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This study aims to focus on the optimal green R&D of a capital-constrained supply chain under different channel power structures as well as the impact of capital constraint, financing cost, channel power structure and cost-reducing efficiency on green R&D and supply chain profitability.

A two-echelon supply chain is considered. The upstream firm engages in green R&D but has capital constraints that can be overcome by external financing. Green R&D is beneficial to reduce production costs and increase consumer demand. Based on whether or not the upstream firm is capital constrained and dominates the supply chain, four models are developed.

Capital constraints significantly lower green R&D and supply chain profitability. Transferring leadership from the upstream to the downstream firms leads to higher green R&D levels and downstream firm profitability, whereas the upstream firm's profitability is increased (decreased) if green R&D investment efficiency is high (low) enough. Greater financing costs reduce green R&D and downstream firm profitability; however, the upstream firm's profitability under the model in which it functions as the follower increases if the initial capital is sufficient. More importantly, empirical analysis based on practice data is used to verify the theoretical results reported above.

This study reveals how upstream firms in supply chains decide green R&D decisions in situations with capital constraints, providing managers and governments with an understanding of the impact of capital constraint, channel power structure, financing cost and cost-reducing efficiency on supply chain green R&D and profitability.

The major contributions are the exploration of supply chain green R&D by taking into consideration channel power structures and cost-reducing efficiency and the validation of theoretical results using practice data.

Considering the existing evidence on the impact of female board members on the default risks of an organization, the purpose of this study is to investigate the effect of board gender diversity, alongside institutional characteristics and macroeconomic factors, on the financing costs of microfinance institutions (MFIs).

This study collected unbalanced panel data of 1,190 unique MFIs between 2010 and 2018 from the World Bank. The collected data, which covers a total of 95 developing and emerging countries, was thereafter analyzed using the pooled ordinary least squares and random effects model. To overcome endogeneity and omitted variable bias (e.g. time-invariant variables), the authors have also used the generalized method of moments and fixed effects model, respectively. Different proxies of board gender diversity and sub-sample analysis by regions were further undertaken to examine the robustness of the obtained results.

The findings of this study revealed that board gender diversity has a statistically significant negative effect on the financing costs of MFIs. This suggests that a gender-diverse board can generate cheaper funding for MFIs by minimizing their default risks through effective monitoring and strategic management. Furthermore, the negative impact of board gender diversity on financing costs appears to be more pronounced when there is a minimum of two female board members in the boardroom of MFIs. The results of this study remain consistent and valid regardless of alternate model specifications (e.g. sub-sample analysis, use of alternative proxies of board gender diversity and application of different estimators) and endogeneity issues. Ultimately, the findings in this study reiterate the importance of promoting and implementing gender diversity in the boardroom to minimize the financing costs of MFIs.

This study investigated the relationship between board gender diversity and financing costs of MFIs by using relatively recent and global data. The minimum number of female board members required to significantly reduce the financing costs of MFIs was also identified.

Although supply chain finance (SCF) aims to optimize capital flows in the supply chain process, its effectiveness in improving cost performance remains controversial. From the perspective of efficiency motives, this study aims to explore how the combinations of SCF solutions and traditional financing instruments lead to supply chain cost reduction.

A mixed-method approach is used in this study. First, using the fuzzy-set qualitative comparative analysis (fsQCA), the authors analyze 405 survey data across four industries in China and identify the configurations of financing instruments for supply chain cost reduction. Second, to better understand the reasons behind each configuration, the authors conduct the content analysis on the interview data composed of 24 Chinese companies.

The authors find that the effectiveness of SCF solutions for supply chain cost reduction is related to the focal company's use of traditional financing instruments. Moreover, compared with guaranteed financing, companies that use credit financing are more likely to adopt SCF solutions to achieve supply chain cost reduction. Finally, the effectiveness of SCF solutions in reducing supply chain costs varies greatly across industries.

The study’s findings provide insights for policymakers and SCF practitioners in the aspects of simplifying the SCF application.

This study contributes to the current literature by addressing the theory–practice gap related to SCF. The study also provides new understandings of factors related to supply chain cost reduction, as well as factors that influence SCF adoption.

Planning for increased contractor profits should start at the time the contract is signed because low profits and lack of profitability are the primary causes of contractor failure. The purpose of this paper is to propose an integrated profit maximization model (IPMM) that aims for maximum expected profit by using time-cost tradeoff analysis, adjusted start times of activities, minimized financing cost and minimized extension of work schedule beyond the contract duration. This kind of integrated approach was never researched in the past.

IPMM is programmed into an automated system using MATLAB 2016a. It generates an optimal work schedule that leads to maximum profit by means of time-cost tradeoff analysis considering different activity acceleration/deceleration methods and adjusting the start/finish times of activities. While doing so, IPMM minimizes the contractor’s financing cost by considering combinations of different financing alternatives such as short-term loans, long-term loans and lines of credit. IPMM also considers the impact of extending the project duration on project profit.

IPMM is tested for different project durations, for the optimality of the solutions, differing activity start/finish times and project financing alternatives. In all cases, contractors can achieve maximum profit by using IPMM.

IPMM considers a deterministic project schedule, whereas stochastic time-cost tradeoff analysis can improve its performance. Resource allocation and resource leveling are not considered in IPMM, but can be incorporated into the model in future research. Finally, the long computational time is a challenge that needs to be overcome in future research.

IPMM is likely to increase profits and improve the chances of contractors to survive and grow compared to their competitors. The practical value of IPMM is that any contractor can and should use IPMM since all the data required to run IPMM is available to the contractor at the time the contract is signed. The contractor who provides information about network logic, schedule data, cost data, contractual terms, and available financing alternatives and their APRs can use an automated IPMM that adjusts activity start times and durations, minimizes financing cost, eliminates or minimizes time extensions, minimizes total cost and maximizes expected profit.

Unlike any prior study that looks into contractors’ profits by considering the impact of only one or two factors at a time, this study presents an IPMM that considers all major factors that affect profits, namely, time-cost tradeoff analysis, adjusted start times of activities, minimized financing cost and minimized extension of work schedule beyond the contract duration.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.

This study aims to investigate how opening high-speed railways affects the cost of debt financing based on China's background.

Using panel data on Chinese listed firms from 2008 to 2017, this study constructs a quasi-natural experiment and adopts a difference-in-difference model with multiple time periods to empirically examine the relation between the high-speed railway openings and debt financing cost.

Our results show that opening high-speed railways reduces the cost of debt financing, and this negative correlation is more significant in non-state firms, firms with weaker internal control, and firms that hire non-Big Four auditors. Besides, we explore the impact mechanisms and find that opening high-speed railways improves analyst attention, institutional investor participation, and information disclosure quality, which in turn lowers the cost of debt financing.

The results imply that the opening of high-speed railways helps to alleviate the information asymmetry and adverse selection between firms and creditors and ultimately reduces the cost of corporate debt financing.

This paper can inform firms and stakeholders about the impact of opening high-speed railways on debt financing cost: it improves the information environment, reduces the geographical location restrictions of debt financing, ensures the reasonable pricing of corporate debt, and thus promotes the healthy and sound development of the debt market.

This paper provides theoretical support and empirical evidence for the impact of infrastructure construction on the information environment of the debt market in China, which enriches the research on the “high-speed railway economy.” In addition, as an exogenous event, the opening of high-speed railways instantly shortens the time distance between firms and external stakeholders, which gives us a natural environment to conduct empirical research, thus providing a new perspective for financial research on firms' geographical location.

The purpose of the study is to investigate the financing channels and carbon emission abatement preferences of supply chain members, and further examine the optimal contract design of the retailer.

This paper develops a low-carbon supply chain composed of one retailer and one manufacturer, in which the retailer provides trade credit to the manufacturer. Considering the cap-and-trade regulation, the manufacturer with uncertain yield makes decision on whether to invest in emission abatement. There are bank loan and trade credit to finance production for the manufacturer and green credit to finance emission abatement investment. Meanwhile, the retailer may provide the manufacturer with three kinds of contracts to improve emission abatement efficiency, namely, revenue sharing, cost sharing or both sharing.

The results show that the retailer prefers to offer financing service at lower interest rate, but trade (and green) credit financing is always optimal for manufacturer and supply chain. The investment in emission abatement is value-added to all players. The sharing contracts offered by the retailer at lower sharing ratios can realize Pareto improvement of the system regardless of the financing scheme. However, comparing with the revenue or cost sharing contract, the existence of optimal sharing ratios makes the both sharing contract more favorable to the retailer.

The findings provide guidance for the emission-dependent manufacturer in financing and emission abatement decisions, as well as recommendations for the retailer to offer loan service and sharing contract.

This paper integrates green credit into bank loan or trade credit to analyze the financing decision of the manufacturer with uncertain yield and further considers the influence of three kinds of sharing contracts introduced by the retailer on improving operational performance.

The authors provide firm-level evidence that external financing affects international trade in a way different from internal financing.

The authors separate new entrants from incumbent exporters and investigate the roles of external and internal financing in export market participation and export quantity.

The authors find that external financing is of particular importance, as well as internal financing, in helping a firm become a new exporter. By contrast, external financing, unlike internal financing, is not significantly important for an incumbent exporter to stay in the international market. Regarding export quantity, a firm's internal financing is positively associated with more export quantity, whereas external financing is not.

The authors’ findings are consistent with the existence of significant fixed cost for entering the export market and external financing is particularly needed to cover such cost. Meanwhile, the financial need for maintaining the export status is much less and can be satisfied via internal financing.