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This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of fuzzy numbers.

This research has been organized to proceed along the following steps: computing the grey relational coefficients for alternatives with respect to each attribute using a fuzzy GRA methodology. Grey relational coefficients provide the required (output) data for additive DEA models; computing the priority weights of attributes using the AHP method to impose weight bounds on attribute weights in additive DEA models; computing grey relational grades using a pair of additive DEA models to assess the performance of each alternative from the optimistic and pessimistic perspectives; and combining the optimistic and pessimistic grey relational grades using a compromise grade to assess the overall performance of each alternative.

The proposed approach provides a more reasonable and encompassing measure of performance, based on which the overall ranking position of alternatives is obtained. An illustrated example of a nuclear waste dump site selection is used to highlight the usefulness of the proposed approach.

This research is a step forward to overcome the current shortcomings in the weighting schemes of attributes in a fuzzy multiattribute GRA methodology.

The aim of this work is to provide a theoretical model that can help companies to develop a unique approach to achieve both corporate environmental sustainability (CES) and successful customer experience management (CEM).

A two-phase study achieved the research aim. The first phase consisted of the analysis of contemporary theoretical contributions with a focus on CES and CEM. In the second phase, taking a qualitative approach, the key dimensions identified in the initial analysis were investigated to explore the dominant perceptions of practitioners and to hone the theoretical categories.

Five innovative pathways emerged from the study to inform decision-making while maintaining the dual objectives of CES and successful CEM. These pathways are combined to offer a strategic tool for managers and for research advances. This original integrated model also offers six novel theoretical propositions that describe how to shape corporate decisions to achieve environmental sustainability in CEM.

Firms can benefit from an approach that integrates CES and CEM to develop a new mindset for an innovative and valuable decision-making process and to design more captivating experiences for customers. Nevertheless, the efficacy and generalizability of the theoretical framework and propositions require empirical testing.

This paper makes an original contribution to the environmental sustainability and marketing literature by bringing together all elements in these fields of research in a conceptual model. Moreover, this paper proposes theoretical propositions that advance knowledge of the subject and offer ideas for future research and managers.

The purpose of this paper is to review the food supply chain management (FSCM) in terms of systems and implementations so that observations and lessons from this research could be useful for academia and industrial practitioners in the future.

A systematical and hierarchical framework is proposed in this paper to review the literature. Categorizations and classifications are identified to organize this paper.

This paper reviews total 192 articles related to the data-driven systems for FSCM. Currently, there is a dramatic increase of research papers related to this topic. Looking at the general interests on FSCM, research on this topic can be expected to increase in the future.

This paper only selected limited number of papers which are published in leading journals or with high citations. For simplicity without generality, key findings and observations are significant from this research.

Some ideas from this paper could be expanded into other possible domains so that involved parties are able to be inspired for enriching the FSCM. Future implementations are useful for practitioners to conduct IT-based solutions for FSCM.

As the increasing of digital devices in FSCM, large number of data will be used for decision-makings. Data-driven systems for FSCM will be the future for a more sustainable food supply chain.

This is the first attempt to provide a comprehensive review on FSCM from the view of data-driven IT systems.

Terrestrial laser scanning (TLS) point clouds have been widely used in deformation measurement for structures. However, reliability and accuracy of resulting deformation estimation strongly depends on quality of each step of a workflow, which are not fully addressed. This study aims to give insight error of these steps, and results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. Thus, the main contributions of the paper are investigating point cloud registration error affecting resulting deformation estimation, identifying an appropriate segmentation method used to extract data points of a deformed surface, investigating a methodology to determine an un-deformed or a reference surface for estimating deformation, and proposing a methodology to minimize the impact of outlier, noisy data and/or mixed pixels on deformation estimation.

In practice, the quality of data point clouds and of surface extraction strongly impacts on resulting deformation estimation based on laser scanning point clouds, which can cause an incorrect decision on the state of the structure if uncertainty is available. In an effort to have more comprehensive insight into those impacts, this study addresses four issues: data errors due to data registration from multiple scanning stations (Issue 1), methods used to extract point clouds of structure surfaces (Issue 2), selection of the reference surface S_ref to measure deformation (Issue 3), and available outlier and/or mixed pixels (Issue 4). This investigation demonstrates through estimating deformation of the bridge abutment, building and an oil storage tank.

The study shows that both random sample consensus (RANSAC) and region growing–based methods [a cell-based/voxel-based region growing (CRG/VRG)] can be extracted data points of surfaces, but RANSAC is only applicable for a primary primitive surface (e.g. a plane in this study) subjected to a small deformation (case study 2 and 3) and cannot eliminate mixed pixels. On another hand, CRG and VRG impose a suitable method applied for deformed, free-form surfaces. In addition, in practice, a reference surface of a structure is mostly not available. The use of a fitting plane based on a point cloud of a current surface would cause unrealistic and inaccurate deformation because outlier data points and data points of damaged areas affect an accuracy of the fitting plane. This study would recommend the use of a reference surface determined based on a design concept/specification. A smoothing method with a spatial interval can be effectively minimize, negative impact of outlier, noisy data and/or mixed pixels on deformation estimation.

Due to difficulty in logistics, an independent measurement cannot be established to assess the deformation accuracy based on TLS data point cloud in the case studies of this research. However, common laser scanners using the time-of-flight or phase-shift principle provide point clouds with accuracy in the order of 1–6 mm, while the point clouds of triangulation scanners have sub-millimetre accuracy.

This study aims to give insight error of these steps, and the results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds.

The results of this study would provide guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. A low-cost method can be applied for deformation analysis of the structure.

Although a large amount of the studies used laser scanning to measure structure deformation in the last two decades, the methods mainly applied were to measure change between two states (or epochs) of the structure surface and focused on quantifying deformation-based TLS point clouds. Those studies proved that a laser scanner could be an alternative unit to acquire spatial information for deformation monitoring. However, there are still challenges in establishing an appropriate procedure to collect a high quality of point clouds and develop methods to interpret the point clouds to obtain reliable and accurate deformation, when uncertainty, including data quality and reference information, is available. Therefore, this study demonstrates the impact of data quality in a term of point cloud registration error, selected methods for extracting point clouds of surfaces, identifying reference information, and available outlier, noisy data and/or mixed pixels on deformation estimation.

The main purpose of this study is to test the performance of the ink-jet printed microwave resonant circuits on Low temperature co-fired ceramics (LTCC) substrates combined with microfluidic channels for sensor applications. Normally, conductive patterns are deposited on an LTCC substrate by means of the screen-printing technique, but in this paper applicability of ink-jet printing in connection with LTCC materials is demonstrated.

A simple microfluidic LTCC sensor based on the microstrip ring resonator was designed. It was assumed the micro-channel, located under the ring, was filled with a mixture of DI water and ethanol, and the operating frequency of the resonator was tuned to 2.4 GHz. The substrate was fabricated by standard LTCC process, and the pattern of the microstrip ring resonator was deposited over the substrate by means of an ink-jet printer. Performance of the sensor was assessed with the use of various volumetric concentrations of DI water and ethanol. Actual changes in concentration were detected by means of microwave measurements.

It can be concluded that ink-jet printing is a feasible technique for fast fabrication of micro-strip circuits on LTCC substrates, including microfluidic components. Further research needs to be conducted to improve the reliability, accuracy and performance of this technique.

The literature shows the use of ink-jet printing for producing various conductive patterns in different applications. However, the idea to replace the screen-printing with the ink-jet printing on LTCC substrates in connection with microwave-microfluidic applications is not widely studied. Some questions concerning accuracy and reliability of this technique are still open.

The objective of this study is to present a successful strategy to promote Korea as the logistics hub of Northeast Asia. Firstly, we introduce the necessity of a logistic hub strategy for Korea. In order to develop a successful strategy, we consider the 'free trade zone' model of the Netherlands and China. We develop a realistic and suitable model for Korea based on this Jree trade zone' model. Our proposal for a successful logistic hub strategy for Korea is the fulfillment of the following six objectives: 1) security of market accessibility, 2) improvement of the logistic system, 3) improvement of the education system, 4) improvement of the tax system, 5) assurance of labor market flexibility, and 6) development of an appealing living environment for foreigners.

Emotionally intelligent leadership (EIL) theory combines relevant models, theories, and research in the areas of emotional intelligence (EI) and leadership. With an intentional focus on context, self and others, emotionally intelligent leaders facilitate the attainment of desired outcomes. The 21 capacities described by the theory equip individuals with the knowledge, skills, abilities, and other characteristics to achieve desired results. The purpose of this article is to propose an integrative, process-oriented EIL theory to provide a framework for conceptualizing and integrating future research and practice. The authors review and organize research and theory in emotional intelligence and leadership within the context of higher education, introduce the EIL model, and provide suggestions for future research. The article concludes with practical implications for leadership development in the context of higher education.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

The 1997-98 financial crisis has had a profound effect on how East Asian economies the role of the IMF and its strategic interests relative to those of the United States in the international financial regime. It has prompted them to create a regional mechanism for financial and monetary cooperation, ranging from deeper policy dialogue and surveillance, to a system of financial cooperation, and common exchange rate arrangements. This paper analyses the economic and strategic motivations behind this and outlines recent developments in financial cooperation in East Asia to provide possible directions for the future.

A network of bilateral swap arrangements under the Chiang Mai Initiative(CMI) needs stronger policy dialogue and surveillance to develop into a regional financing facility, a sort of East Asian IMF. The facility plays a role as an regional lender of last resort, providing short-term funds to a member country facing a temporary liquidity shortage and for market intervention to stabilize foreign exchange rate. East Asian countries need to achieve regional exchange rate stability. In the long run, the region may develop a common currency arrangement, but it cannot be expected in the very near future because there is no convergence of macroeconomic conditions, economic structure and systems. A realistic approach would be for East Asian developing countries to adopt a currency basket system to minimize the impact of dollar/yen exchange rate volatility on their economies. Strong political will and a vision for regional integration will be required to introduce it.

Increasing carbon productivity is an effective way to reduce carbon emissions, while boosting economic prosperity. For appropriate formulating and enforcement of energy saving and carbon emissions reduction policies in various sectors, it is of great significance to investigate the evolution characteristics and convergence modes of carbon productivity across the manufacturing sectors.

Using slack-based measure directional distance function (SBM-DDF) and global Malmquist–Luenberger (GML) productivity index, this paper measures the carbon productivities of 29 manufacturing subsectors in Shanghai, China, from 2001 to 2016 under the total factor framework. Furthermore, based on the convergence theories, it empirically examines the convergence of carbon productivity across these manufacturing sectors.

The measurement results suggest that the carbon productivities of the manufacturing sectors in Shanghai show an increasing tendency on the whole, and technical efficiency instead of technological change makes a main contribution to the increase. It is found that there is no obvious σ convergence across the manufacturing sectors in Shanghai, but there exist both absolute ß convergence and conditional ß convergence. Moreover, there is heterogeneity in convergence characteristics between the clean sectors and polluting sectors. The findings also show that firm size and industry structure have significant positive impacts on the growth of carbon productivities of the manufacturing sectors, whereas the impacts of capital deepening and energy consumption structure are significantly negative.

This paper measures the carbon productivities of the manufacturing subsectors by applying SBM-DDF and GML index, so as to improve the accuracy. It provides an insight into the convergence of carbon productivity across the manufacturing sectors.