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Monetary incentives have been widely adopted by brands to promote consumer engagement in their brand communities on social networking sites. This paper aims to explore how the interactions triggered by an emerging monetary incentive, red packets, affect consumers’ brand attitude in the context of WeChat brand groups (WCBGs).

According to whether brands ask for commercial returns from consumers, two types of interactions were identified, namely, exchange red packet interaction (ERPI) and communal red packet interaction (CRPI). The corresponding influences on brand attitude were examined in three experiments.

Compared to CRPIs, ERPIs elicit greater normative community pressure, inducing a less favorable brand attitude. Moreover, this impact is moderated by the time frame of brand communities. In the long-term WCBGs, a significant difference exists between ERPIs and CRPIs, while such difference attenuates or even disappears in short-term WCBGs.

When using red packets as an engagement strategy, brand managers should be alert to their potential negative influence. Specifically, in short-term brand communities, ERPIs enable managers to acquire commercial returns without hurting brand attitude. In long-term brand communities, managers are advised to implement CRPIs to foster a positive brand attitude.

This study investigates red packet interactions in brand communities, which have been widespread but unexplored. The results expand the literature by addressing the undermining effect of ERPI and the moderating effect of the time frame.

This study aims to provide a conceptual framework for exploring the relationship between online game product engagement and online brand community engagement and how these two types of customer engagement affect subsequent offline benefit for customers and online and offline benefits for firms. This study also investigates the antecedents of online game product engagement from the virtual experience perspective.

This study collected data from online gamers in Taiwan. Of the 580 responses, 548 were valid. Smart PLS 3 was used to test the measurement model and the hypotheses in the research model.

The conceptual model is supported. First, the findings show that learning, entertainment, flow and social interaction play key roles in explaining online game product engagement. Second, online game product engagement has a positive effect on online brand community engagement. Finally, online game product engagement and online brand community engagement are crucial drivers of customers’ offline benefit and firms’ online and offline benefits.

Four contributions are made by this study. First, this study explores firms’ online benefit (virtual item purchase intention) and offline benefits, including licensed product and co-branded product purchase intention. Second, this study explores the customer’s offline benefit (offline skill development). Third, it focuses on two types of customer engagement, including online game product engagement and online brand community engagement, and explores the relationship between them. Finally, the concept of virtual experience is used to explore the antecedents of online game product engagement.

This study investigates the use of gamification in promoting the silver generation's adoption of mobile payment technology through the gamified cultural practice of gifting red packets. It considers the effectiveness of using gamification in a cultural context to promote technology acceptance among older adults. This crossover between digital technology and cultural traditions brings unique gaming elements to the adoption of technology.

Drawing upon technology acceptance Model (TAM) and prospect theory, a research model is evaluated using structural equation modeling. Data were collected via survey from elderly consumers who are current users of WeChat but are yet to use its mobile payment functions.

The results reveal the perceived effectiveness of gamification is determined by the perceived enjoyment of the game and contributes to users' attitude development, directly and through its perceived usefulness. Perceived risks were identified as a barrier to converting positive attitude into adoption intention.

The findings contribute to the conceptualization and understanding of the effectiveness of gamification in technology adoption, specifically among the silver generation.

In contrast with previous gamification studies on gamified experience, this study introduces a new conceptualization of the perceived effectiveness of gamification and its measurement. This study validates game engagement as being effective in encouraging seniors to adopt a technology. In an era of an aging population where digitization is a norm, improving the digital literacy and digital inclusion of elders by encouraging them to adopt technology is essential to developing a more accessible and inclusive social environment.

In this research, the authors demonstrate the advantage of reinforcement learning (RL) based intrusion detection systems (IDS) to solve very complex problems (e.g. selecting input features, considering scarce resources and constrains) that cannot be solved by classical machine learning. The authors include a comparative study to build intrusion detection based on statistical machine learning and representational learning, using knowledge discovery in databases (KDD) Cup99 and Installation Support Center of Expertise (ISCX) 2012.

The methodology applies a data analytics approach, consisting of data exploration and machine learning model training and evaluation. To build a network-based intrusion detection system, the authors apply dueling double deep Q-networks architecture enabled with costly features, k-nearest neighbors (K-NN), support-vector machines (SVM) and convolution neural networks (CNN).

Machine learning-based intrusion detection are trained on historical datasets which lead to model drift and lack of generalization whereas RL is trained with data collected through interactions. RL is bound to learn from its interactions with a stochastic environment in the absence of a training dataset whereas supervised learning simply learns from collected data and require less computational resources.

All machine learning models have achieved high accuracy values and performance. One potential reason is that both datasets are simulated, and not realistic. It was not clear whether a validation was ever performed to show that data were collected from real network traffics.

The study provides guidelines to implement IDS with classical supervised learning, deep learning and RL.

The research applied the dueling double deep Q-networks architecture enabled with costly features to build network-based intrusion detection from network traffics. This research presents a comparative study of reinforcement-based instruction detection with counterparts built with statistical and representational machine learning.

Convivo is a VoIP system designed to provide reliable voice communication for poor quality networks, especially those found in rural areas of the developing world. Convivo introduces an original approach to maintain voice communication interaction in the presence of poor network performance: an Interface‐ Adaptation mechanism that adjusts the user interface to reduce the impact of high latency and low bandwidth networks. Interface modes facilitate turn taking for high latency connections, and help to sustain voice communication even with extremely low bandwidth or high error rates. An evaluation of the system, conducted in a rural community in the Dominican Republic, found that Interface‐Adaptation helped users to maintain voice communication interaction as network performance degrades. Transitions from full duplex to voice messaging were found particularly valuable. Initial results suggest that as users get more experience with the application they would like to manually control transitions based on feedback provided by the application and their own perceived voice quality.

China has been one of these countries that followed glocalization with the establishment of Chinese social media platforms, which adopt global trends and software patterns. WeChat has been a success story that at first emerged as a social communication tool but has extended to include commercial dynamics as well. Hence, this study aims to understand WeChat user’s general perceptions of the WeChat platform as a general social platform and as a commercial business platform.

In this study, the sample (n = 400) was obtained from a specific group of people who have had experiences with different WeChat tools and their payment systems. Nonrandom purposive sampling was used by considering its higher probability of representativeness. The online survey that was given to participants through the WeChat groups included 14 questions, in which eight questions are for demographics and general WeChat use, and six questions are for WeChat payment. After descriptive statistical analysis, comparison-based tests were conducted and interpreted accordingly.

Overall, the study participants had a high frequency of using WeChat’s messaging and moments features. Moreover, users perceive WeChat and its payment tools as unsecured or not secure enough. However, that perception did not affect their intention to continue adopting the app. Hence, regardless of the unsecure perception, study participants still had high usage of WeChat pay.

This paper provides an example from China that is known as a high-tech country, and there are a very few studies on the WeChat app despite their high number of users and daily financial transactions.

Student participation has been an important issue for information literacy (IL) teachings. The purpose of this paper is to promote active student participation in IL courses with Rain Classroom, an intelligent teaching tool.

Using mixed method research, the paper presents a practical case study of the author’s experiences with Rain Classroom to improve teaching and learning of IL.

The study shows that Rain Classroom helps implement problem-based learning, promote student participation in class interaction and optimize learning experience, which facilitates a shift of the IL course from passive to active learning.

It is known that university public courses have large class sizes (more than 50 students per class), and, therefore, class interaction is difficult to organize. So this is a big issue for the researchers to study.

The proposed Rain Classroom is a free teaching tool and can be used in other academic libraries to enhance active student participation in IL lessons.

The paper includes implications for improving interaction in large-size conference or trainings using Rain Classroom.

The existing literature has not traced the reports on using the Rain Classroom to enhance student participation in IL courses in academic libraries. This paper intends to fill this gap and share practical methods and experiences, deepening the application research of Rain Classroom.

The purpose of this paper is to provide a framework on how strategic philanthropy can be included in humanitarian supply chains delivery. This framework explains the modalities where strategic philanthropy can be successful when collaborating with key humanitarian supply chain actors.

A philanthropy delivery framework is developed based on the literature related to strategic philanthropy and humanitarian supply chains. The delivery framework is further validated with the real-life case study of a multinational firm during the 2011 Thai floods.

Procter and Gamble (P&G) was involved in the Thailand flood 2011 relief efforts in three phases: preparation, immediate response, and reconstruction phase. The company supported and distributed a water purifier through a non-governmental relief agency, the Princess Pa Foundation, under the Thai Red Cross Society, that enabled P&G to not only gain the trust of the targeted community during all the phases but in the continued usage of their water purifier after the event. Community leaders and P&G’s modern trade retailers played an important role in collaborating in this humanitarian supply chain to enable the successful delivery and usage of the donated water purifier.

This proposed delivery framework is appropriate for in-kind products and services philanthropy. The case study describes how strategic philanthropy can be implemented in a specific case, i.e. flood disaster.

Academia, practitioners, and companies who are involved in humanitarian reliefs may adopt and adapt this framework in order to enable a win-win situation for all stakeholders in the humanitarian supply chain.

The delivery framework suggests that firms can develop successful strategic philanthropy through systematic humanitarian supply chain collaboration. It explains how a company can operate its philanthropic programs through collaboration with others as well as describes how these different actors can work together.

The small area network for data communication within routers is suffering from storage of packet, throughput, latency and power consumption. There are a lot of solutions to increase speed of commutation and optimization of power consumption; one among them is Network-on-chip (NoC). In the literature, there are several NoCs which can reconfigurable dynamically and can easily test and validate the results on FPGA. But still, NoCs have limitations which are regarding chip area, reconfigurable time and throughput.

To address these limitations, this research proposes the dynamically buffered and bufferless reconfigurable NoC (DB2R NoC) using X-Y algorithm for routing, Torus for switching and Flexible Direction Order (FDOR) for direction finding between source and destination nodes. Thus, the 3 × 3 and 4 × 4 DB2R NoCs are made free from deadlock, low power and latency and high throughput. To prove the applicability and performance analysis of DB2R NoC for 3 × 3 and 4 × 4 routers on FPGA, the 22 bits for buffered and 19 bit for bufferless designs have been successfully synthesized using Verilog HDL and implemented on Artix-7 FPGA development bond. The virtual input/output chips cope pro tool has been incorporated in the design to verify and debug the complete design on Artix-7 FPGA.

In the obtained result, it has been found that 35% improvement in throughput, 23% improvement in latency and 47% optimization in area has been made. The complete design has been tested for 28 packets of injection rate 0.01; the packets have been generated by using NLFSR.

In the obtained result, it has been found that 35% improvement in throughput, 23% improvement in latency and 47% optimization in area has been made. The complete design has been tested for 28 packets of injection rate 0.01; the packets have been generated by using NLFSR.