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The emergence of decentralized finance (DeFi) allows arbitrageurs to obtain risk-free income from price gaps of cryptocurrency tokens in many global markets. Several automated arbitrage techniques have been invented to profit from single or multiple platforms, including Centralized and Decentralized Exchange (CEX and DEX), triangular, and DEX-Fait. This paper proposes the arbitrage strategy of cross-cryptocurrency exchanges (ASCEX), a novel automated arbitrage strategy for CEX-DEX platforms, to maximize profit and loss (PNL) using a token route searching algorithm. Based on feature comparison, ASCEX outperforms the existing trading strategies available. Our actual trade experiment shows that ASCEX can generate up to 0.95% monthly risk-free profit compared to 0.34% trading on DEX alone.

This study explores the use of rough-set methods for marketing decision support systems in the retail business. A tutorial presentation of Rough Set Data Analysis (RSDA) in the context of knowledge discovery from time series databases is given. We show how an RSDA model can be used to develop a marketing decision support system which can capture the complex relationships between marketing factors, such as advertising and promotion, and the total impact on sales levels in order to find influential advertising strategies. This information is used by the business manager to make faster and better strategy decisions for the business to survive in the rapidly changing and competitive environments. The data set used for RSDA application example contains weekly investments in different media categories: TV, radio, cinema, morning press, evening press, popular press, special interest press, and outdoor posters; for seven makes of cars in the Swedish market.

Over the last few decades, Corporate Social Responsibility (CSR) disclosures become a powerful driver of overall stakeholders’ development while the relationship between CSR and its performance has provided conflicting results due to the most used intersecting circle representation of assessment of CSR. This study fills an important gap by analyzing the framework of CSR assessment practices on identification of five criteria and 17 indicators encompassing the strategies of accountability, transparency and compliance of CSR. To achieve the goal of CSR, the strategies have been defined in connection with different literatures and quaternary survey for criteria selection, where the criteria are expressed in a fuzzy horizon. This multi-criteria decision-making (MCDM) model has been solved using a fuzzy analytical networking process and balanced scorecard (BSC) method to develop selection strategy and criteria for implementation of CSR. The paper’s outcomes help administrators of corporate sectors, particularly in developing countries, to follow sustainable actions as CSR providers effectively and to gain a significant reasonable advantage. The findings exposed the CSR assessment structure and interrelationships among BSC perspectives/criteria and indicators on which managers are needed to emphasize to get optimum CSR performance. In this study, the most important strategy and criteria to perform optimum CSR level are as follows: “accountability of CSR project” is the best strategy; “Project team work, incentives, Environmental resources, Communication for motivation, Reporting initiative of stockholders, CSR project with stockholder capital, Strategic governance, Mission sustainability, political role, Human resources”, respectively, are criteria.

As technologies become more open and easily applied, they will be used extensively as they promise competitive advantage through more efficient and effective management of supply chain processes. At the same time, however, they represent a potential trap for organizations thinking that they will supplant the need for effective strategy formulation, appropriate management of resources, or effective change and knowledge management systems. The management of the supply chain will be facilitated by more sophisticated technologies, but the organizations that are likely to benefit most will still be those able to choose, implement, and manage technologies appropriate to the requirements of their trading partner networks. A set of propositions and a framework explaining the nature of these relationships is presented.