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The authors propose a semiparametric approach for testing independence between two infinite-order cointegrated vector autoregressive series (IVAR(∞)). The procedures considered can be viewed as extensions of classical methods proposed by Haugh (1976, JASA) and Hong (1996b, Biometrika) for testing independence between stationary univariate time series. The tests are based on the residuals of long autoregressions, hence allowing for computational simplicity, weak assumptions on the form of the underlying process, and a direct interpretation of the results in terms of innovations (or shocks). The test statistics are standardized versions of the sum of weighted squares of residual cross-correlation matrices. The weights depend on a kernel function and a truncation parameter. Multivariate portmanteau statistics can be viewed as a special case of our procedure based on the truncated uniform kernel. The asymptotic distributions of the test statistics under the null hypothesis are derived, and consistency is established against fixed alternatives of serial cross-correlation of unknown form. A simulation study is presented which indicates that the proposed tests have good size and power properties in finite samples.

While there exist many surveys on the use stochastic frontier analysis (SFA), many important issues and techniques in SFA were not well elaborated in the previous surveys, namely, regular models, copula modeling, nonparametric estimation by Grenander’s method of sieves, empirical likelihood and causality issues in SFA using regression discontinuity design (RDD) (sharp and fuzzy RDD). The purpose of this paper is to encourage more research in these directions.

A literature survey.

While there are many useful applications of SFA to econometrics, there are also many important open problems.

This is the first survey of SFA in econometrics that emphasizes important issues and techniques such as copulas.

Unsustainable logging and illegal logging for domestic and international trade and trafficking continue to lead to deforestation. It is crucial that Sustainable Development Goal 15 ‘Sustainably manage forests, combat desertification, halt and reverse land degradation, halt biodiversity loss’ is achieved to maintain the livelihoods of people and protect the planet. This is the case in Vietnam as well, where many people, including indigenous groups, rely on the forest for their survival. Drawing on semistructured interviews in Vietnam and a literature review, we investigate how the abuse of forest policies leads to human insecurity. From this, we propose solutions to (1) end unsustainable harvesting and illegal logging (SDG 15.7), (2) integrate the value of forests (culturally and economically) into national and local planning, the development process and poverty elimination strategies (SDG 15.9) and (3) improve the use of forest protection funding provided by international donors.

This paper aims to present a systematic approach in the literature survey related to metal additive manufacturing (AM) processes and its multi-physics continuum modelling approach for its better understanding.

A systematic review of the literature available in the area of continuum modelling practices adopted for the powder bed fusion (PBF) AM processes for the deposition of powder layer over the substrate along with quantification of residual stress and distortion. Discrete element method (DEM) and finite element method (FEM) approaches have been reviewed for the deposition of powder layer and thermo-mechanical modelling, respectively. Further, thermo-mechanical modelling adopted for the PBF AM process have been discussed in detail with its constituents. Finally, on the basis of prediction through thermo-mechanical models and experimental validation, distortion mitigation/minimisation techniques applied in PBF AM processes have been reviewed to provide a future direction in the field.

The findings of this paper are the future directions for the implementation and modification of the continuum modelling approaches applied to PBF AM processes. On the basis of the extensive review in the domain, gaps are recommended for future work for the betterment of modelling approach.

This paper is limited to review only the modelling approach adopted by the PBF AM processes, i.e. modelling techniques (DEM approach) used for the deposition of powder layer and macro-models at process scale for the prediction of residual stress and distortion in the component. Modelling of microstructure and grain growth has not been included in this paper.

This paper presents an extensive review of the FEM approach adopted for the prediction of residual stress and distortion in the PBF AM processes which sets the platform for the development of distortion mitigation techniques. An extensive review of distortion mitigation techniques has been presented in the last section of the paper, which has not been reviewed yet.

The insertion of a peg in a hole is the final phase in the assembly of a peg and a block with a hole. This paper briefly analyses the physical interaction between these two components during insertion, describes a simple fine‐motion device which utilizes this interaction to insert pegs into closely‐fitting holes, and discusses possible variations to the construction of the device.

Most governments around the world rely heavily on tax revenue to fund not only their recurrent expenditure but also their long-term development goals. There is some evidence suggesting that tax evasion in Vietnam has, over the years, been on the rise in terms of number, scale and degree of sophistication. It may thus be beneficial to understand the extent to which various relevant psychological factors interact to influence the tax compliance of Vietnamese taxpayers. This chapter attempts to quantify the effects of taxpayer's emotion, trust and perception on their tax compliance in Vietnam. It adopts a positivist research framework, a quantitative research method and primary data collection. First, a simple, theoretical model in which emotion and trust affect tax compliance both directly and indirectly through perception as a mediating variable, is constructed. The Baron−Kenny method is then applied to the data collected from an e-survey to test various hypotheses derived from the devised theoretical model. The results show that taxpayer's perception positively and significantly influences tax compliance whereas emotion and trust exert significant and positive effects on tax compliance both directly and indirectly (via perception). The findings suggest that voluntary tax compliance in Vietnam can be improved through better tax administration services, more fiscal policy accountability and pro-active tax socialization.

The advancement of additive manufacturing technologies has resulted in producing parts of high quality and reduced manufacturing time. This paper aims to achieve a simultaneous optimal solution for build time and surface roughness as the output data and also to find the best values for the input data consisting of build orientation, extrusion width, layer thickness, infill percentage and raster angle.

For this purpose, the effects of process parameters on the response variables were investigated by the design of experiments approach to develop empirical models using response surface methodology. The experimental parts of this research were conducted using an inexpensive and locally assembled fused filament fabrication (FFF) machine. A total of 50 runs for 4 different geometries, namely, cylinder, prism, 3DBenchy and twist gear vase, were performed using the rotatable central composite design, and each process parameters were investigated in two levels to develop empirical models. Also, a novel optimization method, namely, the posterior-based method, was accomplished to find the best values for the response variables.

The results demonstrated that not only the build orientation and layer thickness have notable effects on both response variables but also build time is dependent on extrusion width and infill percentage. Low infill percentage and high extrusion width resulted in increasing build time. By reducing layer thickness and infill percentage while increasing extrusion width, parts of high-quality surface finish and reduced built time were produced. Optimum process parameters were found to be of build direction of 0°, extrusion width of 0.61 mm, layer thickness of 0.22 mm, infill percentage of 20% and raster angle of 0°.

Through the developed empirical models and by minimizing build orientation and layer thickness, and also considerations for process parameters, parts of high-quality surface finish and reduced built time could be produced on FFF machines. To compensate for increased build time because of reduction in layer thickness, extrusion width and infill percentage must have their maximum and minimum value, respectively.

Green innovation in supply chains is crucial for socioeconomic development and stability. Factors that influence collaborative green innovation in the supply chain are complex and diverse. Exploring the main influencing factors and their mechanisms is essential for promoting collaborative green innovation in supply chains. Therefore, this study analyzes how upstream and downstream enterprises in the supply chain collaborate to develop green technological innovations, thereby providing a theoretical basis for improving the overall efficiency of the supply chain and advancing green innovation technology.

Based on evolutionary game theory, this study divides operational scenarios into pure market and government-regulated operations, thereby constructing collaborative green innovation relationships in different scenarios. Through evolutionary analysis of various entities in different operational scenarios, combined with numerical simulation analysis, we compared the evolutionary stability of collaborative green innovation behavior in supply chains with and without government regulation.

Under pure market mechanisms, the higher the green innovation capability, the stronger the willingness of various entities to collaborate in green innovation. However, under government regulation, a decrease in green innovation capability increases the willingness to collaborate with various entities. Environmental tax rates and green subsidy levels promote collaborative innovation in the short term but inhibit collaborative innovation in the long term, indicating that policy orientation has a short-term impact. Additionally, the greater the penalty for collaborative innovation breaches, the stronger the intention to engage in collaborative green innovation in the supply chain.

We introduce the factors influencing green innovation capability and social benefits in the study of the innovation behavior of upstream and downstream enterprises, expanding the research field of collaborative innovation in the supply chain. By comparing the collaborative innovation behavior of various entities in the supply chain under a pure market scenario and government regulations, this study provides a new perspective for analyzing the impact of corresponding government policies on the green innovation capability of upstream and downstream enterprises, enriching theoretical research on green innovation in the supply chain to some extent.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

The purpose of this paper is to present research work based on the authors’ conceptual framework reported in the VRAP Conference 2013. It is related with an efficient method to obtain an optimal part build orientation for additive manufacturing (AM) by using AM features with associated AM production knowledge and multi-attribute decision-making (MADM). The paper also emphasizes the importance of AM feature and the implied AM knowledge in AM process planning.

To solve the orientation problem in AM, two sub-tasks, the generation of a set of alternative orientations and the identification of an optimal one within the generated list, should be accomplished. In this paper, AM feature is defined and associated with AM production knowledge to be used for generating a set of alternative orientations. Key attributes for the decision-making of the orientation problem are then identified and used to represent those generated orientations. Finally, an integrated MADM model is adopted to find out the optimal orientation among the generated alternative orientations.

The proposed method to find out an optimal part build orientation for those parts with simple or medium complex geometric shapes is reasonable and efficient. It also has the potential to deal with more complex parts with cellular or porous structures in a short time by using high-performance computers.

The proposed method is a proof-of-concept. There is a need to investigate AM feature types and the association with related AM production knowledge further so as to suite the context of orientating parts with more complex geometric features. There are also research opportunities for developing more advanced algorithms to recognize AM features and generate alternative orientations and refine alternative orientations.

AM feature is defined and introduced to the orientation problem in AM for generating the alternative orientations. It is also used as one of the key attributes for decision-making so as to help express production requirements on specific geometric features of a desired part.