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The paper aims to focus on so‐called NoSQL databases in the context of cloud computing.

Architectures and basic features of these databases are studied, particularly their horizontal scalability and concurrency model, that is mostly weaker than ACID transactions in relational SQL‐like database systems.

Some characteristics like a data model and querying capabilities of NoSQL databases are discussed in more detail.

The paper shows vary different data models and query possibilities in a common terminology enabling comparison and categorization of NoSQL databases.

This work focuses on the interoperability of the blockchain from the viewpoint of its technological evolution in the wider context of supply chain systems. Interoperability concerns the most since it is among the most persevering problems in the process of blockchain adaptation. The study aims to trace and pinpoint all the different methods that affect the interoperability of blockchains, gather all the obtainable evidence and recognize gaps in between the applicable approaches mentioned across the contemporary academic literature.

An analysis is done of seven interoperability approaches based on their relevance, practical usefulness and adoption processes concerning the blockchain. Mainly, this work examines interoperability from several different perspectives. An interoperability modular decomposition via a layered model has been defined through the level of conceptual interoperability (LCIM) and level of information system interoperability (LISI), which represent the most popular metrics with regard to assessing the level of interoperability from a qualitative level.

Generally, the findings of this work are directed in two major aspects: Firstly, it expands the research around blockchain technology interoperability by providing crucial background information and pinpointing important connotations for both industrial and academic environments. It also defines and analyzes several different approaches toward the blockchain platform's interoperability. Secondly, it also identifies and proposes several scenarios that take advantage of multiple blockchain application approaches, highlights various issues and challenges to the evolution of interoperability standards and solutions and indicates the desired areas of further research.

An essential aspect of the originality of this paper is that, contrary to other work contributions, this work summarized the different interoperability approaches for blockchain in supply chain systems. Mainly, seven approaches were discussed for practitioners and researchers, and the open issues and future research direction were considered.

This paper aims to provide a roadmap for organizations to build big data projects and reap the most rewards out of their data. It covers all aspects of big data project implementation, from data collection to final project evaluation.

In each stage of the proposed roadmap, we introduce different sets of information and communications technology platforms and tools to assist IT professionals and managers in gaining a comprehensive understanding of the methods and technologies involved and in making the best use of them. The authors also complete the picture by illustrating the process through different real-world big data projects implementations.

By adopting the proposed roadmap, companies and organizations willing to establish an effective and rewarding big data solution can tackle all implementation challenges in each stage of their big data project setup: from strategy elaboration to final project evaluation. Their expectations of privacy and security are also baked, in advance, into the big data project design.

While technologies to build and run big data projects have started to mature and proliferate over the last couple of years, exploiting all potentials of big data is still at a relatively early stage. The value of this paper consists in providing a clear and systematic methodology to move businesses and organizations from an opinion-operated era where humans’ skills are a necessity to a data-driven and smart era where big data analytics plays a major role in discovering unexpected insights in the oceans of data routinely generated or collected.

This chapter reviews the underlying technologies of cryptoassets, including fundamental cryptographic primitives used in distributed ledger technologies and permissionless blockchain technologies and their consensus protocols such as proof-of-work and proof-of-stake. It discusses the pros and cons of existing approaches to improve blockchain scalability and considers the requirements for security and decentralization. The chapter also examines the following techniques: layer 1 tuning, layer 1 sharding, and layer 2 solutions. It concludes with an overview of technologies to swap cryptoassets off-chain, technical requirements for cross-chain transactions, and reviews cross-chain atomic swap implementation using hashed time lock contracts.

As the core technology of blockchain, various consensus mechanisms have emerged to satisfy the demands of different application scenarios. Since determining the security, scalability and other related performance of the blockchain, how to reach consensus efficiently of consensus mechanism is a critical issue in the blockchain.

The paper opted for a research overview on the blockchain consensus mechanism, including the consensus mechanisms' consensus progress, classification and comparison, which are complemented by documentary analysis.

This survey analyzes solutions for the improvement of consensus mechanisms in blockchain that have been proposed during the last few years and suggests future research directions around consensus mechanisms. First, the authors outline the consensus processes, the advantages and disadvantages of the mainstream consensus mechanisms. Additionally, the consensus mechanisms are subdivided into four types according to their characteristics. Then, the consensus mechanisms are compared and analyzed based on four evaluation criteria. Finally, the authors summarize the representative progress of consensus mechanisms and provide some suggestions on the design of consensus mechanisms to make further advances in this field.

This paper summarizes the future research development of the consensus mechanisms.

The purpose of this paper is to analyze the operational decisions of a manufacturer who produces multiple products and the government's selection of cap-and-trade and carbon tax regulations.

This paper explores the production decisions of a multi-product manufacturer under cap-and-trade and carbon tax regulations in a cap-dependent carbon trading price setting and compares carbon emission, the manufacturer's profits and social welfare under the two regulations. Game theory and extreme value theory are used to analyze our models.

First, the authors find that the optimal profit of the manufacturer (the optimal cap) increases and then decreases with the cap (the unit carbon emission of product). Second, if the environmental damage coefficient is moderate, the optimal cap of unit environmental damage coefficient is independent of the product carbon emission or other related product parameters. Ultimately, cap-and-trade regulation always generates more carbon emission than carbon tax regulation. And cap-and-trade regulation (carbon tax regulation) can generate more social welfare if the environmental damage coefficient is low (high), and the social welfare under the two regulations is equal to each other, or otherwise.

This paper contributes the prior literature by considering the inverse relationship of the allocated cap and the carbon trading price and discusses the social welfare under cap-and-trade and carbon tax regulations. Some important and new results are found, which can guide the government's implementation of the two regulations.

Cycle time reduction is important for order fulling process but often subject to resource constraints. This study considers an unrelated parallel machine environment where orders with random demands arrive dynamically. Processing speeds are controlled by resource allocation and subject to diminishing marginal returns. The objective is to minimize long-run expected order cycle time via order schedule and resource allocation decisions.

A stochastic optimization algorithm named CAP is proposed based on particle swarm optimization framework. It takes advantage of derived bound information to improve local search efficiency. Parameter impacts including demand variance, product type number, machine speed and resource coefficient are also analyzed through theoretic studies. The algorithm is evaluated and benchmarked with four well-known algorithms via extensive numerical experiments.

First, cycle time can be significantly improved when demand randomness is reduced via better forecasting. Second, achieving processing balance should be of top priority when considering resource allocation. Third, given marginal returns on resource consumption, it is advisable to allocate more resources to resource-sensitive machines.

A novel PSO-based optimization algorithm is proposed to jointly optimize order schedule and resource allocation decisions in a dynamic environment with random demands and stochastic arrivals. A general quadratic resource consumption function is adopted to better capture diminishing marginal returns.

This paper investigates to find whether it is possible to align the interests of a small and medium manufacturing enterprise (SMME) with its raw material supplier in a manufacturing supply chain (MSC) to achieve a sustainable solution. To this end, current study examines the coordination of an MSC under cap and trade consisting of a raw material supplier and a carbon-emitting SMME confronting a stochastic demand.

The model is developed under both the decentralized and centralized decision-making scenarios. Under the investigated model, the SMME decides on both production quantity and sustainability level simultaneously. To achieve coordination and align the interests of both MSC members toward sustainable economic development goals, a customized revenue-sharing contract is developed.

Although the centralized model is profitable for the MSC, it makes a loss for the SMME compared to the decentralized scenario. The revenue-sharing agreement is able to create coordination among the MSC members and optimize profitability and sustainability. The established revenue-sharing guarantees a Pareto-improving situation for both members. Applying the established contract not only reduces shortage occasions but also results in more sustainability levels, which in turn means movement toward attaining sustainable economic development goals.

Unlike previous studies, carbon emission is assumed as a nonlinear decreasing function of the sustainability level which is a more realistic case. In accordance with SMMEs business environments, the market demand is also assumed uncertain. In addition, instead of assuming an investment cost for sustainability, the authors assumed unit production/purchasing costs as functions of product sustainability level.

Within a framework of supply chain (SC) coordination, this paper analyzes a green SC consisting of a retailer and a manufacturer, under government incentives and legislations and the consumer environmental awareness. To mitigate carbon emissions and promote the sustainability of the SC, a customized carbon emission trading mechanism is developed.

A game-theoretical decision model formulated determines the optimal sustainability level and the optimal quota of carbon credit from the ceiling capacity set by the government. In order to coordinate the SC and optimize environmental decisions, a novel combination of consignment and zero wholesale price contracts is proposed.

Analytical and numerical analyses conducted highlight that the proposed contract generates a Pareto improvement for both channel members, boosts the profit of the green SC, enhances the sustainability level of the channel and contributes to a reduction in the requested carbon emission credit by the manufacturer.

With the proposed mechanism, governments can protect their industries and, more importantly, comply with European Union (EU) rules on annually reducing emission ceilings allocated to industries.

Different from previous studies on cap-and-trade strategies, the proposed mechanism enables companies to select lower emission quota/allowances than the maximum amount set by the government, and in return, companies can benefit from several incentive strategies of the government.

The purpose of this paper is to model a credit card market where the retailers may charge differential prices depending on the instrument of payment used by the consumer. According to the research agenda proposed by Rochet and Wright (2010), the authors find conditions for the existence of differential prices equilibrium and analyze the effects of that price differentiation on the consumer’s welfare.

This is done when the consumer has also the store credit as an alternative of payment. The equilibrium prices are computed assuming a Hotelling competition among retailers in both scenarios, when the cost of the store credit provided by the retailer is greater than that provided by the credit card and vice versa.

From this, the authors prove that the average price under the price differentiation is lower than the single price under the no-surcharge rule; nevertheless, the retailer’s margins remain the same in both situations. Furthermore, some cross-subsidies are expunged when price differentiation is allowed. The authors also conclude that the consumers’ welfare is greater when the no-surcharge rule is abolished. Finally, if the retailers face menu costs whenever they differentiate prices, the authors provide sufficient conditions for differential prices remain as equilibrium.

This is an important input for discussions among regulators and players of the credit card market.

From the analysis the authors can conclude that price differentiation, according to the instrument of payment, is a welfare improving policy. The authors explicitly determine the average price in that setting and the differentiated prices even in presence of costs that arise from price differentiation. The obtained theoretical results can be used as an input for econometric modeling purposes.