LL) and photon penetration (PP), and each was thoroughly investigated. Furthermore, these three approaches were evaluated in terms of printing speed, precision and accuracy, manufacturing scale and cost.

The parameters of each approach were compared independently, and then a practical comparison was conducted among these three approaches. Finally, a variety of technologies, opportunities, challenges and advantages of each significant method, as well as a future outlook for layerless rapid prototyping, are presented.

The impact of enterprise social media (ESM) on employees is not always beneficial. The constant connectivity of ESM can trigger emotional issues, threatening employees' psychological states. This study aims to explore the potential risks of ESM usage on thriving at work by examining how ESM usage affects thriving and for whom this relationship is amplified.

Drawing on Affect Event Theory, this study proposes a research model for investigating the underlying mechanisms and boundary conditions of the negative impacts of different ESM usage patterns on employees' thriving at work. This study employed Smart-PLS 4.0 with structural equation modeling to analyze multi-wave survey data from 255 employees, testing the proposed model.

The results indicate the following: (1) ESM usage triggers employees' workplace fear of missing out (WFoMO), increasing their online vigilance and consequently hindering their thriving at work. (2) The impact of ESM usage on employees' WFoMO and thriving at work varies with their ambition levels, with high-ambition employees being more susceptible to negative effects and (3) Different types of ESM usage exert distinct effects on employees.

This study substantiates the potential negative impact of ESM usage on employees' thriving at work, contributing to the literature on the “dark side” of ESM usage and thriving at work. This study confirms the critical mediating role of emotion, offering a novel theoretical perspective on understanding the mechanisms linking ESM usage and its outcomes. Additionally, this study identifies the moderating role of employee ambition, complementing the boundary conditions of ESM usage.

The aim of this study is to evaluate Big Data Analytics (BDA) drivers in the context of food supply chains (FSC) for transition to a Circular Economy (CE) and Sustainable Operations Management (SOM).

Ten different BDA drivers in FSC are examined for transition to CE; these are Supply Chains (SC) Visibility, Operations Efficiency, Information Management and Technology, Collaborations between SC partners, Data-driven innovation, Demand management and Production Planning, Talent Management, Organizational Commitment, Management Team Capability and Governmental Incentive. An interpretive structural modelling (ISM) methodology is used to indicate the relationships between identified drivers to stimulate transition to CE and SOM. Drivers and pair-wise interactions between these drivers are developed by semi-structured interviews with a number of experts from industry and academia.

The results show that Information Management and Technology, Governmental Incentive and Management Team Capability drivers are classified as independent factors; Organizational Commitment and Operations Efficiency are categorized as dependent factors. SC Visibility, Data-driven innovation, Demand management and Production Planning, Talent Management and Collaborations between SC partners can be classified as linkage factors. It can be concluded that Governmental Incentive is the most fundamental driver to achieve BDA applications in FSC transition from linearity to CE and SOM. In addition, Operations Efficiency, Collaborations between SC partners and Organizational Commitment are key BDA drivers in FSC for transition to CE and SOM.

The interactions between these drivers will provide benefits to both industry and academia in prioritizing and understanding these drivers more thoroughly when implementing BDA based on a range of factors. This study will provide valuable insights. The results from this study will help in drawing up regulations to prevent food fraud, implementing laws concerning government incentives, reducing food loss and waste, increasing tracing and traceability, providing training activities to improve knowledge about BDA and focusing more on data analytics.

The main contribution of the study is to analyze BDA drivers in the context of FSC for transition to CE and SOM. This study is unique in examining these BDA drivers based on FSC. We hope to find sustainable solutions to minimize losses or other negative impacts on these SC.