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The aim of this study is to determine the impact of different dimensions of consumer engagement in social media on firm performance in social media.

Beyond likes and comments, combined with the interactive behavior of consumer engagement with firms on social media, we proposed a set of metrics for consumer engagement on social media, namely personal engagement, user-interactive engagement, and fan-interactive engagement. We used the fixed-effect model and validated the impact of consumer engagement in different dimensions on firm performance.

The result shows that personal engagement and user-interactive engagement significantly correlate with firm performance; however, the same effect was not observed in fan-interactive engagement.

Prior researches on consumer engagement in social media are mainly about consumer engagement in firm-initiated social media page. In this study, we consider the consumer engagement behavior in firm-initiated and consumer-initiated social media pages, then validate the impact of different dimensions of consumer engagement on firm performance.

This study caries a survey approach using the expert's interview and literature to select the important criteria to select and evaluate the third-party reverse logistics providers (3PRLPs) in manufacturing companies. In total, 16 criteria are selected to evaluate 3PRLPs, and these criteria are classified on the basis of three main elements of sustainable growth, including economic, social and environmental development. Therefore, a hybrid decision-making approach is utilized to evaluate and rank the 3PRLPs in manufacturing companies.

This paper proposes a new decision-making approach using the projection model and entropy method under the interval-valued intuitionistic fuzzy set to assess 3PRLPs based on sustainability perspectives. A survey approach using the literature review and experts' interview is conducted to select the important criteria to select and evaluate 3PRLPs in manufacturing companies. To assess the criteria weight, the entropy method is used. Further, the projection model is applied to prioritize the 3PRLPs option. Sensitivity analysis and comparison process are performed in order to test and validate the developed method.

The presented methodology uses the benefits to determine the former for measuring the parameters considered and the latter for rating the 3PRLPs alternatives. A case study is taken to 3PRLPs in the manufacturing industry to illustrate the efficiency of the introduced hybrid method. The findings of this study indicate that when facing uncertainties of input and qualitative data, the proposed solution delivers more viable performance and therefore is suitable for wider uses.

The conception of the circular economy (CE) comes from the last 4 decades, and in recent years, tremendous attention has been carried out on this concept, partially because of the availability of natural resources in the world and changes in consumption behaviour of developed and developing nations. Remarkably, the sustainable supply chain management concepts are established parallel to the CE foundations, grown in industrial practice and ecology literature for a long time. In fact, to reduce the environmental concerns, sustainable supply chain management seeks to diminish the materials' flow and minimize the unintentional harmful consequences of consumption and production processes. Customers and governments are becoming increasingly aware of the environmental sustainability in the CE era, which allows businesses to concentrate more resources on reverse logistics (RLs). However, most manufacturing enterprises have been inspired to outsource their RL operations to competent 3PRLPs due to limited resources and technological limitations. In RL outsourcing practices, the selection of the best 3PRLP is helpfully valuable due to its potential to increase the economic viability of enterprises and boost their long-term growth.

This paper aims at fabricating large metallic components with high deposition rates, low equipment costs through wire and wire and arc additive manufacturing (WAAM) method, in order to achieve the morphology and mechanical properties of manufacturing process, a bead morphology prediction model with high precision for ideal deposition of every pass was established.

The dynamic response of the process parameters on the bead width and bead height of cold metal transfer (CMT)-based AM was analyzed. A laser profile scanner was used to continuously capture the morphology variation. A prediction model of the deposition bead morphology was established using response surface optimization. Moreover, the validity of the model was examined using 15 groups of quadratic regression analyzes.

The relative errors of the predicted bead width and height were all less than 5% compared with the experimental measurements. The model was then preliminarily used with necessary modifications, such as further considering the interlayer process parameters, to guide the fabrication of complex three-dimensional components.

The morphology prediction of WAAMed bead is a critical issue. Most research has focused on the formability and defects in CMT-based WAAM and little research on the effect of process parameters on the morphology of the deposited layer in CMT-based WAAM has been conducted. To test the sensitivities of the processing parameters to bead size, the dynamic response of key parameters was investigated. A regression model was established to guide the process parameter optimization for subsequent multi-layer or component deposition.

Social media is still influencing consumers and is extending social commerce (S-Commerce) use. Different social media activities can influence the users' trust and e-satisfaction at different levels, which in turn influence the purchase intentions. This is evident for the food and beverage industry as S-Commerce mediated by social media can help realise a shorter time to market and meet buyer demands. In addition, credibility factors may influence trust and purchase intentions. Understanding the various factors of influence such as social constructs, namely ratings, reviews and referrals; design constructs such as credibility and features and behavioural constructs such as trust, satisfaction and motivation; and analysing the relationship between these factors and how they influence purchase intentions can provide deeper insights into S-Commerce research, decision-making process and purchase intentions particularly from a food and beverage context.

Drawing on trust through social media activities and surface credibility as well as e-commerce satisfaction, the authors have proposed a research model to investigate the purchase intention of consumers in S-Commerce platforms. Survey data were collected from six countries in Asia and analysed using SEM-PLS.

Results indicated that both trust and surface credibility significantly influence e-commerce satisfaction leading to purchase intention. Furthermore, surface credibility, which is a novel predictor for purchase intention in S-Commerce context, is highly significant on e-commerce satisfaction. Besides, encouraged by surface credibility, it was identified that trust significantly affects e-commerce satisfaction and results in purchase intention. This research adds contribution to theory and practice in S-Commerce stream as discussed at the end of the paper.

The results of this research contribute to the S-Commerce literature and have practical implications for practitioners in the food and beverage industry. As such, focussing on these constructs, this paper analyses the relationship between the social media activities, trust, e-commerce satisfaction, surface credibility and intention to buy.

The purpose of this paper is to investigate the influence of perceived brand leadership of an e-commerce website on satisfaction and repurchase intention. Moreover, the different roles of gender and age were explored in the proposed model.

An online survey was administered to Chinese consumers (n=476) who have purchased products on e-commerce websites. Using SmartPLS 3.0 software, a partial least squares structural equation modeling analysis was conducted in this study.

The results showed that all factors of perceived brand leadership (i.e. quality, value, innovativeness and popularity) have positive influences on satisfaction, and in turn satisfaction significantly affects repurchase intention. Also, value and popularity have positive influences on repurchase intention. In addition, gender differences were found in the proposed model. More specifically, the influence of quality on satisfaction was stronger for male consumers, while the impact of popularity on satisfaction was stronger for female. In terms of age differences, the influence of quality on satisfaction was stronger for the consumers over 40 years old as compared to the younger consumers (i.e. the 20s). Moreover, the influence of innovativeness on satisfaction and repurchase intention was stronger for the 20s consumers as compared to the consumers who are over 40 years old.

This study attempts to apply the concept of brand leadership to the e-commerce setting by addressing differential consumption decision-making process. In addition, different gender and age groups reveal unique preferences and consumption patterns.

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.

Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.

The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.

This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.

The purpose of this paper is to investigate the mechanism of building trust during the transition from online payment to mobile payment, as well as to examine the effect of trust on the satisfaction and continuance intention of mobile payment users. Based on trust transfer theory, this study proposes that trust in online payment (i.e. trust in source) and two source-target relationship factors, namely, perceived similarity and entitativity, affect trust in mobile payment (i.e. trust in target). In turn, the resulting trust influences user satisfaction and continuance intention toward mobile payment in an online-mobile payment context.

The model was empirically tested on data collected from 219 mobile payment users of a famous payment enterprise in China.

The results indicated that the trust transfer process positively influences the continuance intention of mobile payment through satisfaction. Satisfaction is an important factor affecting continuance intention. Moreover, trust in online payment, perceived similarity, and perceived entitativity between online and mobile payments can positively influence trust in mobile payment.

This study investigates the post-adoption usage of mobile payment from the trust transfer perspective. It focuses on the trust-building process and emphasizes the importance of trust on the continuance intention toward mobile payment in an online-mobile payment context.

This study aims to review the recent advancements in high entropy alloys (HEAs) called high entropy materials, including high entropy superalloys which are current potential alternatives to nickel superalloys for gas turbine applications. Understandings of the laser surface modification techniques of the HEA are discussed whilst future recommendations and remedies to manufacturing challenges via laser are outlined.

Materials used for high-pressure gas turbine engine applications must be able to withstand severe environmentally induced degradation, mechanical, thermal loads and general extreme conditions caused by hot corrosive gases, high-temperature oxidation and stress. Over the years, Nickel-based superalloys with elevated temperature rupture and creep resistance, excellent lifetime expectancy and solution strengthening L12 and γ´ precipitate used for turbine engine applications. However, the superalloy’s density, low creep strength, poor thermal conductivity, difficulty in machining and low fatigue resistance demands the innovation of new advanced materials.

HEAs is one of the most frequently investigated advanced materials, attributed to their configurational complexity and properties reported to exceed conventional materials. Thus, owing to their characteristic feature of the high entropy effect, several other materials have emerged to become potential solutions for several functional and structural applications in the aerospace industry. In a previous study, research contributions show that defects are associated with conventional manufacturing processes of HEAs; therefore, this study investigates new advances in the laser-based manufacturing and surface modification techniques of HEA.

The AlxCoCrCuFeNi HEA system, particularly the Al0.5CoCrCuFeNi HEA has been extensively studied, attributed to its mechanical and physical properties exceeding that of pure metals for aerospace turbine engine applications and the advances in the fabrication and surface modification processes of the alloy was outlined to show the latest developments focusing only on laser-based manufacturing processing due to its many advantages.

It is evident that high entropy materials are a potential innovative alternative to conventional superalloys for turbine engine applications via laser additive manufacturing.