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This study is to reconfigure a hierarchical supply chain model utilizing databases and text files to understand future pathways due to COVID-19 pandemic has had a bullwhip effect, disrupting the global supply chain, and a mechanism is needed to address this disruptive event under pandemic uncertainties.

To address this mechanism, this study employs bibliometric analysis and text mining to reconfigure a hierarchical supply chain model under pandemic conditions and associates it with social media to conduct an intuitive visual analysis.

The current academic concerns are related to an overconcentration on risk management and a data-driven approach, generating an enormous gap between the concerns of academics and those of the public. The evidence shows that for both countries with outstanding performance and those that need improvement, the efficiency in terms of preventing the spread of the pandemic should be promoted.

This study contributes to (1) reconfiguring a hierarchical supply chain model under pandemic uncertainties and (2) bridging theory and practice by offering comparable interrelated attributes to guide post-COVID-19 strategies in the supply chain. The findings are that the supply management approach and big data are attributes that involve the concerns of world public and academics under pandemic uncertainties.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

The purpose of this paper is to extract the characterized mineralization information from large numbers of data obtained from geologic exploration based on rough set; analyze the inherent relation between mineral information genes and metallogenic probability, and offer the scientific basis for target prediction.

Mineral information includes all kinds of relative metallogenic information. In order to extract comprehensive metallogenic prediction information, it is necessary to filter initial observation information to emphasize the factors that are most advantageous to metallogenic prognosis. Rough set can delete irrespective or unimportant attributes on the premises of no information missing and no classification ability changing, without supplementary information or prior knowledge, which has important theoretic and practical value for metallogenic prognosis.

The association and importance of geological information referring to prospecting are found out through attribute reduction based on rough set.

The analysis of geological and mineral information based on rough set is a novel approach for high‐dimensional complex non‐deterministic polynomial problems which are predominant in geological research. The research successfully extracts characterized mineralization information to offer the scientific basis for target prediction.

Looks at the eighth published year of the ITCRR and the research, from far and near, involved in this. Muses on the fact that, though all the usual processes are to the fore, the downside part of the industry is garment making which is the least developed side. Posits that the manufacture of clothing needs to become more technologically advanced as does retailing. Closes by emphasising support for the community in all its efforts.

The aim of this research was to identify and describe driving forces of importance in sponsorship during the seven years preceding a mega-sporting event like the Olympic Games 2008 in Beijing. This was done through the development of a conceptual 'meansobjectives model' linking sponsorship to brand equity factors and to objectives. The proposed model enables matching with real data consisting of 200 randomly chosen advertisements, articles and press releases from Chinese newspapers and the internet, revealing six types of means-objectives in sponsorship.

Within the fast-moving consumer goods (FMCG) supply chain, one of the problems facing the distribution channel strategy is the presence of the gray market. The article shows two novel antecedents of the participation of official distributors in this gray channel: Negative impact on distributor performance and the relationship with their supplier. Knowledge of this background helps to preserve the strategy outlined for the official distribution channel.

Data were collected from 172 Spanish wholesale distributors and analyzed using PLS-SEM.

The authors found that the damage through negative affectation in the official distributor's performance and the cooperation provided by the manufacturer, have different effects. While affectation is shown to be a powerful antecedent of participation in the gray market, the effect of perceived manufacturer cooperation does not show strong results.

In business practice, these findings lead the manufacturer to keep transactions carried out in the gray market at low levels and provide cooperation to official distributors to guarantee the official channel strategy aimed at efficiency in the distribution of branded goods.

The background of the gray market discussed in the study has not been previously analyzed in the literature. In this way, the authors contribute to the knowledge of such a common problem as the presence of the gray market in the segmentation of distribution channels of high-demand products.

Examines the ninth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The purpose of this paper is to identify and prioritize the drivers, enablers and resistors of agri-logistics improvements in an emerging economy like India. The field of agri-logistics lies at the critical intersection of the agricultural and logistics sectors and is capable of ameliorating the state of food distribution in the country. The inefficiencies inherent in the food distribution system in India lead to massive post-harvest wastage that is estimated at around 13bn dollars per annum. This paper examines the improvement drivers, enablers and resistors of agri-logistics that can significantly contribute toward the enhancement of the agricultural supply chain.

The synthesis and prioritization of drivers, enablers and resistors was based on an extensive literature review and consultation with experts. With the help of semi-structured interviews and a fuzzy analytic hierarchy process approach, the research develops a drivers-enablers-resitors framework.

The outcome is a hierarchy-based framework that prioritizes the drivers, enablers and resistors of agri-logistics. The research reveals the critical areas where decision makers should channelize their resources and efforts to gain maximum benefits.

The segmentation of the factors impacting agri-logistics into drivers, enablers and resistors provides a fresh perspective on the issue and helps improve understanding of the problem. Prioritization of the factors represents a unique contribution to the field of agri-logistics.

The discussion on energy efficiency has been increasing due to the increasing population, emissions of degradable and harmful pollutants, and clean energy substitutes are being developed in order to manage and control the energy requirements all over the world. Against this backdrop, the factors of technological innovation and environmental regulations have been determined as key indicators for the evaluation of sustainable developments and practices in the energy efficiency evaluation studies.

A two-stage analysis process has been configured for evaluation of the energy efficiency. The first stage includes the estimation of the Total factor energy efficiency scores using the data envelopment Multiplier input-oriented methodology, while the second stage includes the exploration of the impact of technological innovation and government environmental regulations on the Total factor energy efficiency scores obtained in the first step through the application of a spatial regression model.

This paper highlights the link between the need for and impact of energy efficiency innovations and shows that the energy efficiency goal can be fulfilled by incorporating laws on sustainability and incorporating strict regulations that allow for the use of clean energy, low carbon energy technologies.

The present study, furthermore, provides evidence from 15 countries, five from three different continents, i.e. Asia, Europe and Africa so that a cross-country performance of these factors can be evaluated. The main contribution of the present study is the evaluation of the technological innovation on energy efficiency. There have been studies evaluating various factors on the development of energy-efficient practices; however, the focus on the role of technological innovation and governmental regulations has been scarce.

The authors point out that the existing research confuses the operational liabilities formed based on the “transaction” relationship with the financial liabilities formed based on the “investment” relationship, which not only exaggerates the value of leverage but also underestimates the level of protection that companies provide for creditors alone. That is, the confusion of concepts not only triggers the problem of leverage misestimate but also triggers the short-term financial risk misestimate. The performance of “nominal leverage” and “nominal short-term solvency” based on total assets calculation cannot reflect the real leverage level and the real short-term financial risk of enterprises.

To distinguish the concepts of “assets” and “capital” and rationalize the relationship between “transactions” and “investments”, authors systematically design the “real leverage” indicators and “real short-term solvency” indicators, and measure the degree of misestimate of leverage and short-term financial risk indicators by traditional research. On this basis, this paper describes and analyses the trends of leveraged misestimate and short-term financial risk misestimate of listed companies in China and analyses which companies have more serious leverage misestimate. And it helps readers to form an objective understanding of the leveraged misestimate and short-term financial risk misestimate of listed companies in China.

Firstly, the overall high level of leverage of listed companies in China in the traditional sense is largely because of the misestimate of indicators. And this kind of misestimate is more serious among firms that have advantages in trading, such as state-owned enterprises and firms with higher market shares. Secondly, for most firms with normal solvency, traditional research systematically overestimated the negative impact of “nominal leverage” on financial risk indicators (represented by short-term solvency). The overestimation is significant in firms with serious leverage misestimate. Thirdly, indicators’ misestimate of the traditional research makes the banks cannot make effective credit decisions according to the firm's “real leverage” and “real short-term solvency”.

Firstly, clarify the differences between the concepts of “assets” and “capital”, and clarify the level of “real leverage” of listed companies in China, which is conducive to the process of “de-leveraging”. Secondly, revise the problem of misestimate of related indicators, so that financial institutions can clearly identify the true profitability and real risk level of the entity domain, and thus improve the effectiveness of credit decisions.