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This study attempts to examine whether it is beneficial to introduce the buy online and return to store (BORS) strategy in a competitive market. We consider two competing dual-channel retailers, and investigate conditions under which it is optimal for one or both of the retailers to offer the BORS strategy. We first assume that a partial refund is offered for online returns and then consider the important case of a full refund. We show that whether both retailers adopt this strategy significantly depends on the return rate and cross-selling profit. Specifically, if the return rate is sufficiently low (high), at least one retailer (both retailers) will adopt this strategy when cross-selling profit is relatively high. Nonetheless, both retailers will fall into the prisoner's dilemma under certain conditions. Interestingly, the return rate and proportion of consumers with a high hassle cost associated with BORS returns significantly influence the equilibrium channel strategy and the existence of the prisoner's dilemma. We further find that, when both retailers implement the BORS strategy, they both benefit from offering a full refund return policy when the number of online-type consumers is large enough and the unit cross-selling profit is relatively small, but should provide a partial refund otherwise. When only one retailer adopts the BORS strategy, a partial refund return policy is preferable.

The product return rate (RR) is an important metric for retailers; even small RR changes can significantly impact retailers’ profit. Companies and researchers typically favor and employ one of three methods to calculate the RR: based on the number of returned items, these items’ revenue, or their profit contribution. Interviews with 24 managers and industry experts reveal that two methods, item-based and revenue-based, are often used. However, little is known about how much the interpretation of RRs depends on the calculation method. In this article, the authors rely on extensive datasets to investigate these potential differences empirically. Analyzing more than 8 million transactions at sixteen different retailers, the authors find that RRs calculated via the three methods differ on average by 24.3%. The size of these differences makes cross-sectional comparisons of RRs calculated via different methods difficult. In contrast, the authors find that the developments of the RRs over time are similar, which allows for a meaningful time-series comparison of RR developments, regardless of the method. Finally, this research shows that all three calculation methods result in RRs that are equally insightful (leading) indicators of relevant retailer performance metrics.

On the Ground • The three most well-recognized sustainability pillars are environmental, social, and economic. • Ranch economic sustainability hinges on asset value dynamics and ranch profitability. • Ranch economic sustainability metrics include multiyear average positive accrual adjusted net income, rate of return on assets (valued at market value)

Given overall lack of gender diversity in the venture capital and entrepreneurship industry shown in Calder-Wang and Gompers (2017) we ask: What promotes greater gender diversity in hiring? Does diversity lead to better firm performance and higher investment returns? In this paper, using a unique dataset of the gender of venture capital partners’ children, we find strong evidence that when partners have more daughters, the propensity to hire female partners increases. Moreover, our instrumental variable results suggest that increased gender diversity improves deal and fund performance. Lastly, the effects are primarily driven by the gender of senior partners’ children.

Financing is a necessary economic activity of the new energy automobile enterprises, and it has an important function to push the enterprise to expand reproduction and promote the development speed of the enterprise. At the same time, there are many kinds of financing modes, such as internal financing, external debt financing and equity financing. If the financing mode is matched with the enterprise status, the financing activity is easier to succeed and the risk is also smaller. Otherwise, improper financing mode will not only affect the profit of enterprises, but also affect the survival of enterprises. We suppose that, after financing, the business manager of the enterprise can make a choice to invest either hydrogen-fueled vehicle project or lithium-ion battery vehicle project, in this case, we made an equilibrium analysis on the choice of investing which one new energy vehicle project and corresponding financing mode, according to the incomplete information dynamic game model, it is concluded that the equilibrium point (perfect Bayesian equilibrium refinement) of financing is most likely to appear in the state of equity financing; when the rate of return on assets of investment projects is within a certain range, both the financing enterprise and the investor can obtain the bigger profit. In addition, the risk value of the project also is calculated by using VaR model.

E-commerce has witnessed a steady growth with advances in digital technologies. However, one of the challenges faced by online retail is its inability to provide customers with the opportunity to “touch-and-feel” a product before purchasing, thereby resulting in a higher rate of product returns. To address this, online retailers, nowadays, are adopting various omnichannel configurations. Using a stylized model, we study three such omnichannel configurations: selling the product online, establishing a showroom while selling the product online (‘Experience-in-Store-and-Buy-Online (ESBO)’), and selling the product through both a brick-and-mortar (B&M) store and the online channel while allowing in-store product returns (‘Buy-Online-and-Return-In-Store (BORS)’). Based on product attributes such as product standardization and valuation we recommend optimal omnichannel strategies. Our results show that depending on whether a premium product is highly personalized or standardized, opening an additional showroom or a B&M store becomes optimal for the retailer. In contrast, for a low-valued, highly personalized product, the retailer prefers opening an exclusive showroom. Otherwise, for a low-valued, standardized product, the retailer opens an additional B&M store or continues to operate only online based on the product return rate and valuation. If the unit cost of transporting the returned products from customers is low, the retailer prefers to sell the product online only. Moreover, if the hassle cost of online purchase is too high, the strategy of in-store return becomes uneconomic. We also analyze the impact of customers’ exchanging returned items at the B&M store and their product fitness heterogeneity on the retailer’s optimal omnichannel strategy.

Public–private partnership (PPP) schemes show strong capability in delivering infrastructure projects. One challenge in designing PPP contracts is optimising the length of the concession period and level of the minimum revenue guarantee (MRG) to satisfy both public and private parties’ interests. Existing research excludes interaction between the concession period and MRG, but a method that can determine their values simultaneously is needed. This study fills the research gap by proposing a synthetic measure to determine the values of the concession period and MRG. An imperfect information bargaining model is created to find the equilibrium return rate on investment. To achieve the equilibrium of the bargaining game, the required length of the concession period and level of the MRG are calculated based on Monte Carlo simulation and real option analysis. Project QJ is created as a numerical example to verify the applicability of the proposed method. The outcome shows the proposed determination process identifies the optimal length of the concession period and level of the MRG. The length of the concession period is inversely proportional to the level of the MRG and this correlation is influenced by the probability of achieving the equilibrium return rate on investment. When this probability equals 70%, an MRG is not required once the concession period exceeds 24 years. The results also show the concession period decision range is sensitive to change in the concession price.

With the continuous improvement of the global securities market, the market competition is unprecedented fierce. In the aspect of investment decision support system, there is an urgent need to continuously absorb new information processing technologies and improve the scientific and standardization of decision-making, so as to achieve the goal of improving investment decision-making efficiency and stabilizing investment returns. Firstly, this paper introduces the defect that the database, model base and knowledge base are designed and implemented independently in the traditional decision support system. Then, constructing a unified and efficient data processing platform for Internet of Things based on DMFS technology, which realizes the integration of database and model, and innovatively establishes a data mining model facing market big data, dynamically analyzes and proposes investment decisions. Finally, the operating income data of a listed company in recent ten years are selected for simulation, which verifies the efficiency of the model system in processing dynamic data and the stability of investment income.

Vacant taxi drivers' passenger seeking process in a road network generates additional vehicle miles traveled, adding congestion and pollution into the road network and the environment. This paper aims to employ a Markov Decision Process (MDP) to model idle e-hailing drivers' optimal sequential decisions in passenger-seeking. Transportation network companies (TNC) or e-hailing (e.g., Didi, Uber) drivers exhibit different behaviors from traditional taxi drivers because e-hailing drivers do not need to actually search for passengers. Instead, they reposition themselves so that the matching platform can match a passenger. Accordingly, we incorporate e-hailing drivers' new features into our MDP model. The reward function used in the MDP model is uncovered by leveraging an inverse reinforcement learning technique. We then use 44,160 Didi drivers' 3-day trajectories to train the model. To validate the effectiveness of the model, a Monte Carlo simulation is conducted to simulate the performance of drivers under the guidance of the optimal policy, which is then compared with the performance of drivers following one baseline heuristic, namely, the local hotspot strategy. The results show that our model is able to achieve a 17.5% improvement over the local hotspot strategy in terms of the rate of return. The proposed MDP model captures the supply-demand ratio considering the fact that the number of drivers in this study is sufficiently large and thus the number of unmatched orders is assumed to be negligible. To better incorporate the competition among multiple drivers into the model, we have also devised and calibrated a dynamic adjustment strategy of the order matching probability., 23 pages, 16 figures, published in Transportation Research Part C 111 (2020) 91-113

Due to the accelerated expansion of technology and improved living standards, the use of electronic products is increasing exponentially. Unfortunately, the improper disposal of used electronic products, such as cell phones, has resulted in rapid degradation of the environment and is, therefore, posing a great threat to human health. Meanwhile, proper recycling is also likely to generate high profits; thus, recycling of electronic products is a necessity of the time. However, the profitability of recycling and remanufacturing depends upon the return rate, which is very low in the cell phones industry. In this paper, we first identify the root causes of low return rate and, then, develop a novel Radio Frequency Identification (RFID) based return channel to increase the recycling rate. A dual-recovery-channel hybrid manufacturing-remanufacturing production model is proposed, which procure used products of different quality from both the traditional market-driven recovery channel as well as the new RFID based channel. A mathematical model is developed considering the cost of implementation and the design of the proposed RFID based recovery channel. Recovery-channel selection is studied, and results show that a hybrid collection strategy with 85% share of channel-1 and 15% of channel-2 is the optimal one. Moreover, the collection from the proposed RFID based channel increases as the demand increases. For the proposed RFID based system, reader sensing power is found more significant compared to the cost of readers. A numerical example is given with three different cases and impacts of different input parameters are studied to draw important results. Managerial insights are given to assist the designer of the system in some critical decisions.

The basic goal of the company’s operation is to build its value. There are many measures, which makes value an ambiguous category. The value of the company is interested in its stakeholders, who can use the information about the value in various ways to achieve their goals, e.g. investing, managing the company, etc. The purpose of the article is to examine the relationship between the value of the company, its fundamental strength and rates of return. An important element of the study is to indicate the possibility of using the occurrence of the relationship between value and fundamental strength of the company’s stakeholders. The survey results show that fundamental strength influences the shaping of the enterprise value.

Establishment of green credit guarantee schemes (GCGSs) and returning a portion of the tax revenue originally generated from spillover effect of green energy supply to investors. It can reduce the risk of green finance and increase the rate of return of green energy projects, respectively. In addition, technical developments in the sphere of distributed ledger technologies provide the opportunity to increase the transparency in green finance and investments. This paper contributes to literature by proposing two applied frameworks, backed by theoretical models on green finance and investment based on projects size. The objective is to induce the private participation in green finance and investment.

Portfolio optimization problem is concerned with choosing an optimal portfolio strategy that can strike a balance between maximizing investment return and minimizing investment risk. In many cases, the return rate of risky asset is neither a random variable nor a fuzzy variable. Then, it can be described as an uncertain variable. But, the existing works on uncertain portfolio optimization problem fail to find an analytic solution of optimal portfolio strategy. In this paper, we define a new uncertain risk measure for the modeling of investment risk. Then, an uncertain portfolio optimization model is formulated. By introducing a new variable, we transform it into an equivalent bi-criteria optimization model. Then, we derive a method for the construction of the set of analytic Pareto optimal solutions. Finally, a numerical simulation is carried out to show the applicability of the proposed model and the convenience of finding the analytic solution.

This paper considers a multi-level closed loop supply chain (CLSC) including a supplier, a producer, a retailer, and a collector. Most of the works in the literature considered remanufactured products as-good-as newly produced items, while in the real world situations, some customers perceive remanufactured items as lower quality products than newly produced ones; so we assume that demands for manufactured and remanufactured items are different which leads to lost sales situations. To make the study more realistic, we assume the return rate of the second-hand items as a variable function which depends on the acceptance quality level of the returns. Also, producing and reproducing processes are assumed to be imperfect, so they can produce some defectives which are reworked in the same cycle. To address this problem, a mathematical model with single manufacturing/remanufacturing cycles is established and solved using two algorithms extended for the case of local (non-integrated) and global (integrated) optimization. The results of our analysis indicate that integration results in higher acceptance quality level of returns, higher replenishment cycle time for both manufactured and remanufactured items and less (higher) number of shipments to the retailer per manufacturing (remanufacturing) cycle. Furthermore, the results indicate that as the revenue of selling newly produced items (remanufactured items) increases, acceptance quality level of the returns decreases (increases) and the total number of shipments to the retailer per manufacturing (remanufacturing) cycle increases (decreases).

A manufacturer invests in product quality to encourage consumers who have purchased in the past to substitute their current product version with a new release. Since price deters the adoption of an upgraded quality product, consumers evaluate both the quality improvements and the new release price before deciding whether to return a good. The returns can be either voluntary (passive returns) or dependent on the firm’s controls (active returns), while the pricing strategies can be either fixed (constant intertemporal pricing) or varying over time (updated intertemporal pricing) depending on the quality improvements. By combining these two ingredients (return type and pricing policy) we formulate a two-period model in which a manufacturer invests in quality improvements and sets the product prices over time. Our results show that when consumers passively return old product versions, the manufacturer should always update its pricing strategies according to the quality improvements. However, when consumer returns are sensitive to quality improvements and price, the manufacturer can be indifferent between setting a constant or an updated pricing policy depending on the effect that quality has on returns. If the manufacturer can choose between a market in which consumer returns are passive or active, it decides according to how quality impacts the returns: When the consumers’ willingness to return according to the quality effect is negligible, the manufacturer prefers to work in a market with passive attitudes towards returns. While the choice of updating the price is always dominant from an economic point of view, it turns out to be suboptimal from an environmental perspective when the effects of quality and price on returns are balanced. When the price effect on returns also depends on the discount granted to consumers, then the discrepancy between economic and environmental returns is amplified.

The aim of this study is to investigate the economic prospects of producing electricity and hydrogen using wind energy under different scenarios. For this, the most essential criteria to investors including Levelized Cost of Wind-generated Electricity (LCOWE), Levelized Cost of Wind-based Hydrogen (LCOWH), payback period, and rate of return are examined. Technical and environmental impacts are factored into the LCOWE formulation to obtain comprehensive insight. Owing to the uncertain nature of future, five degradation rates concerned with wind turbine performance and five likely rates as to the future value of money are investigated under the scenarios of I) utilizing wind electricity to replace fuel oil electricity, II) to replace natural gas electricity and III) without considering environmental penalties. The results indicate that LCOWE would be in the range of 0.0325–0.0755 $/kWh, while the corresponding LCOWH being in the range of 1.375–1.59 $/kg. Moreover, payback period of the related LCOWE and LCOWH would be in the range of 2.55–9.48 yr during the lifetime of wind power plant and 3.91–8.41 yr during that of hydrogen production system, respectively. The corresponding rate of return pertinent to the above-mentioned ones would be respectively in the range of 14.15–23.54% and of 9.87–21.55%.

This study investigates the strategic effect of return policies in a dual-channel supply chain, in which a manufacturer can sell products directly to end customers and indirectly via an independent retailer. The manufacturer decides whether to implement a return policy in either the direct or indirect channel, or in both channels. When the return policy is provided, the cost of returned products has to be covered by the corresponding channel. We consider four possible strategies, including full refund in the direct channel only, full refund in the indirect channel only, full refund in both channels, and no refund in both channels. Given the equilibrium pricing strategies of firms, the preferences of firms over different strategies are determined by comparisons between the anticipated return rate of customers and their perceived value of the return policy. The manufacturer prefers the full-refund policy in both channels when the return rate of the customer is low. Otherwise, the dominant strategy for the manufacturer is the no-refund policy in both channels. The retailer benefits more from the full-refund policy in the indirect channel alone when the return rate is low; otherwise, the retailer prefers the full-refund policy in the direct channel only.

Increasing attention to sustainable development issues and competition between different supply chains are forcing the stakeholders to use different incentives to capture more market share. Collecting channels are one of the effective topics in the reverse competitive chains. Because of the importance of this issue, we consider two collecting reverse supply chains consist of a retailer and a manufacturer who compete together by proposing more rewards to the customers. One of these chains tries to facilitate the collecting process and obtain more market share by using the direct and traditional channels advantages. The other one uses only the traditional channel. Hence, the return rate of each channel not only depends on the self-reward but also is function of the cross-rewards suggested to the customer by the competitors in the other channels. The competitive environment in our model consists of internal and external competitions. Competition between two channels of one chain infers to internal competition, external competition that points out to competition among two supply chains. We apply three game theory structures to obtain the optimal channels rewards: Nash, Nash-Stackelberg-first supply chain, and Nash-Stackelberg-second supply chain. Finally, we comparing the results of decision variables and profit function of members under three structures through numerical analysis. Our numerical investigations show that e-channel because of less costly than traditional channel proposes more appropriate reward to customers, so this channel could obtain a more substantial share of the market. Moreover, the results reveal that highest return rate occurred under Nash scenario while Nash-Stackelberg-first supply chain and Nash-Stackelberg-second supply chain are the most economic scenarios for the first and the second supply chains, respectively.

Financial global crisis has devastating impacts to economies since early XX century and continues to impose increasing collateral damages for governments, enterprises, and society in general. Up to now, all efforts to obtain efficient methods to predict these events have been disappointing. However, the quest for a robust estimator of the degree of the market efficiency, or even, a crisis predictor, is still one of the most studied subjects in the field. We present here an original contribution that combines Information Theory with graph concepts, to study the return rate series of 32 global trade markets. Specifically, we propose a very simple quantifier that shows to be highly correlated with global financial instability periods, being also a good estimator of the market crisis risk and market resilience. We show that this estimator displays striking results when applied to countries that played central roles during the last major global market crisis. The simplicity and effectiveness of our quantifier allow us to anticipate its use in a wide range of disciplines., Comment: 5 pages, 3 figures

When investing in financial markets it is crucial to determine a trading signal that can provide the investor with the best entry and exit points of the financial market, however this is a difficult task and has become a very popular research topic in the financial area. This paper presents an expert system in the financial area that combines Principal Component Analysis (PCA), Discrete Wavelet Transform (DWT), Extreme Gradient Boosting (XGBoost) and a Multi-Objective Optimization Genetic Algorithm (MOO-GA) in order to achieve high returns with a low level of risk. PCA is used to reduce the dimensionality of the financial input data set and the DWT is used to perform a noise reduction to every feature. The resultant data set is then fed to an XGBoost binary classifier that has its hyperparameters optimized by a MOO-GA. The importance of the PCA is analyzed and the results obtained show that it greatly improves the performance of the system. In order to improve even more the results obtained in the system using PCA, the PCA and the DWT are then applied together in one system and the results obtained show that this system is capable of outperforming the Buy and Hold (B&H) strategy in three of the five analyzed financial markets, achieving an average rate of return of 49.26% in the portfolio, while the B&H achieves on average 32.41%.

Public utilities and regulators are implementing various forms of regulatory mechanisms that decouple revenues from commodity sales to remove a disincentive or create an incentive for utilities to invest in and encourage consumers to conserve electricity, natural gas and water. A major question is whether such regulatory mechanisms affect investor-perceived risk, the cost of common equity and the utility rates of such commodities. This is an important question as regulators in the US are and have been considering the impact of decoupling on investment risk and therefore the cost of common equity in rate proceedings. This matter is also important for regulators globally as they consider decoupling as a policy initiative in setting rates and rate of return. Currently, decoupling is primarily a US ratemaking policy for energy and water utilities as are price caps in Europe. Empirical testing, based on the available data in the US, consistently demonstrates that decoupling has no statistically measurable impact on risk and the cost of common equity. Therefore, at this juncture, policy is moving ahead, at least in the US, without empirical evidence on whether it does have impact on risk and return.

The study examined the role of social influence process of subjective norm, image and voluntariness on perceived usefulness of social media (PUSM) in private university libraries. The quest to ascertain the impact of the social factor in a profit-motivated environment prompted the study. The descriptive research design alongside multistage sampling procedures was applied and the questionnaire method was used for data collection. One hundred and ninety (190) librarians, selected from 13 private university libraries provided the data, out of which 184 copies of the instrument were correctly filled and returned, representing 96.8 per cent return rate. Statistical tools like simple percentage, mean and standard deviation of the Special Package for the Social Sciences (SPSS) were employed to analyse the research questions. Results shown that image was the strongest determinant among the proposed social factors of PUSM, followed by subjective norm. While voluntariness was a weak predictor of PUSM, the overall PUSM of librarians in the private university domain in the studied region was very high. This implies that the social factor is significant predictor of technology adoption in the private university library environment. Accordingly, the study concluded that if the performance potentials of social media are consciously communicated and imbibed by librarians through adequate training, whether or not private universities operate in a mandatory environment, PUSM of librarians will remain positively high.

The value of an asset in a financial market is given in terms of another asset known as numeraire. The dynamics of the value is non-stationary and hence, to quantify the relationships between different assets, one requires convenient measures such as the means and covariances of the respective log returns. Here, we develop transformation equations for these means and covariances when one changes the numeraire. The results are verified by a thorough empirical analysis capturing the dynamics of numerous assets in a foreign exchange market. We show that the partial correlations between pairs of assets are invariant under the change of the numeraire. This observable quantifies the relationship between two assets, while the influence of the rest is removed. As such the partial correlations uncover intriguing observations which may not be easily noticed in the ordinary correlation analysis.

This paper provides an early assessment of the effects of the negative interest rate policy (NIRP) introduced by the Bank of Japan in January 2016. We propose a simple analytic model, which shows under appropriate conditions that lowering the negative interest rate on reserves further into a more negative range by the central bank leads to lower interest rates on bonds, reduces the required rate of return from stocks, and depreciates the value of the domestic currency. We also provide the most relevant empirical information available at present on the effectiveness of the NIRP and suggest that the available evidence thus far is consistent with the results implied by our analytic model.

The closed-loop network design of a hybrid manufacturing and recovering system plays an important role on improving both the production efficiency and environmental quality, especially under a multi-product multi-stage scenario. Besides, with the growing awareness of environmental concerns by legislators, decision makers have been forced not only to enhance utilization of the returned products or components but also to control carbon emission of the whole hybrid system. To optimize the closed-loop logistics superstructure design, a multi-objective model integrating the manufacturing and recovering process in a multi-product multi-stage environment is proposed in this research. Both operations cost and environmental influence are regarded as two objective categories. In addition, the carbon emission regulation is considered in the model by integrating and characterizing the energy input and greenhouse output throughout the hybrid system. Finally, a numerical case originated from an electronic assembly plant is presented under different scenarios to illustrate the effectiveness of the proposed approach. A sensitivity analysis is given to compare the impacts of carbon emission and return rate on each sub-objective of the logistics and environmental issues.

We develop a model of investment with financial constraints and use it to investigate the relation between investment and Tobin’s  .A firm is financed partly by insiders, who control its assets, and partly by outside investors. When their wealth is scarce, insiders earn a rate of return higher than the market rate of return, i.e., they receive a quasi-rent on invested capital. This rent is priced into the value of the firm, so Tobin’s  is driven by two forces: changes in the value of invested capital, and changes in the value of the insiders’ future rents per unit of capital. This weakens the correlation between  and investment, relative to the frictionless benchmark. We present a calibrated version of the model, which, due to this effect, generates realistic correlations between investment,  ,a nd cashflow.

Most developed economies invest in public goods such as national defense, education, infrastructure, and the environment. Discount rates used to evaluate such projects should reflect the rate of return on the current mix of investment opportunities. Rates derived from the productivity of private capital neglect returns beyond the market boundary. The present paper derives discount rates using an augmented measure of national income inclusive of non-market goods. In an empirical application focusing on air pollution and climate damages in the United States economy, the paper reports that the difference between augmented and market discount rates averages 0.3 percentage points from 1999 to 2014.

In the age of “Internet+”, many Internet service platforms (ISPs) in China have been widely introduced to the closed-loop supply chain (CLSC). To further study the role of the Internet service platform, this paper considers a CLSC composed of a manufacturer, a retailer and an Internet service platform who invests in research and development (R&D), advertising and Big Data marketing, and develops the goodwill dynamic model based on the differential game theory. The construction of a goodwill dynamic model has two purposes, namely, to increase sales and the return rate. The optimal decisions for 3 players under two different cooperative scenarios are obtained, namely, the retailer payment scenario (scenario D) and the manufacturer cost-sharing scenario (scenario S). The supply chain members gain more profit or achieve a higher level of goodwill for products under certain conditions, i.e., a high residual value from remanufacturing, a high sharing rate of residual value from the retailer's recycled products, and a low recycling cost. Interestingly, the wholesale price increases with the residual value of recycled products when goodwill effectiveness is low, while the price declines when goodwill effectiveness is high. After comparing two cooperative scenarios, the result shows that an Internet service platform will invest more in Big Data marketing under the manufacturer cost-sharing scenario, and cooperation between the manufacturer and the Internet service platform can help improve the goodwill of enterprises or products. Moreover, the manufacturer cost-sharing scenario is payoff-Pareto-improving in most cases through the coordination of a cost-sharing rate, and the effectiveness of Big Data marketing exerts a positive effect on goodwill and the development of the industry. In addition, the retailer has “free rider” tendencies in the manufacturer cost-sharing scenario. The results encourage more enterprises to enhance the value of goodwill through cooperation with Internet service platforms because Internet service platforms conveniently utilize Big Data marketing to increase the sales of products and the collecting rate of used products, which in turn helps environmental sustainability.

This paper studies the welfare properties of mutual funds in a Diamond–Dybvig economy with two sources of aggregate risk: (i) shocks to long-term investment returns; and (ii) shocks to aggregate liquidity demand. Mutual funds are inefficient when the long-term investment is risky. Mutual funds improve upon autarky by introducing a wedge between the market and technological rates of return. However, the wedge distorts the decisions of consumers not facing liquidity shocks, and the resulting equilibrium is inefficient. If only aggregate liquidity demand is subject to shocks, mutual funds can implement the social optimum (even when liquidity demand is not directly observable) by means of a price-contingent dividend policy.

In recent years, the manufacturer has received pressures from both consumers and government regarding the environmental awareness. The government has forced the manufacturer through regulations to take care their end-of-life products for reducing the environmental damage. Meanwhile, an increase in the consumers’ environmental awareness leads to a competitive advantage to the manufacturer who has environmentally friendly products and processes. This study considers the green efforts from the manufacturer and retailer to deal with the government regulations and the consumers' environmental awareness. The purpose of this study is to investigate the behavior of supply-chain members in the green supply chain management under the reward-penalty mechanism from the government. Under the game-theoretical settings, the manufacturer seeks to maximize his/her profit by considering the optimal behaviors of the retailer and/or independent third party. The equilibrium solutions of the proposed models are obtained in the closed-form format. We found that the return rate and green effort can be improved by the reward-penalty mechanism. When considering decentralized channels under the reward-penalty mechanism, the manufacturer collects used products is deemed more effective when he/she cannot offer a higher transfer price.

The major challenge for filling the financing gaps of green energy is lower rate of return of green projects comparing to fossil fuels. Electricity tariffs are often regulated by governments; It has to be kept in low price to serve for every households as a necessary goods. Sources of revenue from green energy comes only from user charges. Hence it is not so much attractive for private investors. The paper is proposing a model for utilization of the tax revenue spillover of green energy supply by returning the portion of it to green energy projects in order to increase their rate of return. In addition, the paper is proposing a social community based funding scheme for smaller scale green projects (e.g. solar and wind). The paper theoretically and empirically shows that utilizing spillover effect in form of tax return for funding green energy projects will increase the rate of return and make them feasible and interesting for the private investors.

Considering the circumstances of supply disruption and government subsidy, optimal recovery and production strategies for the closed-loop supply chain are investigated. It is assumed that the quality of returned products is exponentially distributed, buyback cost, return rate and remanufacturing cost are function of quality level of returned items, upon this, an optimal operation and subsidies policy model is built. A numerical example is used to verify the validity and credibility of the model by adopting Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The results show that the manufacturer could arrange properly the ratio of remanufacturing and manufacturing lots and the minimum quality of returned products to achieve system optimal outcome; besides, the enterprises should make effective decisions in the face of supply disruption; meanwhile, the government can adopt an appropriate subsidy policy to encourage the recovery of returned items. The research is helpful for the operation of the enterprises under supply disruption and the design of the government’s reasonable subsidy mechanism.

The process of “transitioning” to adulthood for youth with disabilities has long been recognized to be an important but understudied public policy concern. This paper evaluates the labor market effects of Virginia’s school-to-work vocational evaluation program, PERT. Using a unique panel data set containing more than a decade of labor market and service information, we provide the first-ever assessment of the long-term employment impacts of a transitioning program for youth with disabilities. Overall, the estimated effects are substantial: PERT has an estimated median quarterly rate of return of nearly 30%.

Shallow geothermal resource has been considered as a new and promising form for clean heating in some areas in China, such as Xiong’an New Area. In this paper, a real option model is established to explore the optimal investment timing and investment scale of shallow geothermal resources. According to numerical results, we found that in the reference scenario the critical value of marginal revenue is 4.30 yuan / m2, and the optimal investment scale is 1.28 million square meters. Simultaneously, the investors are advised to invest after 1.05 years and they will get the unit investment return of 39.34 yuan / m2.

Distributed energy storage system (DESS) is an effective way in adapting to increasing penetration of distributed generations (DGs) and will play an important role in the operation of active distribution networks (ADNs). However, the high capital cost and limited life cycles restrict the further development of DESS. In this paper, an operational strategy based method for economic evaluation of DESS is proposed. Firstly, rate of return is set as the economic evaluation index. Then, the economic operation model is established. By applying convex relaxation, the original nonlinear programming (NLP) model is converted into an effectively solved second-order cone programming (SOCP) model. Finally, the effectiveness of the economic evaluation method is verified on the modified IEEE 33-node test feeder.

Solar power has achieved great development in the last decade, and it should continue to play a central role in the face of climate change and sustainable development challenges. This paper builds a real options model that provides a microeconomic analytical framework with the Least Squares Monte Carlo (LSM) method to assess the investment choices of a typical solar panel producer in China facing trade and domestic supply- and demand-side policy uncertainties. It builds a baseline scenario and three policy scenarios with decreasing anti-dumping and countervailing charges, constant feed-in tariff (FIT) level and reduced investment cost. A typical producer will have to make an investment decision on building a new production line in five years based on a decision impact analysis within 20 years. The result shows an immediate investment decision for all scenarios. The producer will have higher return from investment in building a solar power plant with a constant FIT. Export is the optimal choice in other scenarios where investment return is lower. After sensitivity analysis, the paper concludes and can be used as a toolkit for solar panel producers and a reference for policy makers to evaluate the impact of policy uncertainties.

Financial literacy has become an interesting topic recently, given the global trends and the need for individuals to take responsibility for their personal finances and, in particular, for their retirement planning. In this paper we investigate financial literacy of adults in Bosnia and Herzegovina. Our survey questionnaire is based on the OECD/INFE questionnaire, with some adjustments to national specificities. The method of research is the online survey. Looking at the results, our research overall shows rather low level of financial literacy of Bosnian citizens. In particular, low level of understanding and skills related to basic concepts, such as compound rate of return and diversification, indicate that there are many aspects of financial knowledge that could be improved. Financial knowledge and behavior of our sample is better positioned than the average in other countries. Due to worse attitude, the overall level of financial literacy is lower than the average in other countries. In addition, the analysis showed that attitudes towards the money are worse than the attitudes of citizens in other countries. Looking at at different levels of income, we notices no statistically significant difference in behavior and attitudes within different groups. The low level of financial literacy emphasizes the importance of introducing financial education at an earlier age, since the lack of financial education can cause people to start saving later in life, thus limiting required retirement goals. As a result, it is unlikely to achieve an optimal balance between current consumption during work and future consumption as individuals retire. In addition, the lack of information on the distribution of risk and return on various investments can lead to the misallocation of their pension portfolios.

In this study, we used regression discontinuity and difference-in-differences methods to verify whether price effects exist in the China Securities Index (CSI 300). Results suggest that the stocks included in this index had an extra abnormal rate of return of approximately 15% compared with the control group. Furthermore, the excluded stocks had a negative abnormal return of approximately 10% before the exclusion announcement, which reversed after the announcement. However, the price effects of the excluded stocks were not significant. Overall, the results indicate that price effects in the CSI 300 are asymmetrical.

The bullwhip effect, or how uncertainty associated with the end customers' demand propagates through the entire supply chain, has been widely discussed in supply-chain management literature. Although there is a well-established research stream on the causes and mitigating factors for the bullwhip effect in forward supply chains, few studies have investigated how this phenomenon manifests itself in closed-loop supply chains. We argue that this phenomenon can affect the supply chain's environmental performance by increasing emissions, waste and consumption of natural resources. Aiming at filling this theoretical gap, this article compares the causes and mitigating factors of the bullwhip effect in forward supply chains and closed-loop supply chains. To this end, we employ a systematic literature review that combines bibliometric and content analyses. The studies examined in our review indicate that the causes of the bullwhip effect in closed-loop supply chains are similar to those in forward supply chains. However, most of the studies have not considered that the quality of returned products are different from the quality of their new counterparts' products, adding another variable into the complexity of a given supply chain which, in turn, could lead to higher variability, thereby causing the bullwhip effect. Regarding mitigation, we found that the primary mitigating factor is related to increasing the product return rate. Moreover, we suggest that closing a supply chain can reduce the bullwhip effect, which could lead to positive impacts in the environmental performance of supply chains.

This paper studies price and promised delivery lead time (PDL) competition between two e-tailers in the context of e-commerce. Product returns are considered, which are affected by late and early delivery inaccuracies, i.e., the delay and early arrival of random actual delivery time relative to PDL. The goal is to examine whether the Nash Equilibrium exists in the competition, and to explore the impact of product returns on equilibrium solutions. We consider two cases where the sensitivities of the return rate to late delivery inaccuracy and early delivery inaccuracy are symmetric/asymmetric. The results suggest that (1) firms with lower basic return rates or lower return rate sensitivities, always quote higher prices and shorter PDLs; (2) it is not always profitable for firms whose competitors’ return parameters increase.

The total return to higher education is the rate of return based on earnings plus non-monetary private and social benefits beyond earnings that captures higher education’s contribution to development. A theory of endogenous development is a new scholarly contribution where firm and household production with education externalities and the endogeneity of new ideas leads to an optimal rate of development. This rate is higher than in an economy without these externalities. Since measures of private non-market and social benefit externalities are positive, externalities contribute to higher per capita development. The total return is estimated to be considerably higher than the opportunity cost of funds and the return on physical capital, the first major evidence of serious underinvestment in higher education in the US for optimal development. Policy-relevant treatment effects and policy options with implications for optimal development and for improving the worsening condition of the dissatisfied middle class are considered.

We solve a version of the analytical Real Business Cycle (RBC) model with a predetermined rate of return on household saving. The solution differs from that of the benchmark RBC model along two dimensions: (i) Policy functions depend on the variance of the technology shock. (ii) There is a suboptimal pattern of excess saving. We discuss the economic intuition underlying these properties. We also demonstrate that unconditional welfare can be higher in the suboptimal model with predetermined interest rates, providing a clear illustration of the pitfall with unconditional welfare comparisons.

Global warming has raised a global concern on climate change. One of the effective measures to combat this global warming is to limit/conserve the energy uses globally. It is a common scientific consensus that around 30% in average of the total energy uses in modern countries comes from the energy uses from the existing building blocks.This article gives a systematic manner to develop strategies of how to effectively greening the existing buildings [GEB]. The findings concluded that using the above GEB strategies can achieve a total of energy savings in a range of 40%–60%. This high energy savings will contribute to carbon intensity reduction in the range of 20%–30%.A Green Audit Award [GAA] is postulated to help to identify the green potential/deficiencies of the existing buildings with the aim to wrap up a green improvement plan so that the existing buildings can become green within the constraints of the existing building under the assessment. A pilot test in terms of a case study confirmed that the GAA assessment scheme coupled with the GEB strategies is feasible and cost effective to turn the existing building green.Government support and promotion is crucial for the sustainability of these GEB strategies and a survey from previous study of cost coming from the illness and the pay to avoid this illness points out that the proposed funds to be subsidized for both greening and maintenance of existing buildings with age ≥ 40 years is justifiable for GEB promotion.With the advance of GEB strategies focusing on the rate of return for energy savings, GAA assessment will be an effectual tool to attain the objective of this paper to transform the existing buildings to green with ease and cost effectively, and with the effort of each existing building in adopting the above GEB strategies, an enormous effect will be anticipated in combating the global warming in return. Keywords: Greening existing buildings strategies, Green Audit Award, LEED-EB, Building energy index

This paper uses administrative tax data to estimate top wealth in the United States. We assemble new data that links people to their sources of capital income and develop new methods to estimate the degree of return heterogeneity within asset classes. Disaggregated fixed income data reveal that rich individuals earn much more of their interest income in higher-yielding forms, and have much greater exposure to credit risk. Consequently, in recent years, the interest rate on fixed income at the top is approximately three times higher than the average. Using firm-level characteristics to value firms, we find that twenty percent of total pass-through business wealth accrues to those with losses. We combine this new data on fixed income and pass-through business returns with refined estimates of C-corporation equity, housing, and pension wealth to deliver new capitalized wealth estimates. Our approach---which builds on Saez and Zucman (2016) and Bricker, Henriques, and Hansen (2018)---reduces bias because wealth and rates of return are correlated. From 1989 to 2016, the top 1%, 0.1%, and 0.01% wealth shares increased by 7.6, 5.1, and 3.0 percentage points, respectively, to 31.5%, 15.0%, and 7.0%. While these changes are less dramatic than some prior estimates, wealth is very concentrated: the top 1% holds nearly as much wealth as either the bottom 90% or the "P90-99" class. We discuss implications for income inequality measures, capital tax policy, and savings behavior. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

The accounting for defined-benefit (DB) pension expense in U.S. GAAP involves offsetting pension costs against an expected (rather than actual) return on pension assets. Pensions commentators argue that this expensing model tilts pension portfolios towards riskier assets – as sponsoring firms can benefit from assuming higher expected rates of return on riskier assets (which reduce pension expense and boost reported income), without bearing the cost of higher volatility in reported income. We examine a recent regulatory change in U.S. GAAP, which mandates the relocation of the expected return on pension assets from “above the line” of to “below the line” of operating income. Consistent with this change reducing the financial reporting incentives for risk-taking, we predict and find that a sample of U.S. firms subject to this mandate reduces risk-taking in pension assets following the change, relative to a control sample of Canadian firms not subject to the change. In cross-sectional tests, we find that the reduction in risk-taking is more pronounced in (1) firms where the financial reporting incentives for risk-taking were stronger in the pre-period, and in (2) firms where the regulatory change particularly reduced those benefits. Our findings imply that managers are willing to undertake real actions (i.e., invest in riskier assets) to report favorable operating income, and that these incentives are incremental to the incentives to report favorable net income. They also provide evidence that financial reporting incentives serve as a driver of pension asset allocation decisions.

We define a sentiment indicator that exploits two contrasting views of return predictability, and study its properties. The indicator, which is based on option prices, valuation ratios and interest rates, was unusually high during the late 1990s, reflecting dividend growth expectations that in our view were unreasonably optimistic. We interpret it as helping to reveal irrational beliefs about fundamentals. We show that our measure is a leading indicator of detrended volume, and of various other measures associated with financial fragility. We also make two methodological contributions. First, we derive a new valuation-ratio decomposition that is related to the Campbell and Shiller (1988) loglinearization, but which resembles the traditional Gordon growth model more closely and has certain other advantages for our purposes. Second, we introduce a volatility index that provides a lower bound on the market's expected log return.

We study the optimal taxation of risk-free and excess capital income with heterogeneous rates of return, alongside an optimal nonlinear earnings tax. Households can hold three assets: one risk-free, one risky but diversifiable, and one a private investment with idiosyncratic risk whose expected return differs among households. Contrary to expectations, the optimal tax on excess returns to risky assets is ineffective for redistribution, because its effects are annulled by a Domar-Musgrave effect. It assumes only an insurance role, and is positive. The optimal tax on risk-free returns does fulfill a redistributive role, insofar the risk-free returns reveal information about the investors' types beyond what is revealed by the earnings tax base. The optimal nonlinear earnings tax takes the standard Mirrleesian form amended to take account of the stochasticity of capital income tax revenue.

I propose a fast and parsimonious way to estimate the implied rate of return on common equity of single stocks and indexes, resulting from the combination of two easily computable ratios.

Foreign holdings of domestic debt instruments in Nigeria have been increasing. Using data over 2007M1-2019M1, we show that, on average, global factors (global interest rates, oil prices) seem to carry more weight than domestic factors (treasury bills rate and domestic risk) in foreign portfolio invetsors’ decisions in Nigeria. Specifically, we show that foreign participation is, in the long run, positively correlated with oil prices and profitable rates of return on local-currency instruments, but negatively correlated with exchange rate depreciation pressures. In the short run, oil prices, opportunity cost of funds and perception of Nigeria-specific risks also play a role. These results highlight the volatile short-term nature of such flows and call for a package of policy reforms to attract longer term direct investments.

Based on a detailed model of the German tax-benefit system, this paper simulates private and fiscal returns to education for college graduates and college dropouts. Completing a five-year college degree is found to be associated with an internal rate of return (IRR) of 14.2% for gross earnings, 7.4% for disposable income, and 6.6% for the net fiscal contribution. Individuals who drop out of college after two years, and subsequently complete a three-year period of vocational training, are found to have negative IRRs: -0.5% for gross earnings and -5.9% for both disposable income and the net fiscal contribution. In a series of counterfactual experiments, we explore how these returns react to changes in gross earnings, expenditure per student, and the level of income tax payments.