This paper introduces a novel method aimed at enhancing onlinetooffline (O2O) services recommendations by utilizing twolayer knowledge networks. The primary objective of this method is to assist consumers in efficiently navigating the myriad of options available when choosing O2O services. Using co-occurrence relationships, we construct a two-layer knowledge network system, comprising a service knowledge network based on service usage information as the first layer and a consumer knowledge network, built on co-used behaviors as the second layer. The former is established upon service use data, while the latter is founded on co-used behaviors among consumers. The features and information of these two knowledge networks can complement each other to produce precise and effective recommendations. Empirical findings gained from our experiments demonstrate that: (1) the proposed recommendation method outperforms widely-used and state-of-the-art recommendation methods; (2) both the service knowledge network and consumer knowledge network play an equally significant role in O2O service recommendations; (3) the location of O2O services is an essential factor in consumers' choices for services. Notably, this research also identifies the optimal parameter settings for the proposed recommendation method.

This paper develops a game model of a closed-loop supply chain consisting of one manufacturer, one remanufacturer and one retailer and investigates the long-term collection strategies of the manufacturer who needs to cooperate with the remanufacturer to develop the remanufacturing technology. The game model is developed from a fully dynamic perspective on the remanufacturing technology development and analyzed using the system dynamics method. We identify the trade-off in the choice of collection strategies: the early entry in the remanufacturing industry versus the complete control in the later stage. The simulation results show that when the entry barrier to the remanufacturing industry is low, the manufacturer can develop the remanufacturing technology in a short time and the direct reverse channel outperforms the indirect reverse channel; when the entry barrier is high, the manufacturer can achieve more profits under the indirect reverse channel by acquiring the remanufacturing technology directly from the remanufacturer. Moreover, the indirect reverse channel is more likely to be superior for low-barrier remanufacturing industry when the cost advantage is high as the early entry in the remanufacturing industry becomes more important than the complete control in the later stage.

As an important sector of national economy, the industrial sector accounts for 33.4% of gross domestic product while consuming 70% of energy and causing serious air pollution in China. It is meaningful to measure the productivity of industrial sector in China with air pollution consideration. The range-adjusted measure of the nonradial data envelopment analysis, as with natural disposability and managerial disposability, is adopted in order to measure the productivity of provincial industrial sector in China during 2011–2014. The results explain that the unified efficiency under managerial disposability is lower than the unified efficiency under natural disposability and the unified efficiency under natural and managerial disposability, which means that management improvement and technology innovation should be obtained more attention from the government. As modernization of economic restructuring, there is not a trend of unified efficiency under natural disposability. Eastern China has highest unified efficiency under managerial disposability, whereas unified efficiency under natural and managerial disposability are improving in eastern China and western China in period of 2013–2014. The results also describe that more than 20 provinces and nearly half of provinces are suitable for the industrial pollution control investment and research and development investment, respectively. On the basis of the results of the truncated regression model, we can identify the influencing factors of unified efficiency. According to above results, suggestions are proposed in order to improve the productivity.

The majority of countries attempting to switch from conventional energy sources to renewable energy sources have decided to make significant investments in these projects. Considering renewable energy is an industry with a high level of investment expenses, assessing investment risks is critical to making efficient investment strategies. Howbeit, since risk assessment is dependent on expert opinions, uncertainty in the judgment of the consultants should be avoided. In this study, a novel hybrid failure mode and effect analysis approach is proposed to assess the investment risks of renewable energy projects. Results indicated that wind energy is the most appropriate alternative considering technical, marketability, environmental, economic, social aspects. Moreover, the sensitivity analysis is carried out and the robustness and validity of results from the proposed approach are examined. Finally, six different scenarios are considered and the results are interpreted accordingly. The findings of this study will be valuable to authorities, investors, and enterprises involved in the renewable energy projects and evaluating their investment.

Risk assessment and selection of project portfolios are carried out under uncertainty, since this process uses historical data that can be adjusted in the future. The problem is whether the decision is still favorable and the level of risk is still acceptable to the investor. Assessing the quality of alternatives provides additional information about robustness to any changes in the parameters of the problem. The paper describes the concept of accuracy function. Using this concept, portfolios are evaluated to determine which portfolio is more robust with a possible increase in the level of risk. When the risk is reduced, the accuracy function indicates the optimality threshold when the selected portfolio can become Pareto optimal. This helps the investor to better assess the market situation and make more rational investment decisions. Based on the global risk assessment from the World Economic Forum report the case study describes the use of the accuracy function in assessing investment portfolios of projects participating in the Belt and Road initiative. The results show improvement paths to make economic arias more investment friendly.

The diversified strategy can reduce the systematic risk efficiently, but may fail to account for emergent and default risk that many decision-makers usually face at large-scale level. Modern data-driven methodologies allow optimizing both systematic and non-systematic risks in a unified framework. In this article, we demonstrate an approach to analyze and compare partial-diversified portfolios of Credit Default Swap. We classify and investigate different metrics of credit risks and integrate them with limited diversification and other performance objectives. We test the developed approach in a study of hundreds of business contract investments over the recent financial crisis. The results indicate that the decisions using limited diversification are more robust in terms of allocation structure and out-of-sample downside risks reduction. Therefore, the partial-diversified optimization models provide alternatives to support a variety of problems involving unknown risks.

This paper examines how preferential credit based on retailers’ credit line impacts on capital-constraint retailer’s operational decisions. We consider a condition of loan competition when banks and manufacturers offer preferential credit to capital-constraint retailers in the newsvendor model. Different credit lines and discounted rates of preferential credit mainly involve in retailers’ exogenous collateral and risk preference of banks and manufacturers in our model. We investigate impacts of bank financing, trade credit, and portfolio credit (financing from both bank credit and trade credit with different ratios) on retailer’s inventory decision with different cases that the retailer’s financing amounts exceed credit line or not. We derive the equilibrium wholesale price, expected sale price, and order quantity when retailers face with different conditions of collaterals and institutes’ risk preferences facing with market risk. A debt-financed retailer favours items with trade credit compared to bank financing, especially in conditions when its sourcing demand is great and when it finances from high-risk preference institutes. Retailer prefers to using the loan with high trade credit ratio when he opts portfolio credit conditions.

We use hotelling model to analyse store brands as a strategy for B&M (brick-and-mortar) retailers to combat showrooming. We investigate how national-brand product mismatch and store-brand awareness affect supply chain's performance. We reach four major conclusions. First, store-brand strategy may be an effective means for B&M stores to mitigate showrooming. However, it's better to introduce premium store brands. Second, the B&M store's profit grows - and the online store's profit declines - as national-brand product mismatch increases in breadth. When many consumers feel the national-brand product does not match their needs, a product positioning strategy for the store brand can help B&M retailers improve profit margins. Third, as national-brand product mismatch increases in depth, the B&M store's profit rises and online store's profit falls. If national-brand products lack many features that consumers need, a product differentiation strategy can be implemented to use store brands to fill in the gaps left by national brands. Finally, the growth of store-brand awareness will not necessarily benefit the B&M store. The impact of store-brand awareness on the B&M store's profit depends on the hassle cost factort, and a brand promotion strategy will reduce the loss of B&M retailer's profit.

Assuring future performance of systems-of-systems through advanced-technology investments is a perpetual challenge of industry and agencies. Among the complicating factors are technology innovation, escalating scales, and diversity of software and hardware applications, increasing availability and scrutiny of big data, and evolving business, environmental, and legal contexts. These factors are engaging system owner/operators to continually reprioritize these investments, even as transparent principles for investment are needed for appropriate oversight and auditing. In this paper, a branch of resilience analysis offers to address multiple layers of uncertainty that arise from technology plans around future disruptions to large-scale systems-of-systems. The paper presents a methodology to quantify and manage the disruptive influence of individual systems perspectives to the prioritization of technology investments across the system-of-systems. The methodology is demonstrated through a case study on an information technology investment portfolio of the US Department of Commerce, USA. The experience suggests how fiscal limitations, combining with several other factors, has the largest disruption to the prioritization of investments. The results furthermore describe how investments perform relative to one another and characterize where the system-of-systems might be resilient to the perspectives of constituent systems.

This study examines the joint impact of the vertical cross-shareholdings and external financing, including trade credit and bank loans, on the order strategy of a capital-constrained retailer. We set the target retailer and his supplier, which are connected with vertical cross-shareholdings, in the extended Cournot and Stackelberg game. The capital-constrained retailer could raise external financing when he has exhausted his own cash. Besides, the retailer may be faced with the random shock result from the other business. We use optimal response function to model how the capital-constrained retailer determines his order quantity under cross-shareholdings in response to different market conditions (such as his own cash level and other competitor's order strategy). We find that, the retailer orders more under cross-shareholdings if the retailer is well-funded with his own cash or external financing, resulting in a win-win situation for the supplier and retailer. However, if the retailer has run out of all his cash and credit, the cross-shareholdings have no effect on the retailer's order strategy. Thus, it helps the capital-constrained retailer to acquire competitive advantage that he could be well-funded with external financing under cross-shareholdings.