Yanping Guo, Bingqing Xiong, Yongqiang Sun, Eric Tze Kuan Lim and Chee-Wee Tan
Peer-to-Peer Accommodation Service (P2PAS) has emerged as a novel paradigm that enables consumers to book temporary accommodation through P2PAS platforms (online transaction), and…
Abstract
Purpose
Peer-to-Peer Accommodation Service (P2PAS) has emerged as a novel paradigm that enables consumers to book temporary accommodation through P2PAS platforms (online transaction), and then reside in hosts' rooms (offline consumption). Due to potential variance in performance and conflict of interest between hosts and platforms, consumers may differ in their trust perceptions of the two parties, which in turn affects consumers' continuous usage of P2PAS. To this end, the authors endeavor to unravel the effect of consumers' trust incongruence on continuance intention, and to further elucidate the moderating influence of transaction and consumption risks on this relationship. This paper aims to discuss the aforementioned objectives.
Design/methodology/approach
This study collected data through an online survey of 408 P2PAS consumers. Polynomial modeling and response surface analysis were conducted to validate the hypothesized relationships.
Findings
Response surface analysis reveals that trust incongruence did not significantly affect consumers' continuance intention. However, continuance intention would be greater when TP was higher than TH compared with when TH was higher than TP. Furthermore, the analytical results suggest that trust incongruence exerts greater negative effect on continuance intention when transaction and consumption risks were high.
Originality/value
First, the study marks a paradigm shift in conceptualizing the incongruence between TP and TH as a determinant of consumers' continuance intention toward P2PAS. Second, the authors derive a typology of risks that is contextualized to P2PAS. Finally, the authors establish transaction and consumption risks as boundary conditions influencing the effects of trust incongruence on consumers' continuance intention toward P2PAS.
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Yuting Wang, Yao Chen, Jie Fang and Bingqing Xiong
Despite the popularity of leveraging cause-related marketing (CRM) to make societal contributions and bolster business profits, sellers face a profound dilemma when conducting CRM…
Abstract
Purpose
Despite the popularity of leveraging cause-related marketing (CRM) to make societal contributions and bolster business profits, sellers face a profound dilemma when conducting CRM due to consumers’ ambivalent understanding of sellers’ motivation for the initiative. Therefore, it is imperative to unravel consumers’ ambivalent understanding of CRM and determine how sellers can effectively employ CRM to elicit positive evaluations from consumers.
Design/methodology/approach
This study gathered survey data from 217 participants and applied a polynomial regression model and response surface analysis for disentangling ambivalent perception of CRM by investigating the influence of (in)congruence between perceived egoistic and altruistic motivation.
Findings
The incongruence between perceived egoistic and altruistic motivation can positively influence consumers’ evaluations of sellers. Moreover, when perceived egoistic and altruistic motivations are congruent, increasing their absolute level also enhances consumers’ evaluation of sellers. Moreover, sellers’ platform function usage behavior can amplify the positive effect of incongruence but has no salient moderating role on the congruence effect.
Originality/value
Differing from prior literature that predominantly focused on either the positive or negative interpretation of CRM, this study reveals the coexistence of both positive and negative viewpoints and disentangles the congruence and incongruence effect between the two motivational understandings.
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Ming-Hui Liu, Jianbin Xiong, Chun-Lin Li, Weijun Sun, Qinghua Zhang and Yuyu Zhang
The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to…
Abstract
Purpose
The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.
Design/methodology/approach
This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.
Findings
According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.
Research limitations/implications
In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.
Originality/value
Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.
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This study aims to propose a framework of bias in construction project dispute resolution (CPDR hereafter).
Abstract
Purpose
This study aims to propose a framework of bias in construction project dispute resolution (CPDR hereafter).
Design/methodology/approach
With reference to the literatures on effects of bias, manifestations of bias in CPDR were developed. Based on data obtained from construction professionals about their frequency of having these bias manifestations, the underlying constructs of biased behaviors were explored by a principal component factor analysis. A confirmatory factor analysis was further conducted to validate the framework of bias in CPDR.
Findings
Four types of bias were identified as the constructs that underlie biased behaviors in CPDR. These four biases were included in the bias framework proposed: preconception, self-affirmation, optimism and interest-oriented. The potency of these types of bias was also evaluated.
Practical implications
First, the findings inform that the existence of bias in CPDR is real. Early detection allows management to intervene and steer CPDR team back to rational courses. Second, this study suggests optimizing CPDR procedures to diminish the chance of bias occurring.
Originality/value
Bias is almost an uncharted area in CPDR. The study fills this research gap by conceptualizing the underlying constructs of biased behaviors. The findings inform construction professionals of the likelihood of practicing biased behaviors in CPDR. Repeated dispute decisions in the commonly used multi-tiered dispute resolution process would enable the creeping in of biases.
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A public–private partnership (PPP) is an agreement between the government and private investors to deliver long-term public services. The efficiency of PPP projects depends on PPP…
Abstract
Purpose
A public–private partnership (PPP) is an agreement between the government and private investors to deliver long-term public services. The efficiency of PPP projects depends on PPP contracts stipulating contractual parties' corresponding responsibilities and rights to deal with relational and performance risks. Although more complex contracts provide more remedies for mitigating ex-post transaction costs, they also result in the increased ex ante transaction costs associated with contract writing. Thus, contractual complexity is a design choice that can reduce the overall contract transaction costs.
Design/methodology/approach
Using 365 transportation PPP projects in China from 2010 to 2019, this study applies the Poisson regression model to examine the effects of payment mechanisms, ownership by investors and equity structure on contractual complexity.
Findings
PPP contracts have control and coordination functions with unique determinants. Parties in the government-pay mechanism are more likely to negotiate coordination provisions, which results in greater contractual complexity. PPP projects with state-owned enterprises (SOEs) have less contractual complexity in terms of both two functions of provisions, whereas the equity structure has no impact on contractual complexity.
Originality/value
These findings provide a nuanced understanding of how various contractual provisions are combined to perform control or coordination functions and make managerial recommendations to parties involved in PPP projects.
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Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Suhaiza Zailani and Mohammad Iranmanesh
Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general…
Abstract
Purpose
Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general overview of the academic landscape concerning PPP.
Design/methodology/approach
To offer a nuanced perspective, the study adopts the Latent Dirichlet Allocation (LDA) methodology to meticulously analyse 3,057 journal articles, mapping out the thematic contours within the PPP domain.
Findings
The analysis highlights PPP's pivotal role in harmonising public policy goals with private sector agility, notably in areas like disaster-ready sustainable infrastructure and addressing rapid urbanisation challenges. The emphasis within the literature on financial, risk, and performance aspects accentuates the complexities inherent in financing PPP and the critical need for practical evaluation tools. An emerging focus on healthcare within PPP indicates potential for more insightful research, especially amid ongoing global health crises.
Originality/value
This study pioneers the application of LDA for an all-encompassing examination of PPP-related academic works, presenting unique theoretical and practical insights into the diverse facets of PPP.
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Zhen Hu, Qianmeng Li, Tingting Liu, Lu Wang and Zhe Cheng
Public private partnership (PPP) has gained increasing popularity around the globe. Whether the government needs to participate in the PPP special purpose vehicle (SPV) as an…
Abstract
Purpose
Public private partnership (PPP) has gained increasing popularity around the globe. Whether the government needs to participate in the PPP special purpose vehicle (SPV) as an equity coinvestor is a critical issue in PPP development. This research aims to examine the influence of government equity investment on PPP performance by taking public-private communication as an intermediate variable.
Design/methodology/approach
A questionnaire survey was adopted as the main research method. PPP practitioners with extensive experiences from both the public and private sectors were targeted respondents. The survey results were subsequently analyzed using statistical data analysis method.
Findings
Based on the results from the questionnaire survey, this research indicates an inverted U-shaped relationship between the ratio of government equity and performance in PPP projects. In addition, communication plays a mediating role between government equity investment and PPP project performance.
Originality/value
This research explicates the relationship between the equity structure in a PPP SPV and the project performance. It provides important guidance and reference for PPP practitioners to structure the SPV and associated financial and commercial arrangements. It also offers valuable insights into the development of PPP policy, especially regarding the structuring of PPP models in China and elsewhere.
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Weijiang Wu, Heping Tan and Yifeng Zheng
Community detection is a key factor in analyzing the structural features of complex networks. However, traditional dynamic community detection methods often fail to effectively…
Abstract
Purpose
Community detection is a key factor in analyzing the structural features of complex networks. However, traditional dynamic community detection methods often fail to effectively solve the problems of deep network information loss and computational complexity in hyperbolic space. To address this challenge, a hyperbolic space-based dynamic graph neural network community detection model (HSDCDM) is proposed.
Design/methodology/approach
HSDCDM first projects the node features into the hyperbolic space and then utilizes the hyperbolic graph convolution module on the Poincaré and Lorentz models to realize feature fusion and information transfer. In addition, the parallel optimized temporal memory module ensures fast and accurate capture of time domain information over extended periods. Finally, the community clustering module divides the community structure by combining the node characteristics of the space domain and the time domain. To evaluate the performance of HSDCDM, experiments are conducted on both artificial and real datasets.
Findings
Experimental results on complex networks demonstrate that HSDCDM significantly enhances the quality of community detection in hierarchical networks. It shows an average improvement of 7.29% in NMI and a 9.07% increase in ARI across datasets compared to traditional methods. For complex networks with non-Euclidean geometric structures, the HSDCDM model incorporating hyperbolic geometry can better handle the discontinuity of the metric space, provides a more compact embedding that preserves the data structure, and offers advantages over methods based on Euclidean geometry methods.
Originality/value
This model aggregates the potential information of nodes in space through manifold-preserving distribution mapping and hyperbolic graph topology modules. Moreover, it optimizes the Simple Recurrent Unit (SRU) on the hyperbolic space Lorentz model to effectively extract time series data in hyperbolic space, thereby enhancing computing efficiency by eliminating the reliance on tangent space.
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Xing Yao, Shao-Chao Ma, Ying Fan, Lei Zhu and Bin Su
The ongoing urbanization and decarbonization require deployment of energy storage in the urban energy system to integrate large-scale variable renewable energy (VRE) into the…
Abstract
Purpose
The ongoing urbanization and decarbonization require deployment of energy storage in the urban energy system to integrate large-scale variable renewable energy (VRE) into the power grids. The cost reductions of batteries enable private entities to invest energy storage for energy management whose operating strategy may differ from traditional storage facilities. This study aims to investigate the impacts of energy storage on the power system with different operation strategies. Two strategies are modeled through a simulation-based regional economic power dispatch model. The profit-oriented strategy denotes the storage system operated by private entities for price arbitrage, and the nonprofit-oriented strategy denotes the storage system dispatched by an independent system operator (ISO) for the whole power system optimization. A case study of Jiangsu, China is conducted. The results show that the profit-oriented strategy only has a very limited impact on the cost reductions of power system and may even increase the cost for consumers. While nonprofit-oriented energy storage performs a positive effect on the system cost reduction. CO2 emission reduction can only be achieved under a high VRE scenario for energy storage. Integrating energy storage into the power system may increase CO2 emissions in the near term. In addition, the peak-valley spread is crucial to trigger operations of profit-oriented energy storage, and the profitability of energy storage operator is observed to be decreasing with the total storage capacity. This study provides new insights for the energy management in the smart city, and the modeling framework can be applied to regions with different resource endowments.
Design/methodology/approach
The authors characterize two battery storage operating strategies of profit- and nonprofit-oriented by adopting a simulation-based economic dispatch model. A simulation from 36 years of hourly weather data of wind and solar output from case study of Jiangsu, China is conducted.
Findings
The results show that the profit-oriented strategy only has a very limited impact on the cost reductions of power system and may even increase the cost for consumers. While nonprofit-oriented energy storage performs a positive effect on the system cost reduction. CO2 emission reduction can only be achieved under high VRE scenario for energy storage. Integrating energy storage into the power system may increase CO2 emissions in the near term. In addition, the peak-valley spread is crucial to trigger operations of profit-oriented energy storage, and the profitability of energy storage operator is observed to be decreasing with the total storage capacity.
Originality/value
This study provides new insights for the energy management in the smart city, and the modeling framework can be applied to regions with different resource endowments.