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A study was set to define a suitable procedure of quality assurance, aiming to define quality measurements and develop assessment questionnaires. The exercise started with a survey of products and services offered by individual centres. The need for a mission statement emerged as a prerequisite to any quality definition. Objectives for a hypothetical drug information centre were drawn. Essential common quality indicators adequate to the full range of products were identified. Specific quality indicators for each product have also been produced. Recommendations on assessment techniques were defined and follow up measures were indicated. Overall assessment of the service was not tackled as resourcing was considered critical for the production; individual parameters were not weighted, as the weakest ring in a quality chain defines the overall quality of the product. The understanding of needs and queries of customers emerged as crucial to the achievement of quality; indications were given as how to proceed in case of a direct contact with end customers being impossible. Drug information professional's responsibilities were also stressed, particularly in the case of a ‘negative’ answer.

In this chapter, the authors ask two questions: (i) Is the conduct of monetary policy stable across time and similar across major economies? and (ii) Do policy decisions of major central banks have international spillover effects? To address these questions, the authors build on recent semi-parametric advances in time-varying parameter models that allow us to increase the vector autoregressive () dimension and to jointly model three advanced economies (USA, UK and the Euro Area). The main reduced-form finding of this chapter is an increased connectedness between and within countries during the recent financial crisis. In order to study policy spillovers, we jointly identify three economy-specific monetary policy shocks using a combination of sign and magnitude restrictions. The authors find that monetary policy shocks were larger in magnitude and more persistent in the early 1980s than in subsequent periods. The authors also uncover positive spillover effects of policy between countries in the 1980s and diminished, and sometimes negative ‘beggar-thy-neighbour’ effects in the second half of the sample. Moreover, during the 1980s, the authors find evidence for policy coordination between the Federal Reserve, the Bank of England and the European Central Bank.

The purpose of this paper is to investigate a novel generalised grey target decision method (GGTDM) with index and weight involving mixed attribute values.

The mixed attribute values are transformed into binary connection numbers and also comprised of two-tuple (determinacy, uncertainty) numbers to fulfil the decision-making task. The proposed method constructs the weight function to convert the mixed attribute-based weights into the certain number-based weights and determines the alternatives ranking by the comprehensive weighted Gini–Simpson indices (CWGSIs).

The result of decision making regarding the numerical example by the proposed approach is somewhat different from that obtained by the reported vector-based method. The reasons for this are threefold: the decision-making bases are different, the target centre indices are determined by different mechanisms and certain number-based weights are calculated in different ways.

The proposed method ranks an alternative based on the Gini–Simpson index, as derived from the viewpoint of measuring the uncertainty (heterogeneity): however, the vector-based GGTDM makes a decision based on proximity, as is the case when measuring the similarities between index vectors.

The proposed approach is admissible to solving mixed attribute-based decision making especially for alternative indices and attribute weights containing both uncertain numbers.

The proposed method provides a new perspective on measuring the difference of alternatives to the target centre via the CWGSI: the CWGSI is obtained by relying on the pseudo-probabilities achieved by the ratios of the alternative indices to the target centre indices. It also builds a weight function converting the mixed attribute-based weights into certain number-based weights. This method provides a framework that should be tested in terms of its effective decision making using real data and an actual problem.

Purpose: The purpose of this study is to assess the effect of social isolation of minors with a parent or grandparent suffering from amyotrophic lateral sclerosis (ALS) and to determine whether the psychological support offered by an Italian no-profit association helped them to manage stress.

Methodology: This study followed a qualitative research design. The participants responded to in-depth interviews that were processed with inductive thematic analysis.

Findings: Five themes emerged: feedback on the psychological intervention; learning and changes after the intervention; discourses on illness and death in the family; experiences and difficulties during the lockdown and suggestions for other peers who might face the same situation.

Social Implications: Psychological support is necessary for these minors, and it helped them to manage both the stress of living with ALS and the limitations of social relationships during the pandemic. It showed the importance of authentic and honest communication about illness and death that allowed minors to manage anxiety and fear. Positive reinterpretation of these experiences by transforming them into opportunities was also revealed.

Originality: Studies on families with ALS patients are numerous, but studies on children of these patients are still rare, and no study has investigated the impact of the COVID-19 pandemic on these children. This research investigated a topic that has not been covered previously and it also provided the opportunity to know how these children, preadolescents and adolescents living in an already complex environment, have experienced lockdown and restrictions. The study also enriched the literature on this important issue.

This paper investigates the change in informational spillover between nine Asian capital markets and the United States as a result of the 1997–98 financial meltdown in Asia. Our study period extends from about three years prior to the start of the crises on July 2, 1997 to one year after this date. We conduct spillover studies on daily stock market index prices and returns to determine the changes in market interdependence. Our results indicate a considerable increase in cross‐border cointegration during the crisis. Dramatic shifts in predictability and volatility spillovers are observed in most Asian countries as a result of the Asian financial crisis, providing evidence of an increase of interdependence between Asian countries, and thus suggesting contagion. We observe a strong interdependence with the US markets before the crisis, which persists during the crisis. We also show that Hong Kong and Korea have emerged as the most dominant influences in the region during the Asian financial crisis.

Business groups often contain banks or near banks that can protect group firms from economic shocks. A group bank subordinate to other group firms can become an “organ bank” that selflessly bails out distressed group firms and anticipates a government bailout. A group bank subordinating other group firms can extend loans to suppress their risk taking to default risk, preserving risk-averse low-productivity zombie firms. Actual business groups can fall between these polar cases. Subordinated group banks magnify risk taking; subordinating group banks suppress risk taking; yet both distortions promote business group firms’ survival. Limiting intragroup income and risk shifting, severing banks from business groups, articulating Business Group Law, or dismantling business groups may mitigate both distortions but also limits business groups’ internal markets, which are thought to be important where external markets work poorly.

In China, more than 80,000 people have been diagnosed with COVID-19, and more than 3,000 people have lost their lives. It seems that there will be more deaths since the epidemic is not over. All the Chinese provinces have reported the COVID-19 cases. This chapter aims to explore the trend of COVID-19 treatment efficiency in Chinese provinces using the data released daily by China Center for Disease Control and Prevention. Since China Center for Disease Control and Prevention began to release data daily from January 24 to March 12, we have more than 40 groups of daily data for 31 provinces in China mainland. In the calculation, we take the daily data of each province as a sample and then we have more than 1,200 samples in this study.

We use additive two-stage data envelopment analysis as an efficiency evaluation tool to calculate the COVID-19 treatment efficiency. In our framework, the first stage is to understand the infection rate and the second stage is to evaluate the treatment efficiency. In the first stage for the tth day, we use total population (p) and number of people infected in the previous day (inf _t−1) as the inputs and cumulative number of people infected in the current day (inf _t ) as the output. In the second stage for the tth day, we use cumulative number of people infected in the current day (inf _t ) as the input and cumulative death in the current day (death _t ) and cumulative recovery in the current day (recov _t ) as the outputs. Some techniques on how to deal with undesirable outputs such as inf _t and death _t are employed in this study.

After we have the infection rate and treatment efficiency for the samples more than 1,200, we analyze the COVID-19 treatment efficiency and its development trend from January 24 to March 12 in 34 regions of China from static and dynamic aspects. The results show that, on the whole, the overall efficiency and phased efficiency of COVID-19 treatment efficiency in all regions of China are relatively high, which reflects the key factor for the Chinese government to quickly control the epidemic in the short term. Relatively speaking, the average efficiency value in the infection stage (first stage) is lower than the average efficiency value in the healing stage (second stage), which shows that the focus of anti-epidemic in China should be early detection and prevention rather than treatment process. In terms of trend, the total efficiency of COVID-19 treatment in each region shows a trend of “increasing first and then decreasing.” Our analysis indicates that in the initial stage, the continuous increase of various resources leads to the rise of the total efficiency, while in the later stage, the rapid decline of the number of infected people leads to the decrease of the total efficiency. Based on the results of the efficiency analysis, this study provides corresponding management implications and policy suggestions, hoping to provide some enlightenment and suggestions for the anti-epidemic work of other countries in the severe environment where the epidemic is spreading rapidly.

This chapter explains the impact containerisation has on the various partners of the global supply chain and the challenges companies encounter and the solutions they use in dealing with empty container repositioning.

The phenomenon of imbalanced container flows and its impact on shipping lines, shippers, container haulage companies, port development and the economy are presented. Special attention is given to explain the many solutions companies use to reduce the impact of empty container repositioning, hence tracing out the past research that led to these solutions and pointing to potentially new research directions in the future.

Because of the widespread use of containerisation and the imbalanced container flows that results from globalisation, empty container repositioning will be an ongoing issue for the maritime logistics industry. Many solutions are being used, but there is room for improvement and more research is needed.

Empty container repositioning is an important issue but has not been deemed as such in the literature. This chapter explains the reasons it is important and that its impact is not limited to shipping lines only but affects the whole supply chain.