Search results

For entrepreneurs operating in an Internet-of-Things (IoT) environment, it is essential to monitor more systematically, both the interaction with the consumers and the sharing of information among the consumers. The purpose of this paper is to identify the antecedents of word-of-mouth (WOM) in the online SME’s context in terms of consumers “citing the site” to peers in personal communications. A research model integrates the determinants of retail website-specific positive WOM communication, and proposes that WOM about a particular website is influenced by: site-level variables, that is, website quality and interactivity; and consumer-level variables, these being the site user’s satisfaction with and commitment to the website. The research advances the study of IoT entrepreneurship.

Data were collected from graduate and undergraduate students with business and entrepreneurship majors from a reputed school in the Northeast region of the USA, using an online survey. The hypotheses were then tested with SEM using AMOS 18.0.

Findings suggest that in an IoT context, WOM is influenced by a variety of factors of which the e-satisfaction and attitude toward website constructs play important roles. The study highlights the importance of the e-satisfaction construct and its metrics. E-satisfaction is not only a critical outcome metric, but also a primary predictor of customer e-loyalty, measured in terms of the customer’s positive attitude, stickiness and propensity to spread positive WOM.

The paper contributes to the entrepreneurship and IoT literature with a comprehensive framework of information sharing, interactivity and WOM, showing that specific antecedents drive consumers to cite and advocate for a website to fellow customers. The framework helps retail SME entrepreneurs in the IoT context to design appropriate strategies to influence website visitors’ endorsement of the site to fellow customers.

This study aims to propose a set of institutional frameworks, as well as practical polices and steps, with a view to facilitating the establishment of a unified carbon trading market in China.

Based on existing empirical studies and reviews of the socioeconomic contexts, this study followed a qualitative approach consisting of secondary data collection and analysis, semi-structured interviews to collect primary data and comparative analysis.

The establishment of a national carbon trading market in China is a systemic and complex process which requires coordination among various concerned government agencies and supporting mechanisms. Currently, the development of a unified national carbon market has been impeded by the lack of coordination among local pilot programs, and there is no specific law passed by the People’s Congress or by its Standing Committee to regulate the emerging carbon trading market. It is of vital importance for China, in terms of both practical and strategic aspects, to take a gradualist approach in establishing laws and institutions to guide and support the development of its emerging carbon market.

This present study forms a part of a regional research project aiming to identify sound policy approaches for the establishment of a carbon trading market in China. Due to scope reasons, it focuses only on policy analysis and recommendations.

China’s emerging national carbon trading market has attracted much research attention. However, little has been done from the perspectives of legislations and policies.

This study aims at developing a better understanding of the relationship between network embeddedness and incremental innovation capability and further examines the moderating effect of open innovation.

This paper adopts hierarchical regressions to validate the theoretical model and collect the patent data of the top 54 firm patentees in the smartphone industry as empirical sample. Using patent citation network data, this paper estimates the relationship between open innovation, network embeddedness and incremental innovation capability.

This paper empirically shows that structural embeddedness exerts a negative effect on incremental innovation capability, while relational embeddedness is positively related to incremental innovation capability. And open innovation strengthens the relationship between network embeddedness and incremental innovation capability.

This paper shifts the focus of the determinants of incremental innovation capability from internal factors to the external network features by exploring the linkage between network embeddedness and incremental innovation capability. A counterintuitive conclusion is that structural embeddedness shows a negative effect on firm's incremental innovation capability. Furthermore, in contrast to most previous studies, which only focus on the direct effect of open innovation on the firm's incremental innovation capability, our study examines the moderating effect of open innovation on the relationships between network embeddedness and incremental innovation capability. At last, the results provide practical guidance for firms to occupy the beneficial network positions and adopt appropriate open innovation strategies to improve their incremental innovation capability.

The purpose of this study was to solve the problem of most woven-fabric self-lubricating bearings that find it difficult to function at temperatures above 320°C, by designing a new type of new nuclear joint bearing. The results of this study will help designers to achieve accurate stress distribution, displacement deformation, fatigue life and damage of bearings. All of these can be a guide for designing self-lubricating joint bearings.

Finite element analysis is undertaken to simulate the new design bearings. To get the most appropriate and accurate results, the room temperature simulation (Simulation A), the modulus of elasticity that changes with temperature (Simulation B) and the thermal-structure-coupled simulation (Simulation C) are compared. The fatigue simulation is conducted to verify whether the self-lubricating method is reasonable and whether the bearing can function for over 60 years in an enclosed environment.

Stress distribution and displacement deformation of joint bearing can be accurately achieved via the thermal-structure coupled simulation. Work life and damage results have been achieved via the fatigue analysis, and the suggested working loads can be calculated via safety factors.

The newly designed joint bearing in which the graphite is laid on the outside of the inner ring functions and self-lubricates at temperatures above 320°C.

This study aims to build a global environmental quality protection convention to jointly address the problems of environmental pollution governance worldwide.

From the perspective of environmental pollution of the air, ocean, forest, water and solid waste, the authors summarize the main important measures and mechanisms of environmental pollution governance in various countries.

The results indicate that management research on biodiversity and natural resources must be strengthened, the relationship between economic development and environmental quality management needs to be balanced, the comparative study of domestic and international environmental governance theories and practices should be strengthened, empirical and applied research on environmental governance needs to be focused on, and complete system research on environmental governance and management should be explored. In the future, further strengthening environmental awareness, addressing environmental pollution and managing environmental quality are necessary.

The environment is the foundation of human survival and development. With the development of economy, contradictions between human and natural environment (e.g. air, ocean, forest and water) have become prominent. Environmental pollution governance cannot only help address existing environmental problems but also solve economic problems of various countries. The prerequisite for sustainable development is to lay a solid foundation for the coordinated development of economic growth and pollution management.

The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.

Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.

Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.

First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.

The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.

The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.

The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.

Smart cities show a “booming” trend both in the academia and the industry in recent years. Scholars across the world have been investigating how new technologies are applied to develop new services to the inhabitants and cities all over the world also address the “smart cities” challenges by promoting policymaking and governance. This paper aims to conduct in-depth research on smart cities by combining the study of governance policy study and information technology study.

This paper empirically mapped the trends of smart city development, outstanding scholars and hot topics about smart cities by analyzing important references using CiteSpace. The authors visualized references and topics to analyze smart city research, based on empirical data from Web of Science. Furthermore, two most important research branches – topics from smart city governance research and those from information systems (IS) research were studied, respectively.

First, the authors mapped the development of research and divided the development into three different stages. Second, the authors explored important, influential and instructive publications and publications’ attributes including authors, institutions, journals and topics. Third, the authors found there are different characteristics between the IS group and the governance group in publication situations, influential institutions, journals and authors, although the research points of the two branches are overlapping and fragmented. Finally, the authors proposed important topics, which include “internet of things (IoT)”, “big data”, “smart city systems” and “smart city management” and the authors predicted that “IoT” and “smart city challenge” would be future trends in recent years.

This study is an innovative research of its category because it visualized the development of smart city research, analyzed both governance and technology branches of smart city research synthetically using CiteSpace and forecasted future trends of smart city research by topics analysis and visualization of evolution.

Under the pressure of environment degradation and energy consumption rises, solar photovoltaic power generation (SPPG) has been seen as a strategic emerging industry in China. However, the SPPG projects have many uncertain factors in the process of the life cycle. The purpose of this paper is to evaluate the investment risk comprehensively.

Specifically, this paper firstly identified the risk factors and consequences of SPPG project investment and constructed the investment risk factor evaluation index system. Secondly, the factor analysis method was used to reveal the key investment risk factors and risk consequences. Then, the research hypotheses and conceptual model were proposed, and the empirical analysis was conducted based on the structural equation model (SEM).

The results showed that the six key risk factors (political, economic, technological, management, market and natural) have a significant impact on the risks during the whole period. The influence degree of risk factors in the operational period is such that market factor > political factor > economic factor > management factor > natural factor > technical factor. In addition, the risk of constructional period has a significant impact during the risk of operational period. Except for natural factors, all risk factors are correlated among the mutual influence relationship of risk factors. Finally, this paper puts forward management implications based on the above conclusions: effectively identify investment risk factors and comprehensively improve risk management ability; (refine the risk factors of SPPG project investment and develop targeted risk prevention and control strategies; define risk management objectives and make relevant strategic plans.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further.

It can also help stakeholders propose risk prevention strategies throughout the entire process, to promote the sustainable development of SPPG projects.

This study focuses on the investment risk of SPPG projects, by building an evaluation index system to identify key risk factors, and then establishes a SEM covering constructional period risks and operational period risks to better explore SPPG project risks, in an effort to reveal the mutual influence relationship and influence path of investment risk factors of the projects.

To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.

Considering the dual roles of the e-commerce platform as a seller and an initiator, a typical game-theoretical method is applied to analyze the behavior of supply chain decision-makers and the impact of key variables on equilibriums.

When loan interest rates are symmetric, whether blockchain is used or not, the e-commerce platform financing mode will always produce higher wholesale price and unit carbon emission reduction, while the retail price is the opposite. Higher unit additional income brought by the blockchain can bring higher economic and environmental performances, and the e-commerce platform financing mode is superior to bank financing mode. The application of blockchain may cause the manufacturer to change his/her financing choice. For bank financing, with the increase of loan interest rates, the advantages brought by blockchain will gradually disappear, but this situation will not occur under e-commerce platform financing.

Blockchain is known for its information transparency properties and its ability to enhance user trust. However, the impacts of applying blockchain in a low-carbon platform supply chain with different financing options are not clear. The authors examine the manufacturer's strategic choices for platform financing and bank financing, whether to adopt blockchain, and the impact of these decisions on carbon emissions reduction, consumer surplus and social welfare. The research conclusion can provide reference for the operation and financing decisions of platform supply chain under the carbon reduction target in the digital economy era.