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The study explores how mobile governance affects the administrative burden on older adults, focusing on learning, psychological and compliance costs.

Using attribution theory, the research employs a quantitative research design, utilizing surveys to gather data from 516 older adults across three cities in China: Quzhou, Wuhan and Shanghai. The study examines how intrinsic factors and extrinsic factors of m-government interfaces impact older adults’ administrative burden.

Perceived complexity increases learning, psychological and compliance costs for older adults. Personalization and high-quality information decrease these costs, enhancing user satisfaction. Visual appeal decreases anxiety and psychological costs.

This research links attribution theory with m-government’s administrative burden on older adults, offering new insights into optimizing m-government to serve older adults better.

The single-supplier multi-retailer cold chain is a widely adopted type of supply chain in the real-world food industry. This paper aims to consider the problem of effectively designing and managing a single-supplier multi-retailer cold chain for fresh produce with deterministic demand to minimize the total cost, which includes cooling, loss of value and carbon emission costs.

The global stability index (GSI) method and the non-Arrhenius model are integrated to describe the behavior of food quality degradation. The power-of-two (PoT) policy is adopted in determining the coordinated replenishment policies for the suppliers and retailers, and an appropriate wholesale price structure that can achieve the coordination of the chain is presented.

The properties of the cold chain are uncovered, and an appropriate wholesale price scheme that achieves chain coordination with the optimal PoT decision is provided. In the numerical examples, different scenarios are investigated, and it is found that the cold chain parameters influence the optimal decisions in certain ways.

The PoT policy – an efficient policy to determine the replenishment strategy – has not been adopted in finding the solution of a single-supplier multi-retailer cold chain in the literature. Also, no study has compared the uncoordinated and coordinated cold chain. Moreover, in the existing literature, the wholesale price is usually a constant rather than having a coordinated scheme. This research aims to fill these research gaps.

This study expanded the model of technology acceptance and investigated how the relationship between usefulness, ease of use, efficiency, personalization, safety and security and behavioural intention differ on Gen Z and silver tourists toward smart hotel. This study further applies multiple group analysis to examine whether there are substantial differences among these two groups of respondents.

Using an online survey, this study was undertaken with Gen Z and silver tourists in mainland China who had stayed in smart hotel over the past 12 months. A total of 474 valid responses were collected. Structural equation modelling and multigroup analysis were employed to test the proposed relationships.

This study revealed that personalization did not affect the behavioural intention among Gen Z tourists, meanwhile, there is no positive relationship between usefulness, efficiency and behavioural intention on silver group. Additionally, the findings revealed that there are no substantial differences among Gen Z (digital natives) and silver customers (digital immigrants) regarding smart hotel behavioural intentions.

This study offers strategic guidance for hotel managers to design and reposition smart hotel based on different customer sectors. Further, important implications for smart devices manufacturers are also provided to improve the functioning of hotel service robots.

This is the first study to compare the drivers and outcomes of behavioural intentions among different age groups of tourists toward smart hotels.

The underground logistics system (ULS) is noted to be an innovative delivery alternative that confers benefits such as improved logistics efficiency, reduced traffic congestion and better environmental protection for society. Consumer acceptance is crucial for the widespread application of ULS. Hence, this study aims to explore the drivers affecting consumers’ willingness to adopt an ULS anchored on the uses and gratification theory.

An online survey was implemented among 551 Singapore citizens and structural equation modeling was adopted to examine the theoretical model.

The findings suggest that most gratification variables (i.e. hedonic gratification, environmental protection gratification (EPG) and social gratification), mediated by perceived well-being and conscious attention, have significant effects on consumer adoption of the ULS. Moreover, as shown in the results of total effects, well-being perception exerts the largest impact on consumers’ adoption of ULS, followed by conscious attention, EPG, social gratification, hedonic gratification and convenience gratification.

This study contributes to enriching current theoretical research on consumers’ willingness to accept ULS, and providing several practical implications for logistic service providers and the government to promote consumers’ adoption of ULS.

The imperative for sustainable energy systems is increasingly pressing as the world transitions toward renewable energy sources. Among these, triboelectric nanogenerators (TENGs) have emerged as a viable option for wind energy harvesting. However, they face significant challenges, including material durability under varying wind conditions; the intricacy of material selection and performance; and the trade-off between wear resistance and triboelectric efficiency. This study aims to address the above issues.

Herein, a mode-switch TENG (MS-TENG) was designed to overcome these limitations and serve as a self-powered energy solution for Internet of Things (IoT) sensor networks. The MS-TENG incorporates a multi-stage functional layer and an automatic mode-switching mechanism between contact and non-contact operation, thereby enhancing both efficiency and durability.

It is demonstrated that the MS-TENG achieves a maximum instantaneous output power of 0.069 mW with minimal mechanical wear, effectively capturing wind energy. Its capability to charge capacitors and power a range of electronic devices, such as temperature and humidity sensors, electronic watches and water immersion guards, underscores its practical utility across diverse settings.

This research situates the MS-TENG as a pioneering technology in smart sensor applications for future energy-harvesting endeavors, optimizing energy acquisition under fluctuating wind conditions and reinforcing the sustainability of IoT networks.

Blockchain technology and its applications have recently received the attention of practitioners and academics. Visualizing the full impact these technologies will have on the world is challenging since their adoption is still in the early stages. This chapter explores how blockchain can disrupt the general business and financial world. Blockchain offers information transparency, live data synchronization, and immutable records that prevent fraud. Digital contracts and digital asset management may heavily depend on the development of blockchain and the adoption of smart contracts. Smart contracts can execute financial transactions automatically and enforce all parties' obligations without needing an intermediary and its cost. They can increase speed and simplify processes, reducing licensing ticketing costs and overhead charges. Blockchain also offers technology adoption solutions, like fair payment, cloud storage, smart contracts for financial assets, and international transactions with bilateral double taxation. It has further facilitated the creation of decentralized finance.

Effective information security management (ISM) contributes to building a healthy organizational digital ecology. However, few studies have built an analysis framework for critical influencing factors to discuss the combined influence mechanism of multiple factors on ISM performance (ISMP). This study aims to explore the critical success factors and understand how these factors contribute to ISMP.

This study used a mixed-method approach to achieve this study’s research goals. In Study 1, the authors conducted a qualitative analysis to take a series of International Organization for Standardization/International Electrotechnical Commission standard documents as the basis to refine the critical factors that may influence organizations’ ISMP. In Study 2, the authors built a research model based on the organizational control perspective and used the survey-based partial least squares-based structural equation modeling (PLS-SEM) approach to understand the relationships between these factors in promoting ISMP. In Study 3, the authors used the fuzzy set qualitative comparative analysis (fsQCA) method to empirically analyze the complex mechanisms of how the combinations of the factors affect ISMP.

The following three research findings are obtained. First, based on the text-based qualitative analysis, the authors refined the critical success factors that may increase ISMP, including information security policies (ISP), top management support (TMS), alignment (ALI), information security risk assessment (IRA), information security awareness (ISA) and information security culture (ISC). Second, the PLS-SEM testing results confirmed TMS is the antecedent variable motivating organization’s formation (ISP) and information control (ISC) approaches; these two types of organization control approaches increase IRA, ISA and ALI and then promote ISMP directly and indirectly. Third, the fsQCA testing results found two configurations that can achieve high ISMP and one driving path that leads to non-high ISMP.

This study extends knowledge by exploring configuration factors to improve or impede the performances of organizations’ ISM. To the best of the authors’ knowledge, this study is one of the first to explore the use of the fsQCA approach in information security studies, and the results not only revealed causal associations between single factors but also highlighted the critical role of configuration factors in developing organizational ISMP. This study calls attention to information security managers of an organization should highlight the combined effect between the factors and reasonably allocate organizational resources to achieve high ISMP.

Deep learning techniques are unavoidable in a variety of domains such as health care, computer vision, cyber-security and so on. These algorithms demand high data transfers but require bottlenecks in achieving the high speed and low latency synchronization while being implemented in the real hardware architectures. Though direct memory access controller (DMAC) has gained a brighter light of research for achieving bulk data transfers, existing direct memory access (DMA) systems continue to face the challenges of achieving high-speed communication. The purpose of this study is to develop an adaptive-configured DMA architecture for bulk data transfer with high throughput and less time-delayed computation.

The proposed methodology consists of a heterogeneous computing system integrated with specialized hardware and software. For the hardware, the authors propose an field programmable gate array (FPGA)-based DMAC, which transfers the data to the graphics processing unit (GPU) using PCI-Express. The workload characterization technique is designed using Python software and is implementable for the advanced risk machine Cortex architecture with a suitable communication interface. This module offloads the input streams of data to the FPGA and initiates the FPGA for the control flow of data to the GPU that can achieve efficient processing.

This paper presents an evaluation of a configurable workload-based DMA controller for collecting the data from the input devices and concurrently applying it to the GPU architecture, bypassing the hardware and software extraneous copies and bottlenecks via PCI Express. It also investigates the usage of adaptive DMA memory buffer allocation and workload characterization techniques. The proposed DMA architecture is compared with the other existing DMA architectures in which the performance of the proposed DMAC outperforms traditional DMA by achieving 96% throughput and 50% less latency synchronization.

The proposed gated recurrent unit has produced 95.6% accuracy in characterization of the workloads into heavy, medium and normal. The proposed model has outperformed the other algorithms and proves its strength for workload characterization.

Online patient reviews are of considerable importance on online health platforms. However, there is limited understanding of how these reviews are generated and their impact on patients' choices of physicians. Therefore, this study aims to investigate the antecedents and consequences of online patient reviews on online health platforms.

This study introduced an online interaction model with multiple stages aimed at examining how physicians' service quality affects patients' review behavior and, consequently, influences patients' choices of physicians.

The results revealed that technical quality and emotional care significantly influenced the effort that patients exert and their use of positive emotional words when writing reviews, which, in turn, positively influenced patients' selection of physicians. Moreover, it was found that the voice channel had a significant moderating effect on the relationship between physician service quality and patient review behavior.

The study’s findings can help online health platform managers improve the platform system by optimizing the integrated text and voice interaction functions. The findings can also support physicians in improving service quality, managing online reviews and attracting patients’ choices.

This study enriches the literature on physician service quality, patient online reviews and choices in online health platforms. Furthermore, this study offers a novel perspective on the social exchange process in online healthcare settings by highlighting the role of media in shaping physician–patient interactions.

Social networking services (SNS) empower users with a robust capability to connect with others and manage their social relationships. However, as the size of users’ social networks increases, coupled with the inherent boundary-spanning technical features of SNS, users are faced with unprecedented role stresses. This, in turn, leads to maladaptive lurking decisions. This study delves into the mechanism of this technology-induced decision-making process among SNS users.

Survey data were collected from 491 Chinese WeChat Moment users. The model and hypotheses testing were conducted using SmartPLS 4.0.

Our findings indicate that both social network size and boundary spanning have a positive influence on role conflict and role overload. Both role conflict and role overload significantly contribute to SNS fatigue, which further intensifies users’ lurking intention. Furthermore, SNS fatigue fully mediated the relationship between role conflict and lurking intention, and partially mediated the relationship between role overload and lurking intention.

Our study offers a fresh viewpoint for comprehending lurking behaviors on SNS, furnishing practical insights for platform providers. Additionally, it paves the way for future research into the deeper mechanisms driving SNS lurking behaviors, by providing a novel construct (i.e. boundary spanning) to distinguish and measure the unique social environment of SNS.