Influencing factors on risk perception of IoT-based home energy management services

Executives' ESG cognition and enterprise green innovation: Evidence based on executives' personal microblogs

Based on cognitive theory, we investigated the influence of executives' ESG cognition on corporate green innovation using data from Chinese manufacturing listed companies from 2010 to 2019. The paper first constructs a metric of ESG cognition of company executives by presenting a quantitative analysis of data from their personal microblogs using textual analysis. The findings show that executive ESG perceptions significantly improve corporate green innovation. After addressing the endogeneity issue through a series of robustness tests, the findings of this paper still held true. Further research found that the enhancement effect of executive ESG perceptions on firms' green innovation level was mainly found in the sample without heavy pollution and with lower financing constraints and a higher marketization process. This study makes an important contribution to the research on corporate green innovation based on the perspective of executive ESG cognition while also providing a theoretical basis and practical reference for corporate green innovation practices.

Identifying the Key Drivers and Barriers of Smart Home Adoption: A Thematic Analysis from the Business Perspective

Smart homes embrace advanced technologies and the connectedness of devices that aim to increase consumers’ life quality. They are based on data integration over shared platforms collected via sensors and wireless networks. However, although consumers’ current and potential adoption of smart homes have received some research interest, there is a low number of studies considering the foreseeable future of smart homes from the business perspective. To fulfill this gap in the literature, this study presents the results of an exploratory research attempting to reveal the foresight of the business side regarding the penetration of smart home technologies (SHTs) into consumers’ lives. Based on the opinions of industry experts collected through 13 semistructured in-depth interviews, numerous drivers of and barriers to SHT adoption are uncovered and displayed in their intertwined relationship in a thematic map. In creating this map, the qualitative data gathered through the interviews are integrated with widely used theories/models of technology adoption in the literature to develop a full-fledged set of determinants. As a result, drivers of SHT adoption (five sub-themes) and barriers that hinder smart home penetration (eight subthemes) were determined. Drivers consist of relative advantage, enjoyment, image enhancement, modern and multifunctional design, and consumers’ technology innovativeness. In contrast, the main barriers are high cost, complexity, lack of compatibility, lack of trialability, lack of observability, lack of a trusted brand in the market, lack of facilitating conditions and support services, and consumers’ technology anxiety. This rich set of SHT adoption determinants can be used in future studies to examine their relative impact on consumers’ adoption of SHT.

Factors Affecting the Adoption of IoT-Based Smart Campus: An Investigation Using Analytical Hierarchical Process (AHP)

The advancement of technology is making university campuses smarter every single day. Despite the benefits of these advanced technologies, the literature concerning the adoption of smart campuses is significantly lacking increased knowledge to provide effective smart campus solutions. This study aims to prioritize the adoption factors of an IoT-based smart campus. The study applied an analytical hierarchical process (AHP) on 25 factors drawn from the literature. The factors were classified into technology specific factors (TSF), organizational specific factors (OSF), environmental specific factors (ESF), and end-user specific factors (USF). Based on the results obtained, the most significant contributing factors were government support, privacy concerns, social influence, facilitating conditions, and service collaboration, whereas the least significant contributing factors were enjoyment, availability, reliability, mobility, and compatibility. Moreover, based on the global ranking computation, 12 factors from the OSF, ESF, and USF categories appeared to be more significant than TSF. The findings of this study could help university administrators, manufacturers, and policy-makers to understand the critical factors of smart campuses in order to improve the adoption and utilization of these solutions effectively.

Consumers' purchase intention of wild freshwater fish during the COVID-19 pandemic

The association between the COVID-19 pandemic and the wildlife trade in the seafood market in Wuhan has raised public concern regarding wildlife consumption and public health safety. Considering several coronavirus transmission incidents related to aquatic products and the location of wild freshwater fish in aquatic consumption in China, the effects of COVID-19 on the purchase intention of wild freshwater fish was investigated. Based on 1163 online questionnaires from eight provinces (including two province-level municipalities) in the Yangtze River Basin, ordered logistic regression was carried out to analyze the influencing factors of purchase intention of wild freshwater fish during the COVID-19 pandemic. The empirical results indicated that the COVID-19 pandemic had changed consumers' perceived risk and purchase frequency of wild freshwater fish. External stimulus caused by the COVID-19 pandemic had little influence on perceived risk and purchase intention. Consumer preference had a significant impact on perceived risk and purchase intention. Therefore, efforts should be put to strengthen the popularization of aquatic product knowledge, guide the public to develop scientific and civic eating habits, and improve the traceability system of aquatic products. [EconLit Citations: D12-Consumer Economics: Empirical Analysis, Q22-Fishery; Aquaculture].

A Review of Digital Transformation on Supply Chain Process Management Using Text Mining

Industry 4.0 technologies are causing a paradigm shift in supply chain process management. The digital transformation of the supply chains provides enormous benefits to organizations by empowering collaboration among multiple internal and external organizations and systems. This study presents a narrative review explaining the existing knowledge on digital transformation in supply chain process management using text mining. It summarizes the existing literature to explain the current state of the art in supply chain digitalization. This comprehensive review identifies the most important topics and technologies and determines the future trends in this emerging field. We investigate the articles published in Web of Science and Scopus databases and use text mining techniques (clustering and topic modeling) on the article contents. Using VOS viewer, a bibliometric analysis of 395 articles with 12,700 references is analyzed. The contents of the articles are explored using text mining approaches. The synthesized results reveal that the most important topics in digital transformation are “sustainable supply chain management” and “circular economy and industry 4.0 technologies”. The study further discovers big data, data analytics, blockchain, artificial intelligence, machine learning, and the Internet of Things as the most critical technologies for facilitating supply chain digital transformation. Finally, an overlay heatmap analysis of the research articles found that digital transformation, supply chain management, industry 4.0, decision-making, and sustainability are emerging trends in supply chain digitalization.

Revising Technology Adoption Factors for IoT-Based Smart Campuses: A Systematic Review

Smart education and the sustainable development of smart campuses have drawn significant research attention. This is enabled by intelligent devices that are widely attracting massive applicability in personal and big business contexts and can increase efficiency and convenience. This paper aims to present a solution to address the lack of a proper adoption model for smart campus initiatives. The evaluation and synthesis of the literature were conducted by following the systematic literature review (SLR) procedure. The study’s findings revealed the taxonomy and IoT technologies leading to the wide adoption of IoT-based smart campuses. The technology adoption models and their corresponding variables help the authors identify and classify a suitable adoption framework for smart campuses. The limitations and challenges of adoption theories as they pertain to smart campuses are discussed. Finally, the study adapts perceived scalability, perceived replicability, perceived reliability, perceived privacy and security, perceived trust, the cost of deployment, usefulness, enjoyment, and technicality as adoption factors of sustainable smart campuses. This study offers practical and theoretical implications regarding the adoption and propagation of emerging smart campuses.

Risk Perception and Coping Behavior of Construction Workers on Occupational Health Risks-A Case Study of Nanjing, China

To reduce harm caused by occupational health risks of construction workers exposed to working environments, especially those for interior decoration, it is crucial for them to actively recognize and prevent these risks. Therefore, how to improve their occupational health risks perception and regulate their coping behaviors should be of great concern. However, most prior studies target construction worker safety, and little research focuses on risk analysis from the psychological level of workers. Hence, construction workers' occupational health risk perception level and coping behavior level in Nanjing and the influencing factors were analyzed through statistical analysis with 341 valid questionnaires. Bootstrapping was applied to test the mediating effects of risk perception on the proposed factors and coping behaviors. This study revealed that construction workers have a high-level of occupational health risk perception, yet low-level coping behavior. Gender, age, education level, and unit qualification cause differences in individual risk perception level. Personal knowledge and group effects significantly affect the level of risk perception, which subsequently affect coping behavior. Education level, monthly income, and personal knowledge influence the coping behavior through risk perception. Recommendations were put forward for risk perception and coping behavior improvement from the perspectives of construction workers themselves, enterprises, and governments. This study sheds new light for research areas of occupational health and risk management and provides beneficial practice for improving construction workers' responses to occupational health risks.

A Study of Factors Influencing on Passive and Active Acceptance of Home Energy Management Services with Internet of Things

Since awareness of the influence of home energy management services (HEMS) with Internet of things (IoT) has grown, the study on the acceptance of IoT services has been expanded. Previous studies, however, have not paid attention to the acceptance itself, focusing only on factors affecting the acceptance. This study attempts to draw meaningful implications by exploring the relationships between the acceptance and the factors affecting it with distinctions between passive acceptance and active acceptance. This study analyzed the ordinal logistic regression models based on a survey of 909 adults 19 years of age and older in Korea on HEMS with IoT. In addition, we attempt the ordinal forest to increase the reliability of the research results. As a result, this study showed that consumers’ perception of usefulness was noticeably important to enhance active acceptance and that those who had high sensitivity to new technology acceptance showed high active acceptance, and older women had higher active acceptance. This study might contribute to the research on IoT acceptance in the energy management sector by classifying the acceptance into active acceptance and passive acceptance beyond the framework of setting the acceptance as a single variable.

Internet of things skills and needs satisfaction: do generational cohorts' variations matter?

Purpose

The authors’ understanding of the Internet of things (IoT) skills and needs satisfaction for IoT devices and generational cohorts' variations remains limited as commentaries are often oversimplified and generalized. This research fills a gap in the literature by highlighting the dynamics between the IoT skills and needs satisfaction for IoT devices and seeks to expound on the variations among generational cohorts using the self-determination theory.

Design/methodology/approach

Survey data were obtained from 1,245 residents and IoT device users in Aksaray, Turkey. The obtained data were analyzed with variance-based structural equation modeling and the analysis of variance technique.

Findings

The results demonstrate that IoT skills determine the needs satisfaction for IoT devices. Generation Xers, Generation Yers and Generation Zers are distinct cohorts with respect to the IoT skills and needs satisfaction for IoT devices.

Originality/value

Collectively, this study provides empirical evidence that informs the debate about the contributions of IoT skills and generational cohorts on needs satisfaction for IoT devices. The implications and several avenues for future theory-building research are discussed.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2020-0144

Validating the Adoption of Heterogeneous Internet of Things with Blockchain

Emerging technologies such as Internet of Things (IoT) and blockchain have affected the digital transformation. Blockchain, on the one hand, was initially developed for the purpose of financial trading due to its robustness especially for fault tolerance and cryptographic security in addition to its decentralized architecture. IoT, on the other hand, is an open interconnected network of smart devices able to communicate simultaneously. This arises a challenge in privacy and security, specifically for the data being exchanged. To overcome this, studies have focused on the blockchain to resolve the security and privacy issues of IoT. Indeed, limited studies have proposed to assess blockchain’s viability for IoT and the associated challenges. In this paper, a conceptual model has proposed to identify the crucial factors affecting the adoption of blockchain in IoT. The model consists of four dimensions of factors that we assume will affect the adoption of the two technologies. The dimensions are: attitude-related factors, social influence related factors, data-related factors, and security-related factors. This model is validated through a survey that was distributed between professionals in blockchain and IoT. The findings show a significant impact of data-related factors on the adoption of blockchain in IoT and the intention to use them. The model can play an important role in the development of strategies, standards, and performance assessment.

Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis

There is a growing need for increased flexibility in modern power systems. Traditionally, this flexibility has been provided by supply-side technologies. There has been an increase in the research surrounding flexibility services provided by demand-side actors and technologies, especially flexibility services provided by prosumers (those customers who both produce and consume electricity). This work gathers 1183 peer-reviewed journal articles concerning the topic and uses them to identify the current state of the art. This body of literature was analysed with two leading textual and scientometric analysis tools, SAS© Visual Text Analytics and VOSviewer, in order to provide a detailed understanding of the current state-of-the-art research on prosumer flexibility. Trends, key ideas, opportunities and challenges were identified and discussed.