Risk assessment for public–private partnership projects: using a fuzzy analytic hierarchical process method and expert opinion in China

Public–private partnerships (PPP) have been widely used in China to procure public facilities and services. Complicated problems in PPP projects in China arise because of a variety of risk factors. A proper risk assessment model is needed to identify risks and provide risk response strategies for future Chinese PPP projects. The fuzzy analytic hierarchy process (F-AHP) method provides the ability to solve complex risk assessment of PPP projects. Current risk assessment models are limited to PPP projects in specific countries and do not consider unique risks in China, especially political, economic, social, and legal risks. This paper designed a risk evaluation index system for PPP projects based on the Delphi expert investigation method, and then established an optimized risk evaluation model for PPP projects in China using the F-AHP method. The risks identified are confirmed by interviewing experts from Chinese local government departments, private enterprise, third-party intermediary consulting and regulatory agencies, and academic organizations. The results show that the risks that ranked among the top ten are closely related to China’s political and economic policies and relationships among stakeholders. It can be concluded that government authorities play a critical role in providing a favorable political, social, and economic environment and an effective institutional framework for PPP projects. Furthermore, it is also important to deal with relationships among stakeholders based on the public–private ‘win–win’ principle. This study provides risk response strategies, addressing key issues from eight aspects: an impeccable legal and regulatory framework; a central coordinating and regulating PPP authority; supportive governmental authorities; institutional capacity-building; favorable economic conditions and viability; community, partner, and moral accountability; clear division of responsibilities through contracts; and effective advisory management. These effective measures may be useful in reducing the adverse effects of risk for PPP projects in China.     

Not all high-alexithymia individuals are risk-takers: private self-consciousness moderates the relationship between alexithymia and risk-taking behaviours

This article concerns the influence which alexithymia exerts on risk-taking. In particular, alexithymia is seen as a factor which encourages risk-taking as it allows high-alexithymia individuals to feel emotions which are sufficiently intense to compensate for their deficit of emotional awareness. In this connection, we make the hypothesis that alexithymia’s influence is moderated by private self-consciousness (SC). This is because private SC increases the likelihood that high-alexithymia individuals become aware of their risk-taking tendency and that this tendency is discrepant with their pro-safety standards (‘putting someone in danger is bad’) or self-schemas (‘I am a responsible person’). Thus, private SC is likely to enable and motivate them to consciously regulate their behaviour in a safer direction. This hypothesis was empirically tested by a questionnaire amongst 372 French drivers, whose SC, alexithymia, as well as their current adoption of eight risky behaviours (with a more detailed analysis of speeding). The use of conditional process analyses reveal no main effects of alexithymia and private SC but strong interaction effects, while controlling for other predictors. More precisely, when private SC is low high-alexithymia individuals break more the speed limits and adopt more frequently risky behaviours than low-alexithymia drivers. Conversely, when private SC is high, they are less risk-prone. As practical implication, we recommend the use of techniques increasing private SC amongst high-alexithymia persons.     

Public–private partnerships for nature-based tourist attractions: the failure of Seal Rocks

In 1998, the Seal Rocks Sea Life Centre opened on Phillip Island, Australia. It was a public–private partnership, with a privately funded tourist attraction built on a government-owned protected area. Almost immediately it was beset by problems and court action found in favour of the private developer, who was awarded $A37 million in damages, with ownership of the centre returning to the state. This article fills a gap in the literature examining public–private partnerships by considering this failed venture. It is a qualitative case study, analysing the 2003 appeal court judgement in the case and newspaper accounts from 1995 to 2004. Our findings highlight that deficiencies with the drafting of commercial contracts for public–private partnerships may limit the environmental and economic benefits that are being sought by governments through these arrangements. In this case, the application of a “best efforts” clause was critical, as it required that priority was given to the commercial success of the project over environmental and planning concerns. Furthermore, the development was a centralised decision made by the state government, affording very little input from local parks management and community stakeholders. Such a court finding has important ramifications for future developments of partnership agreements in nature-based tourism.     

The problem of employees' network centrality and supervisors' error in performance appraisal: A multilevel theory

This article reveals an unexplored paradox for HR managers: the centrality of an employee in the social network benefits performance but hampers performance appraisal because it affects supervisors' rating errors. Central employees can be erroneously rated high on performance even when they are not high performers because supervisors tend to overappraise their performance. A distinction is made between rating precision, which depends on supervisors' uncertainty regarding employees' performance, and rating accuracy, which depends on supervisors' bias in favor of employees. Employee centrality is posited to be beneficial to precision but deleterious to accuracy because it regulates the diffusion of positive information, status, and power, all of which distort supervisors' capacity and motivation to accurately appraise performance. It is then argued that rating errors caused by network centrality affect aggregate perceptions of justice in organizations. When employees are highly connected to each other in a dense network, organizations have a strong and positive justice climate. Yet when some employees are more central than others in a centralized network, organizations have a negative and weak justice climate. The article contributes to the literature because it identifies an unexplored dark side of network centrality and offers recommendations for HR managers to cope with its deleterious consequences and for scholars to study them.     

Conditional risk measures in a bipartite market structure

In this paper, we study the effect of network structure between agents and objects on measures for systemic risk. We model the influence of sharing large exogeneous losses to the financial or (re)insurance market by a bipartite graph. Using Pareto-tailed losses and multivariate regular variation, we obtain asymptotic results for conditional risk measures based on the Value-at-Risk and the Conditional Tail Expectation. These results allow us to assess the influence of an individual institution on the systemic or market risk and vice versa through a collection of conditional risk measures. For large markets, Poisson approximations of the relevant constants are provided. Differences of the conditional risk measures for an underlying homogeneous and inhomogeneous random graph are illustrated by simulations.     

A gossip based information fusion protocol for distributed frequent itemset mining

The computational complexity, huge memory space requirement, and time-consuming nature of frequent pattern mining process are the most important motivations for distribution and parallelization of this mining process. On the other hand, the emergence of distributed computational and operational environments, which causes the production and maintenance of data on different distributed data sources, makes the parallelization and distribution of the knowledge discovery process inevitable. In this paper, a gossip based distributed itemset mining (GDIM) algorithm is proposed to extract frequent itemsets, which are special types of frequent patterns, in a wireless sensor network environment. In this algorithm, local frequent itemsets of each sensor are extracted using a bit-wise horizontal approach (LHPM) from the nodes which are clustered using a leach-based protocol. Heads of clusters exploit a gossip based protocol in order to communicate each other to find the patterns which their global support is equal to or more than the specified support threshold. Experimental results show that the proposed algorithm outperforms the best existing gossip based algorithm in term of execution time.     

Virtual interlining within the European airport network: An airfare analysis

Virtual interlining, which covers the actively marketed or ‘non-hidden’ segment of all potential self-connecting flight itineraries, is often assumed to be a money-saving travel strategy. In this paper we assess the price difference between virtual interlined and ‘traditional’ flight itineraries within the intra-European airport network. We query Kiwi.com's recently developed Tequila platform, one of the few specialised online travel agencies (OTAs) offering both ‘traditional’ and virtual interlined flight itineraries, to obtain information on all available flights in the first week of August, October and December 2019. Using a series of sign tests, we investigate whether a statistically significant fare difference exists between the cheapest available (direct and/or indirect) ‘traditional’ and virtual interlined flight itineraries. Our results indicate a statistically significant fare difference between the cheapest indirect ‘traditional’ and the virtual interlined flight itineraries in favour of the latter. However, with regard to direct traditional flight itineraries the results are mixed. We explore the size and the scope of these patterns in more detail, and outline possible avenues for further research.     

基于ANP-PP-SPA的区域洪灾风险评价模型研究

针对现有洪灾风险评价模型的缺陷与不足,从致灾因子、孕灾因子、承灾因子和减灾因子4个方面,通过对14项评价指标的分析与计算,构建洪灾风险评价体系。洪灾风险评价体系以网络层次分析法(ANP)求解主观权重,投影寻踪法(PP)求解客观权重,主客观综合权重与集对分析理论(SPA)耦合,构建基于ANP-PP-SPA的洪灾风险评价模型。以广东省英德市为例,验证洪灾风险评价模型的适用性。计算结果表明,英德市2016年的洪灾风险属于中等级别,符合英德市2016年的实际情况。洪灾风险评价模型不仅综合考虑了评价指标间的相互关系,还较好地体现了洪灾风险的模糊性和随机性,能够为区域洪灾风险决策和洪水管理提供科学依据。     

Factors influencing consumers' purchase decision-making in O2O business model: Evidence from consumers' overall evaluation

Online-to-offline (O2O) has become a rapidly growing e-commerce model worldwide, but the factors influencing consumers' purchase decision-making have not been examined well. After exploring the working mechanism of the O2O model, we extract eleven indexes of consumers' overall evaluation in the O2O model with Crawlzilla and R techniques. Social network analysis (SNA) is adopted to build social networks reflecting consumers' overall evaluation in the O2O model. Based on the modified social network and the extracted subgraph, this study (N = 768) reveals consumers' overall evaluation behavior patterns in the O2O model by calculating network density, central potential, edge betweenness. The results show that shoppers overall evaluate the eleven indexes, especially perceived product quality, online product price, promotion intensity, business reputation, and product brand, which reflects the significant associations between the indexes. Among all the eleven evaluation indexes, perceived product quality, online product price, and business reputation dominate consumers’ decision-making behavior. When making purchase decisions, consumers not only overall consider online product price, perceived product quality, and business reputation but also balance perceived product quality, business reputation, and promotion intensity. Finally, we make some suggestions on marketing strategy for e-commerce companies.