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The purpose of this study is to assess the impact of the shadow economy on three sustainable development indicators while considering the moderating effect of the governance quality, and to highlight the non-linearity of the considered relationship.

A sample of 82 countries covering the period from 1996 to 2017. The dynamic first-differenced generalized method of moments (FD-GMM) panel threshold model is implemented to control for non-linearity.

The shadow economy hinders sustainable development in countries with low-governance quality, while the opposite result holds in countries with high-governance quality. The critical thresholds triggering the switch from one regime to another vary across the sustainable development indicators. Boosting growth requires enhancing the legal system and the economic dimension of governance, while promoting environmental quality requires the implementation and enforcement of specific environment-friendly regulations.

The study addresses non-linearity and the moderating effect of governance quality. The use of six governance indicators allows to gauge the ability of each governance dimension to curb the negative effects of the shadow economy. Considering the three objectives of sustainable development allows to identify specific policy recommendations for each of them.

This paper aims to propose a novel control scheme and offer a control parameter optimizer to achieve better automatic carrier landing. Carrier landing is a challenging work because of the severe sea conditions, high demand for accuracy and non-linearity and maneuvering coupling of the aircraft. Consequently, the automatic carrier landing system raises the need for a control scheme that combines high robustness, rapidity and accuracy. In addition, to exploit the capability of the proposed control scheme and alleviate the difficulty of manual parameter tuning, a control parameter optimizer is constructed.

A novel reference model is constructed by considering the desired state and the actual state as constrained generalized relative motion, which works as a virtual terminal spring-damper system. An improved particle swarm optimization algorithm with dynamic boundary adjustment and Pareto set analysis is introduced to optimize the control parameters.

The control parameter optimizer makes it efficient and effective to obtain well-tuned control parameters. Furthermore, the proposed control scheme with the optimized parameters can achieve safe carrier landings under various severe sea conditions.

The proposed control scheme shows stronger robustness, accuracy and rapidity than sliding-mode control and Proportion-integration-differentiation (PID). Also, the small number and efficiency of control parameters make this paper realize the first simultaneous optimization of all control parameters in the field of flight control.

Most emerging economies have made conscious efforts through policy initiatives to attract foreign direct investment (FDI). However, a significant obstacle to FDI inflow has been the prevalence of corruption in the host country. This study, therefore, aims to examine whether there is an optimum corruption value that results in threshold effects of corruption on FDI.

To achieve this objective, this study used Hansen’s (1999) panel threshold regression (PTR) model by using a panel data of 30 sub-Saharan African (SSA) countries from 2000 to 2021.

This study finds that the nexus between corruption and FDI has a single threshold effect, with a 5.37% optimum corruption threshold value. At this threshold value, corruption affects FDI negatively. Any corruption value that is below the threshold value also elicits a negative corruption–FDI relationship. Despite having a negative relationship when the corruption value is above the optimum corruption threshold, it is not statistically significant.

The implication of the results is that it is deleterious to use corrupt practices to draw FDI to SSA nations.

To the best of the authors’ knowledge, this study is one of the first in the corruption–FDI nexus literature to use Hansen’s PTR model to estimate an optimal corruption threshold. The authors recommend that policymakers in the selected SSA countries reconsider the use of corruption to attract FDI because there is an optimal corruption threshold that could impact FDI in the host country.

The study aims to investigate the presence of herding behavior in the stock market of UK with a special emphasis on news sentiment regarding the economy. The authors focus on the news sentiment because in the current digital era, investors take their decision making on the basis of current trends projected by news and media platforms.

For empirical modeling, the authors use machine learning models to investigate the presence of herding behavior in UK stock market for the period starting from 2006 to 2021. The authors use support vector regression, single layer neural network and multilayer neural network models to predict the herding behavior in the stock market of the UK. The authors estimate the herding coefficients using all the models and compare the findings with the linear regression model.

The results show a strong evidence of herding behavior in the stock market of the UK during different time regimes. Furthermore, when the authors incorporate the economic uncertainty news sentiment in the model, the results show a significant improvement. The results of support vector regression, single layer perceptron and multilayer perceptron model show the evidence of herding behavior in UK stock market during global financial crises of 2007–08 and COVID’19 period. In addition, the authors compare the findings with the linear regression which provides no evidence of herding behavior in all the regimes except COVID’19. The results also provide deep insights for both individual investors and policy makers to construct efficient portfolios and avoid market crashes, respectively.

In the existing literature of herding behavior, news sentiment regarding economic uncertainty has not been used before. However, in the present era this parameter is quite critical in context of market anomalies hence and needs to be investigated. In addition, the literature exhibits varying results about the existence of herding behavior when different methodologies are used. In this context, the use of machine learning models is quite rare in the herding literature. The machine learning models are quite robust and provide accurate results. Therefore, this research study uses three different models, i.e. single layer perceptron model, multilayer perceptron model and support vector regression model to investigate the herding behavior in the stock market of the UK. A comparative analysis is also presented among the results of all the models. The study sheds light on the importance of economic uncertainty news sentiment to predict the herding behavior.

Taking the dialogic organizational development perspective, this study aims to investigate the framing processes when engaging in dialogue for strategy implementation and how these enable the evolution of implementation opportunities.

Through a qualitative exploratory study conducted in a large multinational, the authors analyse the dialogue and interactions among 25 dyads when identifying opportunities to contribute to strategy implementation. The data analysis relies on a process-coding approach and linkography, a valuable protocol analysis for identifying recursive interaction schemas in conversations.

The authors identify four main framing processes – shaping, unveiling, scattering and shifting – and provide a framework of how these processes affect individuals’ mental models through increasing the tangibility of opportunities or elevating them to new value hierarchies.

From a theoretical perspective, this study contributes to the strategy implementation and organizational development literature, providing a micro-perspective of how dialogue allows early knowledge structures to emerge and shape the development of opportunities for strategy implementation.

From a managerial perspective, the authors offer insights to trigger action and change in individuals to contribute to strategy when moving from formulation to implementation.

Rather than focusing on the structural control view of strategy implementation and the role of the top management team, this study considers strategy implementation as a practice and what it takes for organizational actors who do not take part in strategy formulation to enact and shape opportunities for strategy implementation through constructive dialogue.

This study examines the non-linear impact of financial development on income inequality and analyses the mediators through which financial development affects income inequality.

The study uses a dynamic panel threshold method with an endogeneous threshold variable on a comprehensive sample of 85 countries over the period of 1996-2015.

The author finds that financial development activities increase income inequality in developed countries. However, financial development promotes income equality in developing countries. Further, the study finds that education and institutional quality are the channels through which financial development has non-linear impacts on income inequality.

The study explores relatively new method to examine the nonlinear impact of financial development and also considers new dataset for the main explanatory variable.

This study’s aim is to introduce a high-performance sorbent for the removal of both anionic (Congo red; CR) and cationic (methylene blue; MB) dyes from aqueous solutions.

Sodium silicate is adopted as a substrate for GO and AgNPs with positive charge are used as modifiers. The synthesized nanocomposite is characterized by FTIR, FESEM, EDS, BET and XRD techniques. Then, some of the most effective parameters on the removal of CR and MB dyes such as solution pH, sorbent dose, adsorption equilibrium time, primary dye concentration and salt effect are optimized using the spectrophotometry technique.

The authors successfully achieved notable maximum adsorption capacities (Qmax) of CR and MB, which were 41.15 and 37.04 mg g⁻¹, respectively. The required equilibrium times for maximum efficiency of the developed sorbent were 10 and 15 min for CR and MB dyes, respectively. Adsorption equilibrium data present a good correlation with Langmuir isotherm, with a correlation coefficient of R2 = 0.9924 for CR and R2 = 0.9904 for MB, and kinetic studies prove that the dye adsorption process follows pseudo second-order models (CR R2 = 0.9986 and MB R2 = 0.9967).

The results showed that the proposed mechanism for the function of the developed sorbent in dye adsorption was based on physical and multilayer adsorption for both dyes onto the active sites of non-homogeneous sorbent.

The as-prepared nano-adsorbent has a high ability to remove both cationic and anionic dyes; moreover, to the high efficiency of the adsorbent, it has been tried to make its synthesis steps as simple as possible using inexpensive and available materials.

Brief introduction on the importance and the need for plastic analysis methods were presented in the beginning section of this review. The plastic method for analysis was considered to be the more advanced method of analysis because of its ability to represent the true behaviour of the steel structures. Then in the following section, a literature analysis has been carried out on the previous investigations done on steel plates, steel beams and steel frames by other authors. The behaviour of them under different types of loading were presented and are under the investigation of innovative new analysis methods.

Structure member connections also have the potential for plastic failure. In this study, the authors have highlighted a few topics to be discussed. The three topics in this study are T-end plate connections to a square hollow section, semi-rigid connections and cold-formed steel storage racks with spine bracings using speed-lock connections. Connection is one of the important parts of a structure that ensures the integrity of the structure. Finally, in this technical paper, the authors introduce some topics related to seismic action. Application of the Theory of Plastic Mechanism Control in seismic design is studied in the beginning. At the end, its in-depth application for moment resisting frames-eccentrically braced frames dual systems is investigated.

When this study involves the design of a plastic structure, the design criteria must involve the ultimate load rather than the yield stress. As the steel behaves in the plastic range, it means the capacity of the steel has reached the ultimate load. Ultimate load design and load factor design are the methods in the range of plastic analysis. After the steel capacity has reached beyond the yield stress, it fulfills the requirement in this method. The plastic analysis method offers a consistent and logical approach to structural analysis. It provides an economical solution in terms of steel weight, as the sections designed using this method are smaller compared with elastic design methods.

The plastic method is the primary approach used in the analysis and design of statically indeterminate frame structures.

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

This study aims to revisit the empirical debate about the asymmetric relationship between oil prices, energy consumption, CO₂ emissions and economic growth in a panel of 184 countries from 1981 to 2020.

A relatively new research method, the PVAR system GMM, is applied.

The outcome of the PVAR system GMM model at the group level in the study suggests that oil prices exert a positive but statistically insignificant effect on economic growth. Energy consumption is inversely related to economic growth but statistically significant, and the correlation between CO₂ emissions and economic growth is negative but statistically insignificant. The Granger causality test indicates that oil prices, CO₂ emissions, oil rents, energy consumption and savings jointly Granger-cause economic growth. A unidirectional causality runs from energy consumption, savings and economic growth to oil prices. At countries’ income grouping levels, oil prices, oil rent, CO₂ emissions, energy consumption and savings jointly Granger-cause economic growth for the high-income and upper-middle-income countries groups only, while those variables did not jointly Granger-cause economic growth for the low-income and lower-middle-income countries groups. The modulus emanating from the eigenvalue stability condition with the roots of the companion matrix indicates that the model is stable. The results support the asymmetric impacts of oil prices on economic growth and aid policy formulation, particularly the cross-country disparities regarding the nexus between oil prices and growth.

From a methodological perspective, to the best of the author’s knowledge, the study is the first attempt to use the PVAR system GMM and such a large sample group of 184 economies in the post-COVID-19 era to examine the impacts of oil prices on countries’ growth while controlling for other crucial variables, which is noteworthy. Two, using the World Bank categorisation of countries according to income groups, the study adds another layer of contribution to the literature by decomposing the 184 sample economies into four income groups: high-income, low-income, upper-middle-income and lower-middle-income groups to investigate the potential for asymmetric effects of oil prices on growth, the first of its kind in the post-COVID-19 period.