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Based on the cognition–affect–conation pattern, this study explores the factors that affect the intention to use facial recognition services (FRS). The study adopts the driving factor perspective to examine how network externalities influence FRS use intention through the mediating role of satisfaction and the barrier factor perspective to analyze how perceived privacy risk affects FRS use intention through the mediating role of privacy cynicism.

The data collected from 478 Chinese FRS users are analyzed via partial least squares-based structural equation modeling (PLS-SEM).

The study produces the following results. (1) FRS use intention is motivated directly by the positive affective factor of satisfaction and the negative affective factor of privacy cynicism. (2) Satisfaction is affected by cognitive factors related to network externalities. Perceived complementarity and perceived compatibility, two indirect network externalities, positively affect satisfaction, whereas perceived critical mass, a direct network externality, does not significantly affect satisfaction. In addition, perceived privacy risk generates privacy cynicism. (3) Resistance to change positively moderates the relationship between privacy cynicism and intention to use FRS.

This study extends knowledge on people's use of FRS by exploring affect- and cognitive-based factors and finding that the affect-based factors (satisfaction and privacy cynicism) play fully mediating roles in the relationship between the cognitive-based factors and use intention. This study also expands the cognitive boundaries of FRS use by exploring the functional condition between affect-based factors and use intention, that is, the moderating role of resistance to use.

This paper aims to study frictional characteristics of thin-walled tubes in the liquid impact forming (LIF) process.

LIF experiments under various impacting velocities were performed on SUS304 stainless steel tubes with various guiding lengths on a custom-designed measurement system to investigate the effects of impacting velocity and guiding length on the coefficient of friction (COF) in the guiding zone.

The results indicate that the COF changes dynamically in the guiding zone and decreases with the deformation process. The reduction range of the COF is wider in LIF than in both the conventional and pulsating hydroforming (THF), which may be contributed to the impacting velocities in a short time. Moreover, the COF decreases faster in the first half of the LIF process than in the second half. Under different impacting velocities and guiding lengths, the decreasing rate of the COF in the first half is more sensitive and obvious than that in the second half.

A method for determining the COF in the guiding zone in LIF is proposed and the frictional characteristics in LIF are studied. Comparing the COF of tubes in conventional THF, pulsating THF and the LIF process is valuable for improving and predicting the tubular formability in various hydraulic environments for industrial production.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2019-0269

The purpose of this paper is to identify the main environmental impacts of coal mining in China, examine the main institutions and reform factors that failed the control of these damages, and discuss what would be necessary to establish a sustainable and environmentally responsible coal mining sector in the context of market and institutional reforms.

Review of existing knowledge, and semi‐structured interviewing with key informants in the policy and industry sectors has been the main method of primary and secondary data collection. Grounded theory was used to analyze original data.

The large and fast growing coal industry in China has caused significant environmental degradation, including land subsidence and water intrusion, as well as remarkable records of miner's poor safety and health. Market reform was mostly unsuccessful in integrating environmental consideration into production and marketing decisions. Main factors of reform that have been associated with this problem are price deregulation and excessive competition inside the industry. Institutional reform, in fact, enhanced the status of State Environment Protection Agency; however, it impaired environmental governance in the coal industry. It is suggested that market reform as applicable to the China coal industry economic sector in particular should reconsider its approach in light of the numerous problems it has created.

The paper identifies and puts together the condition of the growing coal industry in China after market reform, articulating the huge environmental costs that this development has imposed on the country, while calling for an environmentally sustainable coal industry.

The purpose is to analyze and discuss the sustainable development (SD) and financing risk assessment (FRA) of resource-based industrial clusters under the Internet of Things (IoT) economy and promote the application of Machine Learning methods and intelligent optimization algorithms in FRA.

This study used the Support Vector Machine (SVM) algorithm that is analyzed together with the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm. First, Yulin City in Shaanxi Province is selected for case analysis. Then, resource-based industrial clusters are studied, and an SD early-warning model is implemented. Then, the financing Risk Assessment Index System is established from the perspective of construction-operation-transfer. Finally, the risk assessment results of Support Vector Regression (SVR) and ACO-based SVR (ACO-SVR) are analyzed.

The results show that the overall sustainability of resource-based industrial clusters and IoT industrial clusters is good in the Yulin City of Shaanxi Province, and the early warning model of GA-based SVR (GA-SVR) has been achieved good results. Yulin City shows an excellent SD momentum in the resource-based industrial cluster, but there are still some risks. Therefore, it is necessary to promote the industrial structure of SD and improve the stability of the resource-based industrial cluster for Yulin City.

The results can provide a direction for the research on the early warning and evaluation of the SD-oriented resource-based industrial clusters and the IoT industrial clusters, promoting the application of SVM technology in the engineering field.

This work aims to examine the quality disclosure strategy of sharing economy platforms with network externality, considering consumer risk aversion.

The game theory, sensitive analysis and numerical study are used herein. The equilibria are derived from the game theory. The quality disclosure strategy is analyzed by profit comparison. To further understand the characteristics of the optimal disclosure strategy, sensitive analysis and numerical studies are conducted to detail the analytical results.

Regardless of market structure, the quality disclosure decision problem is a trade-off between information effect and cost effect. Consumer risk aversion is a factor that can incentivize low-quality platforms to disclose quality. Both consumer risk aversion and network externality influence the quality disclosure strategy through information effect. Interestingly, for different competition intensities, consumer risk aversion and network externality could lead to positive or negative information effects of removing uncertainty. The authors show that under certain conditions, consumer risk aversion and network externality could induce more quality concealment.

The quality is set exogenous herein, and the integrated process of quality investment and information disclosure is an interesting direction for future research.

This work provides managerial insights for sharing economy platforms regarding how to wisely consider consumer risk aversion and network externality when sharing quality information.

This work identifies two effects that determine quality disclosure strategy and specifies the role of each factor on quality disclosure.

This study aims to analyze the influence of farmers’ degree of participation in collective action on their adoption decisions and waiting time regarding soil and water conservation (SWC) measures.

The Probit model and Generalized Propensity Score Match method are used to assess the effect of the degree of participation in collective action on farmers’ adoption decisions and waiting time for implementing SWC measures.

The findings reveal that farmers’ engagement in collective action positively influences the decision-making process regarding terrace construction, water-saving irrigation and afforestation measures. However, it does not significantly impact the decision-making process for plastic film and ridge-furrow tillage practices. Notably, collective action has the strongest influence on farmers’ adoption decisions regarding water-saving irrigation technology, with a relatively smaller influence on the adoption of afforestation and terrace measures. Moreover, the results suggest that participating in collective action effectively reduces the waiting time for terrace construction and expedites the adoption of afforestation and water-saving irrigation technology. Specifically, collective action has a significantly negative effect on the waiting time for terrace construction, followed by water-saving irrigation technology and afforestation measures.

The results of this study underscore the significance of fostering mutual assistance and cooperation mechanisms among farmers, as they can pave the way for raising funds and labor, cultivating elite farmers, attracting skilled labor to rural areas, enhancing the adoption rate and expediting the implementation of terraces, water-saving irrigation technology and afforestation measures.

Drawing on an evaluation of farmers’ degree of participation in collective action, this paper investigates the effect of participation on their SWC adoption decisions and waiting times, thereby offering theoretical and practical insights into soil erosion control in the Loess Plateau.

Based on core description, gas logging and laboratory analysis, this paper aims to study the controlling effect of the types of shale sedimentary microfacies in coal formations over shale reservoirs using the example of Shanxi formation in Northern Ordos Basin.

According to core observation, the authors selected typical samples of rock types for thin section analysis to determine the micro features and compositions of rocks.

By using core observation, we found that fine lithology in Shanxi formation included major shale, carbonaceous shale, partially carbonaceous shale, partially silty shale and silty shale with colors of gray, dark gray, black and/or gray. Shanxi Formation shale are deposited in plant-rich and plant-poor swamps, interdistributary depressions of delta plains, interfluvial depressions of meandering rivers as well as microfacies environment of natural levees and the distal crevasse splay.

Currently, the research on the shale gas in Shanxi Formation in the Ordos Basin is still in its infancy. There is yet no research on the fine-grained partition of the sedimentary facies in coal accumulation environment of Shanxi formation and the controlling effect of sedimentary microfacies over shale reservoirs.

Hospital information system (HIS) can be examined as a vital factor for developing the quality of health care and cost managing. There exists abundant literature on HISs, but implementation-based literature of HIS is rare, typically about progressive countries. However, a study that can comprehensively review published articles is scarce. Therefore, this paper aims to examine the systematic and comprehensive study of HIS in developed countries. Together, the benefits and harms relevant to HIS’s different mechanisms have been considered, and the fundamental challenges of them are addressed to design more efficient HIS in the future.

HIS has been used globally for numerous years and is now being used in a wide area. HIS is broadly used in clinical settings. Information technology (IT) and information system have been suggested as a required piece to solve the health-care-related issues. Hence, to improve HIS’s ability, this paper conducted a review method concentratating on research related to HIS until 2019. A total of 21 papers were recognized and examined as principal research for the summary.

The authors found that HIS can help in reduction of medical mistakes, enhancement doctors’ performance and increase in the quality of the care provided. HIS management can be used to provide better health-care services. Therefore, HIS must be sensible and use clear structures. The authors conclude that, generally, with an increase in awareness, acceptability and the need for HIS worldwide, there will be more strategies and approaches available.

First, this paper provides an outline of the status of HIS. Second, it identifies some distinct research gaps that could be worth studying. Some flawless work may be removed because of applying some filters to select the original articles. Surveying all the papers on the topic of HIS is impossible, too.

Design and sustainability of HIS is still a big issue for most developing countries, despite its wide usage in the developed countries. The technology is changing rapidly, so the field should be reviewed regularly. This paper suggests a suitable framework that will guide HIS in the local conditions of developing countries.

The government will be assisted by the suggested solving ways in its performance and design of electronic health-care projects.

The study brings the viewpoints on the state of HIS mechanisms in developing countries. The paper’s results can offer visions into future research requirements. By providing comparative information and analyzing the current growths in this area, this study will support researchers and professionals to understand the progress in HIS mechanisms better.

The purpose of this study is to investigate which of the two carbon allowance allocation methods (CAAMs), i.e. grandfathered system carbon allowance allocation (GCAA) and baseline system carbon allowance allocation (BCAA), is more beneficial to capital-constrained supply chains under the carbon emission allowance repurchase strategy (CEARS).

Adopting CEARS to ease the capital-constrained supply chains, this study develops two-period game models with manufacturers as leaders and retailers as followers from the perspective of profit and social welfare maximization under two CAAMs (GCAA and BCAA), where the first period produces normal products, and the second period produces low-carbon products.

First, higher carbon-saving can better use CEARS and achieve a higher supply chain profit under the two CAAMs. However, the higher the end-of-period carbon price is, the lower the social welfare is. Second, when carbon-saving is small, GCAA achieves both economic and environmental benefits; BCAA reduces carbon emissions at the expense of economic benefit. Third, the supply chain members gain higher profits and social welfare under GCAA, so the government and supply chain members are more inclined to choose GCAA.

By analyzing the profits and total carbon emissions of capital-constrained supply chains under GCAA and BCAA, this study provides theoretical references for retailers and capital-constrained manufacturers. In addition, by comparing the difference in social welfare under GCAA and BCAA, it provides a basis for the government to choose a reasonable CAAM.

This paper aims to study the pricing strategies of an online trading platform with indirect network externalities by considering heterogeneous trading behavior in the downstream market and the long tail.

The game theory, optimization and comparative static are used in this research. The equilibria are derived from the game theory, and with them, the authors optimize the platform’s profit function. Comparative static is used to study pricing strategies.

It is found that with heterogeneous trading behavior, the transaction-based model is more profitable than the subscription-based model by reason of the feasibility of “price discrimination”. However, with certain advantages of subscription fees such as avoiding offline transactions, the subscription-based model is better with a concentrated distribution of sellers’ revenues (the Gini coefficient is small). With a lucrative long tail, the platform should set a low price to attract small sellers in the long tail. Besides, if the Gini coefficient is large, the effects of the market entry barrier of sellers on the optimal price in each model may be opposite.

It implies that the choice of revenue models and pricing strategies are influenced by the Gini coefficient or the long tail. The exogenous setting in which buyers can use the platform for free needs further extension.

The authors provide insights on how to choose revenue models and how to price the sellers with the long tail phenomenon.

This paper emphasizes the role of the long tail on pricing strategies and the effect of heterogeneous trading behavior on model selection.