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This study aims to investigate the factors driving viewers' purchase intention in live-streaming by incorporating stimuli–organism–response (S–O–R) framework and extroversion–introversion personality perspectives.

Data collected from 228 users on live-streaming platforms in Taiwan were used to test the proposed model. The partial least squares method was used to test the measurement and the structural models.

Product attractiveness and trust in streamer significantly impacts purchase intention. The results also reveal that interactivity, breadth of information and uniqueness of information significantly impact product attractiveness, whereas social presence, breadth of information and uniqueness of information positively affect trust in streamer. Furthermore, streamer attractiveness has a greater effect on the purchase intention of extroverts.

This study investigates how the features of media, message and streamer impact purchase intention through their reactions to live-streaming. This research is also one of the earliest studies to examine the moderating role of extroversion–introversion personality on purchase intention and its antecedents in live-streaming commerce.

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.

The development of digital technology has provided technical support to various industries. Specifically, Internet-based freight platforms can ensure the high-quality development of the logistics industry. Online freight platforms can use cargo transportation insurance to improve their service capabilities, promote their differentiated development, create products with platform characteristics and increase their core competitiveness.

This study uses a generalised linear model to fit the claim probability and claim intensity data and analyses freight insurance pricing based on the freight insurance claim data of a freight platform in China.

Considering traditional pricing risk factors, this study adds two risk factors to fit the claim probability data, that is, the purchase behaviour of freight insurance customers and road density. The two variables can significantly influence the claim probability, and the model fitting outcomes obtained with the logit connection function are excellent. In addition, this study examines the model results under various distribution types for the fitting of the claim intensity data. The fitting outcomes under a gamma distribution are superior to those under the other distribution types, as measured by the Akaike information criterion.

With actual data from an online freight platform in China, this study empirically proves that a generalised linear model is superior to traditional pricing methods for freight insurance. This study constructs a generalised linear pricing model considering the unique features of the freight industry and determines that the transportation distance, cargo weight and road density have a significant influence on the claim probability and claim intensity.

With the continuous development of the wind power industry, wind power plant (WPP) has become the focus of resource development within the industry. Site selection, as the initial stage of WPP development, is directly related to the feasibility of construction and the future revenue of WPP. Therefore, the purpose of this paper is to study the siting of WPP and establish a framework for siting decision-making.

Firstly, a site selection evaluation index system is constructed from four aspects of economy, geography, environment and society using the literature review method and the Delphi method, and the weights of each index are comprehensively determined by combining the Decision-making Trial and Evaluation Laboratory (DEMATEL) and the entropy weight method (EW). Then, prospect theory and the multi-criteria compromise solution ranking method (VIKOR) are introduced to rank the potential options and determine the best site.

China is used as a case study, and the robustness and reliability of the methodology are demonstrated through sensitivity analysis, comparative analysis and ablation experiment analysis. This paper aims to provide a useful reference for WPP siting research.

In this paper, DEMATEL and EW are used to determine the weights of indicators, which overcome the disadvantage of single assignment. Prospect theory and VIKOR are combined to construct a decision model, which also considers the attitude of the decision-maker and the compromise solution of the decision result. For the first time, this framework is applied to WPP siting research.

This study explores the influence of cultural heritage tourism perception on China's tourism image. It analyzes the role of the spiritual bond established between overseas Chinese youth and the motherland during their visit to the cultural heritage sites in China. This study constructs a theoretical model with 350 overseas Chinese youth as samples based on the identity theory, Stimulus-Organism-Response (S-O-R) theory, and Howard-Sheth model. The results show that cultural heritage tourism perception directly and positively promotes cultural identity among overseas Chinese youth. It is also indirectly and positively associated with their cultural identity through enhancing the tourism image. Cultural intelligence plays a positive moderating role between cultural heritage tourism perception and cultural identity. The results provide significant implications for developing cultural heritage tourism and cultural communication.

Bicycle sharing offers a novel way to create smart and sustainable mobility solutions for the future. The purpose of this study is to draw on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework for identifying the factors necessary to predict bike-sharing intention among users in India.

Data were collected through a questionnaire distributed across four major cities in India, and 515 responses were analyzed. A sequential approach was employed to analyze the data using Partial Least Square–Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA).

The findings from PLS analysis revealed that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation and price value are the salient variables that affect users' intentions to participate in bike sharing. In addition, based on fsQCA, six configurations of causal conditions are presented as intermediate solutions that produce the same results. Although antecedent conditions, such as habit and social influence, had an insignificant effect on individuals' BSI, they create conditions sufficient to encourage users' participation in bike sharing in combination with other variables.

A few limitations of this research and the implications of the findings in terms of theory and policy implications are also discussed.

The reported study is one of the earliest to explain bike-sharing adoption in India using the UTAUT 2 model.

Drawing upon the third-person effect (TPE) theory, this study focuses on two types of misinformation countering intentions (i.e. simple correction and correction with justification). Accordingly, it aims to (1) assess the tenability of the third-person perception (TPP) in the face of misinformation on social media, (2) explore the antecedents of TPP and its relationship with individual-level misinformation countering intentions and (3) examine whether the mediating process is contingent on different social media usage conditions.

An online survey was conducted with 1,000 representative respondents recruited in Mainland China in January 2022 using quota sampling. Paired t-test, multiple linear regression and moderated mediation analysis were employed to examine the proposed hypotheses.

Results bolster the fundamental proposition of TPP that individuals perceive others as more susceptible to social media misinformation than they are. The self-other perceptual bias served as a mediator between the perceived consequence of misinformation and misinformation countering (i.e. simple correction and correction with justification) intentions. Furthermore, intensive social media users were likely to be motivated to counter social media misinformation derived from the indirect mechanism.

The findings provide further evidence for the role of TPE in explaining misinformation countering intention as prosocial and altruistic behavior rather than self-serving behavior. Practically, promising ways to combat rampant misinformation on social media include promoting the prosocial aspects and beneficial outcomes of misinformation countering efforts to others, as well as reconfiguring the strategies by impelling intensive social media users to participate in enacting countering actions

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-09-2022-0507.

Purpose: This study aims to identify communication speech acts and transaction terms in online stores (Olshop) during live streaming on Facebook amid the COVID-19 pandemic and to understand communication patterns between sellers and buyers when shopping on Facebook live streaming in Indonesia.

The Need for Research: This research is motivated by the skill gap arising from increasing buying and selling transactions through live streaming on Facebook. Cultural and demographic shifts, along with the widespread availability of modern technologies and marketing 2.0 have resulted in the global population adopting social media at rates far beyond our use of the Internet, making a compelling case by example and analogy that social media has the potential to level the playing field and is effective in reaching their target market.

Methodology: The type of research is descriptive-qualitative using corpus data instruments. The data collection technique in this study was carried out by reading and observing the data and listening to speeches about buying and selling women’s equipment from various online stores on Facebook. Then select and sort the data designated as forms, strategies, and functions of speech acts in buying and selling transactions during live streaming on Facebook. The data analysis technique has three steps: (1) reducing the amount of data; (2) presenting the data; and (3) concluding.

Findings: The results show that there are four types of speech acts between sellers and buyers in the live-streaming online shop on Facebook, namely, assertive, directive, expressive, and commissive speech acts.

Despite the opportunities of digital twins (DTs) for smart buildings, limited research has been conducted regarding the facility management stage, and this is explained by the high complexity of accurately representing and modelling the physics behind the DTs process. This study thus organises and consolidates the fragmented literature on DTs implementation for smart buildings at the facility management stage by exploring the enablers, applications and challenges and examining the interrelationships amongst them.

A systematic literature review approach is adopted to analyse and synthesise the existing literature relating to the subject topic.

The study revealed six main categories of enablers of DTs for smart building at the facility management stage, namely perception technologies, network technologies, storage technologies, application technologies, knowledge-building and design processes. Three substantial categories of DTs application for smart buildings were revealed at the facility management stage: efficient operation and service monitoring, efficient building energy management and effective smart building maintenance. Subsequently, the top four major challenges were identified as being “lack of a systematic and comprehensive reference model”, “real-time data integration”, “the complexity and uncertainty nature of real-time data” and “real-time data visualisation”. An integrative framework is finally proposed by examining the interactive relationship amongst the enablers, the applications and the challenges.

The findings could guide facility managers/engineers to fairly understand the enablers, applications and challenges when DTs are being implemented to improve smart building performance and achieve user satisfaction at the facility management stage.

This study contributes to the knowledge body on DTs by extending the scope of the existing studies to identify the enablers and applications of DTs for smart buildings at the facility management stage and the specific challenges.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.