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Using protest event analysis, this study aims to investigate which risk factors influence the severity of environmental protests in China, thus filling a gap in China-related environmental protest literature.

Using a database derived from media coverage of 129 environmental protests in China from 2009 to 2015, this empirical study identifies underlying risk factors influencing environmental protest severity, quantifies these protest cases and verifies the associations between risk factors and severity using ordered logistic regression.

The results show that higher environmental health threat, economic loss, distrust of local government, lack of local governmental response, improper local government action and higher population density are likely to increase environmental protest severity; however, contrary to expectations, environmental information disclosure has no significant effect. These findings illuminate the vital and variational role of local government throughout all stages of the evolutionary process in environmental protests. Moreover, public distrust of local government is the principal cause of these protests.

This study enhances the understanding of how Chinese environmental protests arise from the identified risk factors and contributes to quantitative multi-case research in this area. Furthermore, the findings may help local governments in China, as well as in other countries, to enact positive measures to prevent serious environmental protests and improve their ability to address the environmental problems that cause protests. More effective governance can decrease the number and severity of environmental protests and thus promote social stability.

The goal of this study is to investigate the relationships among brand attachment, online source credibility, and severity of negative online information on perceived negative change in brand evaluation and perceived brand risk.

A 2×2×2 experiment was conducted to explore the effects of brand attachment (low or high), online source credibility (low or high), and online information severity (low or high) on perceived negative change in brand evaluation and perceived brand risk.

The results showed that the severity of negative online information affects perceived negative change in brand evaluation and perceived brand risk significantly. However brand attachment can reduce the effects of negative online information on perceived negative change in brand evaluation and perceived brand risk significantly. The results also showed that the effect of the severity of negative online information on perceived negative change in brand evaluation and perceived brand risk is moderated by online source credibility.

In addition to the main effects in the proposed research model, it is the first study to explore the moderating effects of brand attachment and online source credibility on the relationship between negative online information and perceived negative change in brand evaluation and perceived brand risk.

Modular integrated construction (MiC) reengineers the traditional construction process. By introducing factory production and onsite assembly (OA) of modules, MiC reinvents construction projects' uncertainties and risk profiles. The OA stage constitutes the highest end of the MiC delivery and supply chains, where several inherited and symbiotic errors and risk events become realities, negatively impacting the MiC project's success. This study explored the severities of OA risk factors for MiC projects.

A comprehensive literature review, consultation of experts and a questionnaire survey of domain experts were conducted to assess the severity of fifteen OA risk factors for MiC projects. The risk severity index was used to compute and rank the severities of critical OA risk factors for MiC projects, followed by proposed mitigation strategies.

The study revealed that the top five OA risk factors with the severest impact on MiC projects include modules installation discrepancies and errors, poor cooperation among critical onsite stakeholders, a mismatch between production schedules and site conditions, improper lifting equipment selection for onsite installation and site-fit rework due to discrepancies in drawings.

This study is the first to offer some important insights into the uncertainties that could compromise the OA objectives of MiC projects. It discussed risk management strategies for known and unknown OA risks and made a unique contribution to the theory, practice, and praxis of MiC supply chain risk management.

Risk control programs of modern complex organizations make extensive use of stochastic models. The purpose of this paper is to consider a class of stochastic models in severity and risk duration reduction operations.

A new stochastic model is formulated which is shown to be of some importance in fundamental risk management operations. The investigation of such a model is based on classical methods of characteristic functions theory.

A stochastic model having the form of the product of two non‐negative and independent random variables is formulated. A characterization of the distribution of such a model is established. Moreover, applications of the proposed stochastic model in risk control programs of organizations are provided.

The difficulty of evaluating the corresponding distribution function, which extends the practical applicability of the proposed stochastic model still remains.

The formulated stochastic model consists of a strong analytical tool for investigating operations of risk control programs.

Global trade depends on more complex, prolonged and larger port systems, where port logistics is a backbone for such operations. Ports are responsible for transferring more than 80 percent of the global trade. Port logistics are prone to being risk-oriented. The study proposes a model to study various port logistics barriers and their associated risks for emerging economies in the Industry 4.0 era.

The study develops a framework by integrating the fuzzy set theory, the evidential reasoning approach and the expected utility theorem for identifying the severity value of port logistics barriers under the Industry 4.0 era for emerging economies and prioritize them based on various perspectives. The study identifies multiple risks associated with the barriers, and intensity-based categorization of the risks is performed for risk profiling.

The study reveals that poor infrastructure, nonsupportive policy ecosystem, and lack of research and development are the top barriers that need immediate attention. A new approach has been proposed that changes the importance of perspectives, and 192 analytical experiments were done to study the changing behavior of barriers. The study also presents various types of risks associated with the selected barriers.

In future studies, other barriers can be discovered and studied to develop such models. To cover the entire spectrum of possibilities, belief degrees of the barriers could be used to study the barriers instead of changing the weights.

This study presents a quantification model to prioritize the barriers based on environmental, economic and operational perspectives. Further, the model helps create scenarios for decision-makers to improve port logistics performance and achieve sustainability. The study identifies various risks associated with port logistics barriers and allows decision-makers to take proactive actions.

This study contributes significantly to the literature on port logistics by developing a framework for determining the severity of the barriers in the Industry 4.0 era for emerging economies. Further, the study pinpoints various risks associated with port logistics, and risk profiling is carried out.

As global supply networks proliferate, the strategic significance of supply chain risk management (SCRM) – defined as the identification, evaluation, and management of supply chain-related risks to reduce overall supply chain vulnerability – also increases. Yet, despite consistent evidence that firm performance is enhanced by appropriate fit between strategy and context, extant SCRM research focusses more on identifying sources of supply chain risk, types of SCRM strategy, and performance implications associated with SCRM than on the relative efficacy of alternative primary supply chain risk mitigation strategies in different risk contexts. Drawing on contingency theory, a conceptual framework is proposed that aligns well-established aspects of SCRM to present a rubric for matching primary alternative supply chain risk mitigation strategies (redundancy and flexibility) with particular risk contexts (severity and probability of risk occurrence). The paper aims to discuss these issues.

Conceptual paper.

The proposed framework addresses supply chain managers’ need for a basic rubric to help them choose and implement risk mitigation approaches. The framework may also prove helpful for introducing business students to the fundamentals of SCRM.

The framework and associated research propositions provide a theoretically grounded basis for managing the firm’s portfolio of potential supply chain risks by applying appropriate primary risk mitigation strategies based on the specific context of each risk rather than taking a “one size fits all” approach to risk mitigation. An agenda for progressing research on contingency-based approaches to SCRM is also presented.

This paper aims to help understand how adopting risk allocation criteria impacts the delivery of public–private partnership (PPP) mass housing in Nigeria with the view of promoting the adoption of PPP housing scheme in Nigeria.

The research design adopts the census sampling approach by using well-structured questionnaires distributed to stakeholders involved in PPP-procured mass housing projects, i.e. consultants, in-house professionals, contractors and the organized private sector, registered with PPP departments in the Federal Capital Territory Development Authority, Abuja, Nigeria. Sixty-three risk factors, nine risk allocation criteria and nine project delivery indices were submitted for the respondents to rank on a Likert scale of 7. Two hypotheses were formulated to test whether the risk allocation criteria impacted PPP mass housing delivery or otherwise. The study adopts partial least square-structural equation modeling to model the effect of risk on risk allocation criteria on project delivery indices and risk severity.

The finding shows that project risk allocation criteria have less effect on project delivery indices than on risk severity. The study concludes that risk allocation principles do not directly affect the delivery of PPP-procured mass housing projects. This is evident by the path coefficient of 0.724 values, which is not statistically significant at a 5% alpha protection value. The study concludes that allocating critical risk factors influences the performance of PPP-procured mass housing projects, as the path coefficient of 0.360 is also not significantly far from 0 and at a 5% alpha protection value.

The study is one of the recent studies conducted in PPP-procured mass housing projects in Nigeria owing to the novelty of procurement option in the sector. It highlights the risk factors that can jeopardize the PPP-procured mass housing project objectives. The study is of immense value to PPP actors in the sector by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP mass housing projects.

The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).

The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.

A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.

HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.

The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.

This research investigates the financial viability risk factors that threaten the private investor's economic scheme in the public private partnership (PPP) wastewater treatment plant (WWTP) projects in Egypt. The aims of this study are to: (1) illustrate and cluster the financial viability risk factors in accordance with the PPP WWTP projects' nature, (2) assess the risk factors' criticality degrees according to their severity and frequency levels of the financial viability, and (3) pinpoint the suited allocation of the financial viability risk factors between the public and private parties.

Relying on the previous analysts' endeavors, the questionnaire method, the fuzzy synthetic evaluation approach and the hypothetical normal distribution curve model; the severity, frequency, criticality and allocation preference of 32 financial viability risk factors were assessed from 12 Egyptian PPP experts.

The data analysis yielded that foreign exchange risk, currency risk/inflation, license risk, construction cost-overrun and late site handover are the key factors in arising the financial viability risk issue in the PPP WWTP projects. Considering the discussion of these key risks, the study summarized that the financial viability's key risk factors are notably be affected by the economic, political and administrative circumstances of the host county. Additionally, the inflation lesion was found to be the core reason of most of the key risk factors.

This research originality stems from its contribution to address the gab in the PPP risk assessment literature of the concessionaire's financial viability in the WWTP projects in a country of developing economy as Egypt. This, first, enriches the scholarly based knowledge of the PPP projects' risk analysts of the developing countries. Accordingly, it moves the current PPP risk assessment research further to deeply apprehend these markets' risks. Second, it equips the policymakers in the public and private sectors of such projects with a map that clarifies their assigned risk factors and the responsibilities that each party should bear to generate a mutual stable investment environment for achieving their aims successfully. This, indeed, paves the way for more private investments to be involved in the developing markets' PPP projects with a profitable satisfactory level for the private concessionaire. In the same vein, more WWTP projects, which are highly needed for the public sector and its people, are executed.

A huge number of events can affect the operations of a long and complicated supply chain. This paper deals with the development of a supply chain risk mitigation index (SCRMI) based on a risk mitigation maturity framework. A comprehensive list of supply chain risks has been ascertained and segregated into risks faced at various supply chain echelons through a detailed literature review.

This paper is based on an extensive literature review and questionnaire to identify risks. order of magnitude analytic hierarchy process (OM-AHP) was used as the methodology to assess the prioritization of supply chain risks under two clusters, viz., Probability and severity leading to risk were tested in a distillery.

SCRMI was determined and used to categorize their maturity level in facing supply chain risks. Thus, organization can focus on improvements for their specific needs.

The model was tested in the distillery industry. It should be tested in other contexts with other methods to provide generalizability.

This research provides direction to managers for choosing risk mitigation strategies based on the global supply chain environment. SCRMI can be a performance metric for the supply chain managers.

The manufacturer's readiness to take action in the face of disruptions in the supply chain is a critical challenge in today's complex business environment and SCRMI framework is instrumental in such business environment.