Search results

The purpose of this chapter is to ask and answer the question of what would happen if Genetically Modified Organism (GMO) plant materials were banned. We report on two studies – one with United States only ban and one with a global ban. We used a global computable general equilibrium (CGE) model, Global Trade Analysis Project (GTAP), for the analysis. This model has been used in hundreds of published papers on trade, energy, land use, and environmental issues. Our use of the model was to estimate the crop yield benefits for the major GMO crops, and then to convert this to a loss if the GMO traits were banned. We then shocked the GTAP model with the yield losses and estimate economic, land use, and greenhouse gas (GHG) emission impacts. We found that losing the GM technology would cause commodity and food prices to increase and also bring about a significant increase in GHG emissions. The increase in emissions is caused by the need to convert forest and pasture to compensate for the lost production. Another interesting conclusion of the global ban study is that economic well-being for the United States, the world’s largest GMO user, actually increases with a ban. Many regions that ban or use little GMO varieties like the European Union, India, China, and Japan all see economic well-being decrease. These counterintuitive results are driven mainly by trade patterns. Therefore GMO technology helps agriculture reduce its carbon footprint. Without this technology, agricultural land-use GHG emissions increase as do food prices. Some groups would like to see GMOs banned and also see GHG emissions fall. You cannot have it both ways.

The goal of this work is to determine the nature and potential of the impact of the development of strategic alliances on the achievement of the key Sustainable Development Goals (SDGs) of the states.

The study is involved with the use of the universalisation method, statistical analysis method, trend-based method, simulation-based game approach and correlation analysis method. The values of estimated indicators have been determined through the use of these global rankings, identifying their level between 2018 and 2021 in the countries which rank among the leading countries in the field of development of strategic alliances (Malta, Canada, Sweden and Israel).

It has been established that sustainable economic development of strategic alliances scarcely ever has a positive impact on the achievement of the SDGs of the states. It has been established that such interaction is possible if these business entities observe certain terms ensuring the necessary development parameters of components of sustainable development. Conditions of the achievement of effect from the impact of business associations of these goals have been identified empirically.

It has been proven that such business associations as strategic alliances due to the range of their activity and the potential associated with it can act as economic institutions that complement the functions of the state towards the achievement of sustainable development milestones.

The academic novelty of this research is that it substantiates the potential to secure the impact of strategic alliances on the achievement of certain SDGs associated with the observance of certain organisational and economic conditions of strategic management.

This chapter examines the airline performance effect arising from collaboration between airlines and high speed railway (HSR). The analysis presents scenario simulations using a bi-level model, which takes into account the effect of competition among airlines and HSR. Using real data, we examine the Japanese domestic market and the Japan-based international market: the markets consist of Tokyo Metropolitan Area, Osaka Metropolitan Area, Seoul/Korea, Frankfurt/Germany, Paris/France, London/United Kingdom, and Los Angeles/United States. Analysis of the domestic market assumes airlines and HSR compete against each other, and analysis of the international market assumes airlines only compete with each other. Initially, we conduct performance analysis using a simulation that mimics the current relationship between airlines and HSR. Then we present three scenarios for different combinations of collaboration between airline and HSR based on airline alliances. The results from this exercise are then used to examine the impact of the collaboration on the profits of airlines and HSR, passenger’s utility, and the network design of airlines. Last, we show the potential benefit to airlines – profitability, market share, and demand growth – from the airline-HSR collaboration. Our model shows that in Japan: (1) Airlines can improve their profitability in international operations by the collaboration with HSR when airlines set their hubs so they can connect to HSR; (2) The airline which has a lower unit operating cost than rivals and sets its hubs to connect to HSR can improve its joint profit with HSR through collaboration; (3) Airlines that don’t operate domestic flights and don’t set their hubs to connect to HSR encourage increased fare competition by coordinating with HSR, but their profit decreases. Whether these results are generalizable to other regions should be the subject of future study.

Economic models based on simple rules can result in complex and unpredictable deterministic dynamics with emergent features similar to those of actual economies. I present several such models ranging from cellular automaton and register machines to quantum computation. The additional benefit of such models is displayed by extending them to model political entanglement to determine the impact of allowing majority redistributive voting. In general, the insights obtained from simulating the computations of simple rules can serve as an additional way to study economics, complementing equilibrium, literary, experimental, and empirical approaches. I culminate by presenting a minimal model of economic complexity that generates complex economic growth and diminishing poverty without any parameter fitting, and which, when modified to incorporate political entanglement, generates volatile stagnation and greater poverty.

Introduction: The frequency and complexity of cyber assaults have grown in recent years. Consequently, organisations have increased their expenditures in more robust infrastructure to protect themselves from these cyber assaults. These organisations’ assets, data, and reputations are at risk due to rapidly increasing cybercrimes. However, complete protection from these many and ever-changing threats is very challenging as a result. To deal with them, companies are taking steps to reduce risks and limit company losses in their occurrence.

Purpose: Progressively, the insurance sector organisations are including digital protection as a component of the board’s general danger technique. Protection enterprises, then again, depend on accurately expecting risks, while a significant number of them depend on normalised approaches. Because of the exceptional attributes of the digital assaults, transporters now and again depend on subjective strategies dependent on master decisions. There is an unmistakeable absence of observational information on digital protection, specifically subjective examinations planning to comprehend and depict necessities, impediments, and cycles applicable for digital protection.

Methodology: There are various unanswered inquiries and worries about the oversight and legitimate and administrative assessment of network safety weaknesses in the protection business. In the wake-up of looking over all these worries and issues, steps to alleviate them are laid out after an extensive literature survey and secondary data sources. In this study, the authors have principally viewed the executive parts of the associations as the danger. While considering network protection, their insight of needs was taken as one among a few dangerous treatment systems, just as the necessities of the organisations’ protection in assessing the danger level of likely customers.

Findings: This section analyses past research in network safety and information security in the protection market. The danger of the executives’ strategies, the numerical models, and the forecasts of digital occassions are illustrated in this section. Lastly, the future headings are likewise expressed momentarily.

Practical implications: This review might be valuable for additional examination and logical discussion, yet additionally for down-to-earth applications. Moreover, it could be gainful to organisations as a supportive instrument for better agreement on what digital protection is and how to get ready to take on network safety and information security procedures in the association.

Significance: These associations’ resources, information, and notoriety are in danger because of quickly expanding cybercrimes. Cybercriminals are utilising more refined approaches to start digital assaults. Digital protection was anticipated to affect security conduct before any proof was gathered. Progressively, organisations are including digital protection as a feature of their general danger to the executive system. Because of the exceptional attributes of the digital assaults, transporters as often as possible depend on subjective methods dependent on master decisions. Thus, this space of network safety and information security is vital uniquely in the protection market.

Rapid innovation and developments in personal electronic technology have encouraged users to change users' devices more frequently than ever, which has resulted in creating a massive increase in the amount of electronic waste. The study focuses on identifying the barriers to closed-loop supply chain (CLSC) in the electronic industry.

A framework for analyzing the relationships among CLSC adoption barriers is designed. The authors adopted the decision-making trial and evaluation laboratory (DEMATEL) technique to determine the critical barriers of electronic CLSC from the opinion of experts in the field.

The outcome from the analysis suggests that cost barriers, financial barrier, process barriers and supplier-side barriers are the main causal factors that prevent the adoption and implementation of e-waste CLSC. The causal relationship indicates that financial barrier is the most influential factor, while phycological barrier is the most flexible barrier to the adoption of e-waste CLSC.

This study is restricted to CLSC adoption barriers in the electronic industry by evaluating 36 sub-barriers grouped into 8 main dimensions related to different members of the supply chain.

Closed-loop adoption barriers have been proposed to understand the crucial barriers to implementation of CLSC in the electronic industry. The cause-and-effect relationship indicates the critical factors to be improved to increase adoption of e-waste CLSC, helping managers and regulatory bodies to mitigate the problem areas.

This study contributes to the literature on CLSC by adopting a multi-criteria decision-making (MCDM) technique which captures the critical barriers of e-waste CLSC adoption in Indian scenario.

The authors investigate whether an index-based weather insurance (WII) product can complement or replace existing traditional crop yield insurance for mitigating farmers' financial risks, with an application to blueberry growers in British Columbia (BC).

A hybrid model combining expected utility (EU) and prospect values is developed to analyse farmers' demand for WII.

While weather data are used to investigate supply elements, a hybrid model combining EU theory and prospect theory (PT) is developed to analyse farmers' demand for WII. On the supply side, a quality index is constructed and the relationship between the quality index and key weather parameters is quantified using a partial least squares structural model. The authors then model weather parameters via time-series analysis and statistical distributions to provide reasonable estimates for calculating actuarially sound insurance premiums for a rainfall indexed, insurance product. This model indicates that decreases in the proportion of a blueberry grower's total revenue and revenue volatility will decrease the possibility that they participate in WII. At the same time, an increase in the value loss aversion coefficient and WII's basis risk further leads to less demand for WII. In short, a grower may decide not to participate in WII at an actuarially fair premium due to the combined effects of the above factors. Overall, while the supply analysis enables us to demonstrate that WII can potentially help in mitigating farmers' financial risks, it turns out that, on the demand side, blueberry growers are unwilling to pay for such a product without large government subsidies.

The authors argue that the demand for insurance may be affected by the level and the volatility of a berry grower's total revenue. Hence, the authors propose a hybrid expression that assumes a farmer seeks to maximize the total utility function to capture the rational and intuitive parts of a farmer's decision-making process. The EU represents rationality and the prospect value represents the intuitive component. Meanwhile, the authors investigate the possibility of using key weather parameters to construct a berry quality index – one that could be applied to other agricultural areas for studying the relationship between weather conditions and product quality.

This study quantifies empirically the induced impact of income distribution and consumption expenditure on the structures of agriculture production of Nigerian economy.

The study calibrates an extended input-output model on a social accounting matrix (SAM) for Nigeria for the year 2010. Moreover, the study conducts a dispersion analysis to identify the key agriculture sectors/subsectors both in exogenous and endogenous setup.

This study presents an empirical analysis of propagation in the structure of production particularly in the structure of agriculture sector. It combines the aggregate and the disaggregated levels of analysis and identifies the key sectors/subsectors both in the exogenous and endogenous setup. The comparison of both findings confirms that the composition of income distribution and consumption expenditure significantly influences the composition and the aggregated and disaggregated order of structure of agriculture production.

Knowledge of interindustry connections is vital in policy implications since the policy makers prefer strongly interconnected sectors to the sectors with poor industry linkages. These connections are estimated as forward and backward linkages, which provide indices to set the criteria for key sectors identification. This study presents an empirical analysis of propagation in the structure of production particularly in the structure of agriculture sector. It combines the aggregate and the disaggregated levels of analysis and identifies the key sectors/subsectors both in the exogenous and endogenous setup.

The purpose of this paper is to examine price overreactions in the case of the following cryptocurrencies: bitcoin, litecoin, ripple and dash.

A number of parametric (t-test, ANOVA, regression analysis with dummy variables) and non-parametric (Mann–Whitney U-test) tests confirm the presence of price patterns after overreactions: the next day price changes in both directions are bigger than after “normal” days. A trading robot approach is then used to establish whether these statistical anomalies can be exploited to generate profits.

The results suggest that a strategy based on counter-movements after overreactions is not profitable, whilst one based on inertia appears to be profitable but produces outcomes not statistically different from the random ones. Therefore, the overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the efficient market hypothesis (EMH).

The overreactions detected in the cryptocurrency market do not give rise to exploitable profit opportunities (possibly because of transaction costs) and cannot be seen as evidence against the EMH.

The purpose of this paper is to provide some new empirical evidence on the weekend effect (one of the best known anomalies in financial markets) in Ukrainian futures prices. The analysis uses various statistical techniques.

The analysis uses various statistical techniques (average analysis, Student’s t-test, dummy variables, and fractional integration) to test for the presence of this anomaly, and then a trading simulation approach to establish whether it can be exploited to make extra profits.

The statistical evidence points to abnormal positive returns on Fridays, and a trading strategy based on this anomaly is shown to generate annual profits of up to 25 per cent. The implication is that the Ukrainian stock market is inefficient.

This paper provides some new empirical evidence on the weekend effect (one of the best known anomalies in financial markets) in Ukrainian futures prices. The analysis uses various statistical techniques (average analysis, Student’s t-test, dummy variables, and fractional integration) to test for the presence of this anomaly, and then a trading simulation approach to establish whether it can be exploited to make extra profits. The statistical evidence points to abnormal positive returns on Fridays, and a trading strategy based on this anomaly is shown to generate annual profits of up to 25 per cent. The implication is that the Ukrainian stock market is inefficient.