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Many governments are taking measures in support of small and medium-sized enterprises (SMEs) to mitigate the economic impact of the COVID-19 outbreak. This paper presents a theoretical model for evaluating various government measures, including insurance for bank loans, interest rate subsidy, bridge loans and relief of tax burdens.

This paper distinguishes a firm's intrinsic value and book value, where a firm can lose its intrinsic value when it encounters cash-flow crunch. Wang transform is applied to (1) calculating the appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs, (2) describing the frailty distribution for SMEs and (3) defining banks' underwriting capability and overlap index in risk selection.

Government support for SMEs can be in the form of an appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs.

More available data on bank loans would have helped strengthen the empirical studies.

This paper makes policy recommendations of establishing policy-oriented banks or investment funds dedicated to supporting SMEs, developing risk indices for SMEs to facilitate refined risk underwriting, providing SMEs with long-term tax relief and early-stage equity-type investments.

The model highlights the importance of providing bridge loans to SMEs during the COVID-19 disruption to prevent massive business closures.

This paper provides an analytical framework using Wang transform for analyzing the most effective form of government support for SMEs.

This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.

The purpose of this paper is to provide implementation insights and implications regarding the strategic orientations of servitization by testing its impacts on firm performance, including financial performance and customer service performance.

Empirical research is conducted using an online survey disseminated to manufacturing firms in Southeast China. This research develops and verifies a strategic fit framework to understand the relationship between the strategic orientation of servitization and service innovation (SI), and its resulting impacts on firm performance.

The results show that service orientation (SO) has direct positive impacts on firm performance in the manufacturing sector. Customer orientation (CO) and learning orientation (LO) have no direct impact on firm performance, although they have indirect impacts on it via the mediating role of SI capability. Moreover, SO has a similar indirect impact on firm performance via SI capability.

The survey focuses only on China; future studies should verify whether different cultural backgrounds impact the research results.

The results suggest that firms should build up three strategic orientations (SO, CO and LO) for implementing servitization to facilitate SI capability and, thus, to improve firm performance.

This research contributes to enhancing the theory of servitization by developing a strategic fit model of servitization and revealing the impact mechanism of servitization in the manufacturing sector.

With the aid of naturalistic simulations, this paper aims to investigate human behavior during manual and autonomous driving modes in complex scenarios.

The simulation environment is established by integrating virtual reality interface with a micro-simulation model. In the simulation, the vehicle autonomy is developed by a framework that integrates artificial neural networks and genetic algorithms. Human-subject experiments are carried, and participants are asked to virtually sit in the developed autonomous vehicle (AV) that allows for both human driving and autopilot functions within a mixed traffic environment.

Not surprisingly, the inconsistency is identified between two driving modes, in which the AV’s driving maneuver causes the cognitive bias and makes participants feel unsafe. Even though only a shallow portion of the cases that the AV ended up with an accident during the testing stage, participants still frequently intervened during the AV operation. On a similar note, even though the statistical results reflect that the AV drives under perceived high-risk conditions, rarely an actual crash can happen. This suggests that the classic safety surrogate measurement, e.g. time-to-collision, may require adjustment for the mixed traffic flow.

Understanding the behavior of AVs and the behavioral difference between AVs and human drivers are important, where the developed platform is only the first effort to identify the critical scenarios where the AVs might fail to react.

This paper attempts to fill the existing research gap in preparing close-to-reality tools for AV experience and further understanding human behavior during high-level autonomous driving.

This work aims to systematically analyze the inconsistency in driving patterns between manual and autopilot modes in various driving scenarios (i.e. multiple scenes and various traffic conditions) to facilitate user acceptance of AV technology.

A close-to-reality tool for AV experience and AV-related behavioral study. A systematic analysis in relation to the inconsistency in driving patterns between manual and autonomous driving. A foundation for identifying the critical scenarios where the AVs might fail to react.

This study aims to investigate the influence of CEO’s only-child status on corporate social responsibility (CSR) practices. It seeks to extend the understanding of upper echelon theory by examining unexplored CEO characteristics and their impact on CSR decisions.

The paper uses manually collected CEO family information and Chinese Stock and Market Accounting Research data as a basis to examine the influence of CEOs’ early-life experiences on their engagement in CSR activities. The study applies attachment security theory from developmental psychology and uses upper echelon theory, particularly focusing on CEOs’ only-child status. A comparative analysis of philanthropic donations between CEOs who are only children and those who have siblings is conducted. The study also examines the moderating effects of corporate slack resources and CEO shareholdings.

Preliminary findings suggest that CEOs who are only children are more likely to engage in CSR compared to their counterparts with siblings. However, the difference in donation amounts between the two groups tends to attenuate with decreased slack resources and increased CEO shareholdings.

To the best of the authors’ knowledge, this research represents the first attempt to investigate being the only child in one’s family and the CSR-related decision of CEOs, which extends the upper echelon theory by introducing the family science theory into the management domain.

The purpose of this paper is to test the invulnerability of the guarantee network at the equilibrium point.

This paper introduces a tractable guarantee network model that captures the invulnerability of the network in terms of cascade-based attack. Furthermore, the equilibrium points are introduced for banks to determine loan origination.

The proposed approach not only develops equilibrium analysis as an extended perspective in the guarantee network, but also applies cascading failure method to construct the guarantee network. The equilibrium points are examined by simulating experiment. The invulnerability of the guarantee network is quantified by the survival of firms in the simulating progress.

There is less study in equilibrium analysis of the guarantee network. Additionally, cascading failure model is expressed in the presented approach. Moreover, agent-based model can be extended in generating the guarantee network in the future study.

The approach of this paper presents a framework to analyze the equilibrium of the guarantee network. For this, the systemic risk of the whole guarantee network and each node's contribution are measured to predict the probability of default on cascading failure. Focusing on cascade failure process based on equilibrium point, the invulnerability of the guarantee network can be quantified.

The purpose of this paper is to investigate the impact of strategic collaboration (SC) on sustainable supply chain management (SSCM), considering the mediating role of internal knowledge sharing (IKS) and external knowledge sharing (EKS).

The study population consisted of experts associated with the supply chain in the automotive, food, clothing, pharmaceuticals and chemicals industries. After reviewing the literature, a conceptual framework was developed and applied using a structural equation modeling approach. In this study, samples with 271 observations were collected from manufacturing and servicing companies in Iran.

The results showed that SC in the supply chain has a positive impact on the IKS and EKS and SSCM. IKS and EKS have a positive impact on SSCM. Also, the results showed that IKS and EKS fully mediate in the relationship between SC and SSCM.

This study has been done in the context of Iran, so caution should be taken to generalize the results.

The findings of the study contribute to the knowledge of the managers and policy makers in achieving SSCM. The results provide the important environmental and social concepts regarding the sustainability of supply chain using SC and IKS and EKS.

The purpose of this paper is to present a family of robust metasurface-oriented wireless power transfer systems with improved efficiency and size compactness. The effect of geometric and structural features on the overall efficiency and miniaturisation is elaborately studied, while the presence of substrate losses is, also, considered. Moreover, to further enhance the performance, possible means for reducing the operating frequency, without comprising the unit-cell size, are proposed.

The key element of the design technique is the edge-coupled split-ring resonators patterned in various metasurface configurations and optimally placed to increase the total efficiency. To this goal, a rigorous three-dimensional algorithm, launching a new high-order prism macroelement, is developed in this paper for the fast evaluation of the required quantities. The featured scheme can host diverse approximation orders, while it is drastically more economical than existing methods. Hence, the demanding wireless power transfer systems are precisely modelled via reduced degrees of freedom, without the need to conduct large-scale simulations.

Numerical results, compared with measured data from fabricated prototypes, validate the design methodology and prove its competence to provide enhanced metasurface wireless power transfer systems. An assortment of optimized 3 x 3 and 5 x 5 metamaterial setups is investigated, and interesting deductions, regarding the impact of the inter-element gaps, the distance between the transmitting and receiving components and the substrate losses, are derived. Also, the proposed vector macroelement technique overwhelms typical implementations in terms of computational burden, particularly when combined with the relevant commercial software packages.

Systematic design of advanced real-world wireless power transfer structures through optimally selected metasurfaces with fully controllable electromagnetic properties is presented. The analysis is performed by means of a rapid prism macroelement methodology, which leads to very confined meshes, accurate results and significantly reduced overhead. The selected metamaterial resonators are found to be very flexible and reconfigurable, even in the case of large substrate conductivity losses, whereas their contribution to the system’s total efficiency is decisive.

Research and development (R&D) projects are often pursued through a project portfolio (PP). R&D PPs involve many stakeholders, and without proactive management, their interactions may lead to conflict risks. These conflict risks change dynamically with different stages of the PP life cycle, increasing the challenge of PP risk management. Existing conflict risk research mainly focuses on source identification but lacks risk assessment work. To better manage the stakeholder conflict risks (SCRs) of R&D PPs, this study employs the dynamic Bayesian network (DBN) to construct its dynamic assessment model.

This study constructs a DBN model to assess the SCRs in R&D PP. First, an indicator system of SCRs is constructed from the life cycle perspective. Then, the risk relationships within each R&D PPs life cycle stage are identified via interpretative structural modeling (ISM). The prior and conditional probabilities of risks are obtained by expert judgment and Monte Carlo simulation (MCS). Finally, crucial SCRs at each stage are identified utilizing propagation analysis, and the corresponding risk responses are proposed.

The results of the study identify the crucial risks at each stage. Also, for the crucial risks, this study suggests appropriate risk response strategies to help managers better perform risk response activities.

This study dynamically assesses the stakeholder conflict risks in R&D PPs from a life-cycle perspective, extending the stakeholder risk management research. Meanwhile, the crucial risks are identified at each stage accordingly, providing managerial insights for R&D PPs.

Due to the unknown location, size and timing of disasters, the rapid response required by humanitarian operations (HO) faces high uncertainty and limited time to raise funds. These harsh realities make HO challenging. This study aims to systematically capture the complex dynamic relationships between operations in humanitarian settings.

To achieve this goal, the authors undertook a systematic review of the extant academic literature linking HO to system dynamics (SD) simulation.

The research reviews 88 papers to propose a taxonomy of different topics covered in the literature; a framework represented through a causal loop diagram (CLD) to summarise the taxonomy, offering a view of operational activities and their linkages before and after disasters; and a research agenda for future research avenues.

As the authors provide an adequate representation of reality, the findings can help decision makers understand the problems faced in HO and make more effective decisions.

While other reviews on the application of SD in HO have focused on specific subjects, the current research presents a broad view, summarising the main results of a comprehensive CLD.