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Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

This study aims to focus on the impact of multi-level knowledge sharing between and within organizations on the risk control of rural inclusive finance. The paper presents a synergistic risk control system integrating external and internal factors for rural inclusive finance by constructing different knowledge-sharing platforms in an environment, which is full of many uncertainties.

This study is based on survey methods. To achieve the research objectives, the authors adopt a single case study approach. For data collection, the authors apply a wide variety of methods such as semi-structured interviews, field visits, second-hand databases and official websites.

The results emphasize that using multi-level knowledge sharing such as the inter- and intra-organizational level, can facilitate the risk control of rural inclusive finance during the post-COVID-19 era. Furthermore, it is also noted that achieving knowledge sharing at different levels by building diverse knowledge-sharing platforms can promote the risk control of rural inclusive finance from the individual-organization level to the chain level of multi-organization collaboration, which contributes to the formation of symbiotic risk control ecology.

The authors have formed the “Chinese wisdom” to deal with inclusive financial risks and to promote in-depth development in relation to the “last mile” practice of inclusive finance, which means the final and the most important phase of a project. The conclusions contribute to enriching the outcomes regarding the risk control of rural inclusive finance, provide experiences to its sustainable development and offer a reference to other countries with their risk control of rural inclusive finance.

Drawing on the knowledge-sharing approach, this study creatively resolves the persistent problems in the risk control of rural inclusive finance, which forms a powerful supplement to the extant literature. Meanwhile, the paper combines the two contextual factors of the post-COVID-19 era and emerging economies, which can be deemed as a novel attempt.

This study aims to assess the knowledge-sharing risks and controls in the government sector from the knowledge workers’ perspective.

This qualitative study combines two techniques. First, the study uses the Delphi technique to identify the risks and rank them. Second, the study used a follow-up interview approach to identify the needed controls to mitigate these identified risks.

The Delphi study revealed the top knowledge-sharing risks are related to organizational and individual risks. Furthermore, the study identified the top controls that needed to mitigate these identified risks from technology, process and people dimensions. The study findings suggested that implementing controls on people and processes is the most important, and the focus must be on them, especially in the government sector.

The study offers several practical implications for the government sector to establish a knowledge-sharing risks management strategy. Such study has been given little attention in previous research, especially in developing countries.

The purpose of this study is to investigate the role of procurement digitalization in reducing uncertainty in the supply chain (SC) and how it relates to mitigating SC risks and improving SC resilience (SCRES).

Based on survey data collected from the procurement functions of 147 Finnish firms, this study conceptualizes data analytics, information sharing and procurement process digitalization as drivers of procurement digitalization and investigates their impact on SC risk management and SCRES by using partial least squares path modeling.

Procurement digitalization through data analytics and digital process maturity requires effective information sharing among SC partners and SC risk management to be able to improve SCRES. Procurement digitalization increases information-processing capacities and reduces uncertainty in the SC.

This study contributes to the understanding on the relationships between procurement digitalization and SCRES.

This study aims to establish a centralized decision-making game model and manufacturer-led Stackelberg game model based on factors of risk aversion of supply chain members and product greenness. The research aims to study whether the introduction of the “cost + risk sharing” contract affects coordination of this type of green supply by calculating the optimal decision of each mode.

This research designs a supply chain model under centralized and decentralized decision-making. This model uses the Stackelberg game to calculate the optimal decision under decentralized decision-making to evaluate the effect of a green supply chain and then analyze the “cost + risk sharing” contract and the degree of coordination of the supply chain. A sensitivity analysis is conducted on the centralized mode for the impact of variables on the supply chain.

This research finds a double marginalization effect in decentralized decision-making, and the risk aversion coefficient plays a decisive role in the utility of supply chain members. The specific range of risk- and cost-sharing factors allows supply chain members to achieve Pareto improvements and provides decision-making based on the corresponding management strategies according to each other’s risk preference degree.

The influence of each variable on the green supply chain in the centralized mode is studied by MATLAB numerical simulation. It provides reference for green supply chain members to formulate corresponding management strategies according to each other's risk preference degree.

This research innovatively considers manufacturers and retailers to explore the market demand for product greenness. It introduces a novel “cost + risk sharing” contract to coordinate the green supply chain.

Information asymmetry and poor solvency caused by uncertainties in supply chains are the root causes of supply chain financing risks (SCFR). The purpose of this paper is to explore the effect of supply chain integration on reducing SCFR by incorporating the mechanisms of information sharing and controlling supply chain risks (SCR).

This paper proposes hypothesis to discuss the impact of integration on SCFR and the mediating roles of alleviating information asymmetry and mitigating SCR, aiming at discovering factors and mechanisms to reduce SCFR. The research model was validated by applying structural equation modeling on survey data from 321 Chinese small and medium-sized enterprises (SMEs).

Integration significantly reduces SCFR by dual approaches of information sharing and mitigating SCR, confirming that alleviating information asymmetry to reach information transparency and controlling SCR to reduce uncertainties facilitate less SCFR.

SMEs should enhance integration capability to reduce SCFR as it greatly influences the evaluation of financial service providers on SMEs and the sustainable financing capacity of SMEs. Additionally, any other methods that can improve information sharing and reduce SCR should be attached if possible.

This study represents a pioneering attempt to analyze the impact of integration on reducing SCFR by exploring the specific mechanisms of alleviating information asymmetry and mitigating SCR. Meanwhile, few prior empirical studies have highlighted the importance of SCFR.

This study investigates the relationship between credit booms and bank risk in Association of Southeast Asian Nations (ASEAN) countries, with credit information sharing acting as a moderator.

The authors use a two-step System Generalized Method of Moments (SGMM) estimator on a sample of 79 listed banks in 5 developing ASEAN countries: Indonesia, Philippines, Malaysia, Thailand and Vietnam in the period 2006–2019. In addition, the authors perform robustness tests with different proxies for credit booms and bank risk. The data are collected on an annual basis.

Bank risk is positively related to credit booms and is negatively associated with credit information sharing. Further, credit information sharing reduces the detrimental effect of credit booms on bank stability. The authors find that both public credit registries and private credit bureaus are effective in enhancing bank stability in ASEAN countries. These results are robust to regression models with alternative proxies for credit booms and bank risk.

Banks in ASEAN countries tend to have strong lending growth to support the economy, but this could be detrimental to stability of the sector. Credit information sharing schemes should be encouraged because these schemes might enable growth of credit without compromising bank stability. Therefore, policymakers could promote private credit bureaus (PCB) and public credit registries (PCR) to realize their benefits. The authors' research focuses on developing ASEAN countries, but future research could provide more evidence by expanding this study to other emerging economies. In-depth interviews and surveys with bankers and regulatory bodies about these concerns could provide additional insights in the future.

The study is the first to examine the role of PCB and PCR in alleviating the negative impact of credit booms on bank risk. Furthermore, the authors use both accounting-based and market-based risk measures to provide a fuller view of the impact. Finally, there is little evidence on the link between credit booms, credit information sharing and bank risk in ASEAN, so the authors aim to fill this gap.

This paper aims to clarify how organizations manage their participation in networks to share and jointly create knowledge but also risk unwanted knowledge spillovers at the same time. As formal governance, trust and observation are less applicable in informal networks, the authors need to understand how members address the need to protect knowledge by informal practices. The study aims to investigate how the application of knowledge protection practices affects knowledge sharing in networks. The insights are relevant for organizational and network management to control knowledge risks but harvest the benefits of network engagement.

The authors opted for an exploratory study based on 60 semi-structured interviews with members of 10 networks. In two rounds, network managers, representatives and members of the networks were interviewed. The second round of interviews was used to validate the intermediate findings. The data were complemented by documentary analysis, including network descriptions.

Through analyzing and building on the theory of psychological contracts, two informal practices of knowledge protection were found in networks of organizations: exclude crucial topics and share on selected topics and exclude details and share a selected level of detail. The authors explored how these two practices are enacted in networks of organizations with psychological contracts.

Counter to intuition that the protection of knowledge can be strengthened only at the expense of knowledge sharing and vice versa, networks benefitted from more focused and increased knowledge sharing while reducing the risk of losing competitive knowledge by performing these knowledge protection practices.

Public-private partnership (PPP) projects for construction waste recycling have become the main approach to construction waste treatment in China. Risk sharing and income distribution of PPP projects play a vital role in achieving project success. This paper is aimed at building a practical and effective risk sharing and income distribution model to achieve win–win situation among different stakeholders, thereby providing a systematic framework for governments to promote construction waste recycling.

Stakeholders of construction waste recycling PPP projects were reclassified according to the stakeholder theory. Best-worst multi–criteria decision-making method and comprehensive fuzzy evaluation method (BWM–FCE) risk assessment model was constructed to optimize the risk assessment of core stakeholders in construction waste recycling PPP projects. Based on the proposed risk evaluation model for construction waste recycling PPP projects, the Shapley value income distribution model was modified in combination with capital investment, contribution and project participation to obtain a more equitable and reasonable income distribution system.

The income distribution model showed that PPP Project Companies gained more transaction benefits, which proved that PPP Project Companies played an important role in the actual operation of PPP projects. The policy change risk, investment and financing risk and income risk were the most important risks and key factors for project success. Therefore, it is of great significance to strengthen the management of PPP Project Companies, and in the process of PPP implementation, the government should focus on preventing the risk of policy changes, investment and financing risks and income risks.

The findings from this study have advanced the application methods of risk sharing and income distribution for PPP projects and further improved PPP project-related theories. It helps to promote and rationalize fairness in construction waste recycling PPP projects and to achieve mutual benefits and win–win situation in risk sharing. It has also provided a reference for resource management of construction waste and laid a solid foundation for long-term development of construction waste resources.

PPP mode is an effective tool for construction waste recycling. How to allocate risks and distribute benefits has become the most important issue of waste recycling PPP projects, and also the key to project success. The originality of this study resides in its provision of a holistic approach of risk allocation and benefit distribution on construction waste PPP projects in China as a developing country. Accordingly, this study adds its value by promoting resource development of construction waste, extending an innovative risk allocation and benefit distribution method in PPP projects, and providing a valuable reference for policymakers and private investors who are planning to invest in PPP projects in China.

Collaboration methods are unique strategies that can help organizations hedge against external and internal supply chain risks without stressing their relationships with supply chain partners. However, selecting the most appropriate collaboration method from a given set of strategies is a multifaceted challenge. This paper aims to address this issue.

The decision maker's dilemma of fighting data uncertainty in input parameters to check the efficacy of a given collaboration or mitigation approach is tackled by the integration of Grey theory with the technique for order of preference by similarity to ideal solution (TOPSIS) method. The proposed technique is applied and tested for an Indian diesel generator-set manufacturer to identify the most apposite set of sustainable collaboration strategies.

The results showed that when a firm is bidding for different horizontal collaboration strategies across its supply chain system technology and resource-sharing-centered collaboration strategies are the prominent option. In the case of the company's vertical collaboration deployment, the focus should be kept on information sharing to achieve impactful collaboration. The outcome of the analysis helped the Indian manufacturer to adopt transparent order and production information sharing with its regional distributors and core suppliers within its supply chain.

This study demonstrates from a methodological perspective the successful application of the Grey-TOPSIS approach that effectively captures data uncertainty. It also integrates sustainability parameters in collaboration strategy criteria selections.