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Many waste-to-energy (WTE) plants are constructed and operated using the public-private partnership (PPP) mode in China. However, risk events of PPP WTE incineration projects sometimes occur. This study aims to clarify the relationship of risks in China's PPP WTE incineration projects and identify the key risks accordingly and risk transmission paths.

A risk list of PPP WTE incineration projects was obtained based on literature analysis. Moreover, a hybrid approach combining fuzzy sets, decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) was developed to analyze the causality of risks, explore critical risks and reveal the risk transmission paths. The quantitative analysis process was implemented in MATLAB.

The results show that government decision-making risk, government credit risk, government supervision behavior risk, legal and policy risk, revenue and cost risk and management capacity risk are the critical risks of PPP WTE incineration projects in China. These critical risks are at different levels in the risk hierarchy and often trigger other risks.

Currently, there is a lack of exploration on the interaction between the risks of PPP WTE incineration projects. This study fills this gap by examining the key risks and risk transfer pathways of PPP WTE incineration projects from the perspective of risk interactions. The findings can help the public and private sectors to systematically understand the risks in PPP WTE incineration projects, thus enabling them to identify the risks that need to be focused on when making decisions and to optimize risk prevention strategies. The proposed hybrid approach can offer methodological ideas for risk analysis of other types of PPP projects.

The adoption of mobile payment remains low in certain regions, highlighting the need to identify the factors that enable and inhibit its adoption. This study aims to address this gap by investigating the role of information security, loss aversion and the moderating influence of the herd effect on Inertia and behavioral intentions in the adoption of mobile payment systems.

A structural equation model was developed and tested with 332 valid questionnaires to examine the proposed hypotheses.

The empirical results reveal that information security plays a significant role as an enabler, while loss aversion acts as an inhibitor of mobile payment adoption. Furthermore, the study uncovers the moderating influence of the herd effect on the relationship between Inertia and behavioral intentions.

This study was conducted in a specific region and may not be generalizable to other regions. Future studies could expand the sample size and scope to enhance the external validity of the findings.

This study offers practical implications for mobile payment service providers. Understanding the key enabling and inhibiting factors identified in this study can guide providers in designing and improving their services. Strengthening information security measures can help build trust among potential adopters, while offering incentives can mitigate the impact of loss aversion and encourage early adoption.

The findings of this study have social implications as they contribute to promoting the adoption of mobile payment systems. Increased adoption can enhance financial inclusion and stimulate economic development.

This study provides novel insights into the enabling and inhibiting factors of mobile payment adoption and highlights the moderating role of the herd effect. By shedding light on the influence of social norms on individual behavior in the context of mobile payment adoption, this study contributes to the existing literature and advances our understanding of this phenomenon.

The purpose of this article was to explore the influence of individual perception and social climate on consumer-initiated group-buying purchase decisions. An extended cross-level research model was used to explain how a new mechanism for purchasing through personal interactions could work.

This study utilised a questionnaire survey for data gathering. The subjects of the investigation were group-buying initiators. Hierarchical linear modelling (HLM) was used to experimentally examine the research hypotheses.

The empirical results of the study indicate that the social influence of critical mass can effectively promote positive attitudes and intentions towards consumer-initiated online group buying. An individuals' perception of an initiator's fairness influences their trust in the initiator. In addition, trust in the initiator can positively and significantly influence buyers' attitudes and intentions to online group buying.

Most previous studies on online group-buying focus on how social media influences group-buying behaviours. This study extends social media research by introducing an extended cross-level model to provide a comprehensive investigation into online-shopping. It is a preliminary attempt to systematically verify relationships at the individual and aggregate levels. The decision to group buying requires a relationship of trust to be formed before any transaction takes place, thereby increasing the intention to make a purchase. As a result, group buying is perceived as positive when interpersonal communication is very efficient, or when social influence is high.

Country of origin has profound effects on consumer behavior; yet few studies have examined an antecedent of these effects: why some countries enjoy a positive image while others suffer a negative one. Developing an institutional theory of country image, the authors argue that weak legal institutions at the country level increase firm opportunistic behavior that expropriates consumers and decrease the product quality of local brands, thus decreasing the country’s image regarding its products and brands.

This study measures country image for products and brands using the number of valuable brands (i.e. brands included in the top 500 brands from 2008 to 2016) in a particular home country. Data concerning the rule of law in each country come from the World Bank, and data on the efficiency of countries’ judicial systems comes from Djankov et al. (2007). We also collect patent data from the US Patent and Trade Office, national culture from Hofstede Insights and GDP and GDP per capita from the World Bank as control variables. Panel Poisson regression, Tobit regression and truncated regression are used in the analyses.

Supporting the institutional theory of country image, both the rule of law and efficiency of the judicial systems show positive and significant effects on country image, even when economy size (GDP), degree of economic development (GDP per capita), level of technology and skill (patents) and culture are controlled.

To improve their country’s image and the brand value of local firms, policymakers should strive to strengthen legal institutions aimed at punishing firm opportunistic behavior in their countries.

Previous research on the country-of-origin effect has not yet appreciated the role of legal institutions in developing the construct of country image.

Although multinational enterprises (MNEs) based in emerging economies arose quickly during the past decade, most of these firms lack marketing capabilities and strong brands. Emerging-economy MNEs that have tried to build their own brands have been largely unsuccessful. The purpose of this paper is to argue that corruption in the MNEs’ home countries has been detrimental to their brand values. Corruption makes it more difficult for consumers to govern their transactions with local firms, thus decreasing firms’ trustworthiness and brand values.

Data of the global top 500 most valuable brands of 2008 and 2014 and the Poisson regression model are used.

This study finds that firms based in countries with lower levels of corruption establish more valuable brands than those based in countries with higher corruption, even when GDP and GDP per capita are controlled.

Policymakers who want to help local firms increase their marketing capabilities and establish strong brands should strive to increase the trustworthiness of local firms by undertaking anti-corruption reforms aimed at protecting consumers.

Few studies have address the research question that why emerging-market MNEs lack marketing capabilities and strong brands. This study finds that institutional factors such as corruption at country level prevent them from establishing strong brands.

The purpose of this paper is to combine task-technology fit, theory of planned behaviour and individual technology optimism, and propose a better hybrid technology behavioural intention model to explain Taiwanese students’ usage behaviour for weblog learning.

A 31-item questionnaire with eight constructs was administered to undergraduate and graduate students enrolled in three universities in Taiwan. A total of 380 voluntary, usable responses were received, and a research model estimated using Smart PLS was used to interpret the structural relation results.

The results of the research model were analysed using a structural equation modelling approach to test six hypotheses and three moderating hypotheses; significant support were found for seven of them. Accordingly, this study considered the level of technology optimism as a moderator to explore whether it impacts perceived behavioural control, attitudes and social influences on behavioural intention related to weblog learning.

This research provides a better understanding of individual and system characteristics, as well as social factors regarding weblog learning system acceptance and intention.

The purpose of this study is to develop and empirically test a model that can predict factors affecting student recycling behavior. The theoretical model was based on motivation, place attachment, environmental concern and interpersonal altruism.

A cross-sectional study was conducted with college students in Taiwan using self-report questionnaires. Of the 800 distributed questionnaires, 523 were completed (response rate of 65.4%) and were analyzed using structural equation modeling. Partial least squares (PLS) were used to test the models and hypotheses.

The results showed that environmental concern, motivation, interpersonal altruism and place attachment have significant positive effects on recycling behavior and motivation and place attachment have significant positive effects on interpersonal altruism. This research contributes to the existing literature by discriminating between two sorts of motivation: intrinsic and extrinsic. Based on these findings, suggestions for future research and practical implications are presented.

Few studies have linked motivation, interpersonal altruism, environmental concern and place attachment to recycling behavior. Therefore, this study aimed to explore these relationships, specifically as they affect college students’ behavior. This paper anticipates that increased knowledge about recycling behavior could be used to support the wider adoption of recycling practices.

The digital divide is a concern, as the inequality of information access might have significant influences on social development and quality of life. The purpose of this paper is to examine the perceived benefit of Digital Opportunity Centers (DOCs) programs on remote area participants from the perspective of computer anxiety and personal information ability.

The Taiwanese Government has built DOCs in remote areas to provide information technology (IT) training and learning programs to citizens residing in these areas. DOC program participants in Taiwan voluntarily completed a self-report questionnaire; the authors received 2,105 completed questionnaires, with a response rate of 84.2 percent. This research used partial least-squares (PLS) to empirical the research model.

Using PLS, the results show that information and communication technology ability influences the perceived benefit of DOC programs; computer anxiety has significantly negative effects on package software use, internet use, and IT usefulness; and internet use and IT usefulness have positive effects on perceived benefits.

IT is continuously advancing, but digital resources are still lacking within remote areas. DOCs provide citizens different types of learning experiences related to economic, social, and educational development. DOC programs provide participants with opportunities to obtain and improve basic IT knowledge and abilities and decreasing the digital divide.

The quality of information sharing is of the utmost importance for supply chains (SCs). The purpose of this paper is to improve understanding of the human attitude: willingness to share, its antecedents and its role in improving information sharing quality.

Based on information sharing theory, a theoretical model and research hypotheses are developed. Data from 387 respondents were collected to test the hypotheses and model fit using structural equation modelling and mediation analysis. The impact of social-psychological factors and information technology (IT) infrastructure capability on willingness to share information and, consequently, its effect on information sharing quality were analysed using IBM SPSS Statistics, PROCESS and AMOS.

The statistical analysis showed a good model fit. Trust is the most important antecedent for willingness to share, while the impacts of commitment and reciprocity are also significant. Interestingly, power is not a significant antecedent of willingness. Life satisfaction is a significant precursor to willingness to share information, whereas surprisingly overall job satisfaction does not play a significant role.

Cross-sectional data were used and the scope was limited to SCs.

Managers should be aware that trust, commitment and reciprocity with their SC partners influence the willingness to share information with varying effects. Access to proper IT capabilities increases willingness as does the life satisfaction. SC individuals who are happy with life are more willing. Interestingly, high power might get the sharer to share information albeit unwillingly.

The model provides a social-psychological understanding of the antecedents of human willingness to share information, which is crucial to sharing quality information. Overall, the social-psychological and IT factors model based on information sharing theory is statistically valid for the SC context.

The purpose of this paper is to develop an intelligent system for fashion style selection for non-standard female body shapes.

With the goal of creating natural aesthetic relationship between the body shape and the shape of clothing, garments designed for the upper and lower body are combined to fit different female body shapes, which are classified as V, A, H and O-shapes. The proposed intelligent system combines genetic algorithm (GA) with a neural network classifier, which is trained using the particle swarm optimization (PSO). The former, called genetic search, is used to find the optimal design parameters corresponding to a best fit for the desired target, while the task of the latter, called neural classification, is to evaluate fitness (goodness) of each evolved new fashion style.

The experimental results are fashion styling recommendations for the four female body shapes, drawn from 260 possible combinations, based on variations from 15 attributes. These results are considered to be a strong indication of the potential benefits of the application of intelligent systems to fashion styling.

The proposed intelligent system combines the effective searching capabilities of two approaches. The first approach uses the GA for identifying best fits to the target shape of the body in the solution space. The second is the PSO for finding optimal (with respect to training mean-squared error) weight and threshold parameters of the neural classifier, which is able to evaluate the fitness of successively evolved fashion styles.