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Most poverty research has explored monetary poverty. This chapter presents and analyzes the global multidimensional poverty index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water, and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to subgroups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.

The purpose of this paper is to evaluate how to use nodes in a cluster efficiently by studying the NAS Parallel Benchmarks (NASPB) on Intel Xeon and AMD Opteron dual CPU Linux clusters.

The performance results of the NASPB are presented both with one MPI process per node (1 ppn) and with two MPI processes per node (2 ppn). These benchmark results were analyzed by considering the impact of cache effects, code scalability, memory bandwidth within nodes, and the impact of MPI and the MPI communication network. Memory bandwidth was benchmarked using MPI versions of the Streams benchmarks. The impact of MPI and the MPI communication network are evaluated by benchmarking the performance of MPI sends and receives, MPI broadcast, and the MPI all‐to‐all routines.

The performance results from running the NASPB and from the memory bandwidth benchmarks show that better performance can sometimes be achieved using 1 ppn. Performance results show that the AMD Opteron/Myrinet cluster is able to achieve significantly better utilization of the second processor than the Intel Xeon/Myrinet cluster.

Most Linux clusters are purchased with two processors per node. One would like to run all applications on a cluster with two processors per node using 2 ppn instead of 1 ppn in order to utilize the second processor on each node. However, our results show that this is not always the best choice. Users should always assess their program performance with both 1 ppn and 2 ppn before running production calculations. This issue becomes even more important with the emergence of multi‐core processors.

To the authors' best knowledge, this is the only detailed comparison of AMD Opteron and Intel Xeon dual processor node parallel performance on large Myrinet clusters. The paper should be of value to everybody considering running on or purchasing AMD or Intel‐based Linux cluster.

The purpose of this paper is to adapt the market performance indicator (MPI), used by the European Commission to evaluate market conditions, over time, to show that the MPI explains actual switching behavior better than stated intent and satisfaction. While research on service provider switching has focused on the outcomes of service transactions and the benefits of switching, there is little research on how consumers view market conditions as being favorable or not for switching.

The authors used a mixed methodology of focus groups and longitudinal survey research of cell phone consumers to evaluate the effect of the MPI on satisfaction, perceptions of value, switching intentions and behavior.

The MPI was found to influence perceptions of satisfaction and value, and was found to contribute strongly to actual switching behavior. The results also showed that an improvement in the MPI or market conditions lead to a much greater relationship between it and actual switching behavior, suggesting that there may well be important threshold level, upon which greater switching behavior occurs.

The MPI provides marketers and policy-makers with benchmarks to compare the consumer welfare of different markets in different countries. Switching studies with MPI figures can be more easily generalized to different contexts.

The purpose of this paper is to highlight the case study of the Ministry for Primary Industries’ (MPI) Border Compliance Social Marketing programme. This programme aims to change the behaviour of international visitors to New Zealand. This is to protect New Zealand’s important horticultural and agricultural industries and environment from harmful pests and diseases. The programme encourages travellers to leave potential biosecurity risk items at home, or at least declare them to border staff or dispose of in special amnesty bins at New Zealand’s airports on arrival. It also influences local communities to advocate to friends and family overseas on MPI’s behalf.

Aimed at visitors with the highest identified risk, the programme uses a range of interventions in the pre-travel, in-journey and upon-arrival stages of travel. It is underpinned by social marketing theory and models, qualitative and ethnographic research and an understanding of the passenger journey.

The programme has delivered a significant reduction in the number of passengers being caught with prohibited items and has influenced behaviours in packing bags before travel and declaring items for inspection on arrival in New Zealand.

The programme contributes to the New Zealand biosecurity system, which protects the country’s key horticultural and agricultural industries. For example, the horticultural industry contributes $5.6bn annually to the New Zealand economy. It also protects native flora and fauna, which is a large attraction to overseas visitors, and contributes to the $12.9bn tourism industry.

In the framework of contingency theory, this paper aims to study the contextual variables that influence the variety of the contents of a performance measurement system, specifically the use of non-financial indicators in Moroccan public institutions and enterprises (MPIE).

Aiming to study the factors which influence the use of financial and non-financial indicators within MPIEs, the authors attempted to identify all performance indicators used by the MPIEs in the sample. They selected 23 MPIEs with an industrial and commercial character and analyzed their reports for the period from 2010 to 2015. To evaluate the variety of performance indicators within these organizations, they used the multi-dimensional definition of performance recommended by Kaplan and Norton (1998) and used linear regressions to explain their relationship with the contextual variables.

Three hypotheses were developed regarding these contingency factors, predicting a positive relationship between the age, the size and the competitive environment of the organization, on one hand, and the use of non-financial indicators on the other hand. Following the study of MPIEs, the authors found that these organizations normally use financial indicators. However, the use of non-financial indicators is influenced by the age of the organization alone.

The scientific contribution of this paper is twofold: first, the authors seek to fill the gap in studies of performance measurement systems for MPIEs; second, they wish to enrich the scientific literature for underdeveloped countries which suffer from lack of data. Its managerial contribution is also dual: first, the authors aim to provide managers of MPIEs with a clearer understanding of non-financial measures that fully address the different management needs of their organizations; second, they encourage the government control using non-financial aspects alongside financial aspects.

The purpose of this paper is to investigate whether the quality of the credit process is sensitive to reaching a particular threshold level of non-performing loans (NPLs) and, more importantly, whether higher NPLs ratios could make the monitoring activity ineffective.

The empirical design is composed of two steps: in the first step, the authors introduce a monitoring performance indicator (MPI) of the credit process by combining the non-parametric technique Data Envelopment Analysis with some financial ratios adopted as input and output variables. As second step, the authors apply a threshold panel regression model to a sample of 298 Italian banks, over the time period 2006–2014, and the authors investigate whether the quality of the credit process is sensitive to reaching a particular threshold level of NPLs.

This paper finds that, first, when the NPLs ratio remains below the threshold value estimated endogenously, an increase in the quality of monitoring has a positive impact on the NPLs ratio. Second, if the NPLs ratio exceeds the estimated threshold, the relationship between the NPLs ratio and quality of monitoring assumes a positive value and is statistically significant.

Due to the lack of data, the investigation of NPLs in the Italian industry across loan types combined with the monitoring effort by banks management was not possible. The authors plan to investigate this topic in future studies.

The identification of the threshold has a double operational valence. The first regards the Supervisory Authority, the threshold approach could be used as an early warning in order to introduce active control strategies based on the additional information requested or by on-site inspections. The second implication is highlighted in relation to the individual banks, the monitoring of credit control quality, if objective and comparable, could facilitate the emergence of best practices among banks.

A high NPLs ratio requires greater loan provisions, which reduces capital resources available for lending, and dents bank profitability. Moreover, structural weaknesses on banks’ balance sheets still persist particularly in relation to the inadequate internal governance structures. This means that bank management must able to recognise in advance early warning signals by providing prudent measurement together with an in-depth valuation of loans portfolio.

The originality of the paper is twofold: the authors introduce a new proxy of credit monitoring, called MPI; the authors provide an empirical proof of the Diamond’s (1991) economic intuition: for riskier borrowers, the monitoring activity is an inappropriate instrument depending on the bad reputational quality of borrowers.

The purpose of this paper is to determine the maintenance performance indicators (MPIs) which are significant for maintenance decision making in the apparel industry through an accurate maintenance performance measurement.

A quantitative research approach was followed. A questionnaire survey was used to collect the data which were evaluated based on Mean Weighted Rating and Relative Importance Index.

In total, 15 significant MPIs were determined which can directly affect maintenance decision making. A systematic approach was finally developed by allocating weightages for each critical MPI.

These results can be used to assist the decision-making process and as a performance measurement platform for maintenance management of the apparel industry.

The significance of maintenance has not been recognized and the value created through such massive efforts has remained hidden. Therefore, the need of adopting a performance-based approach for maintenance management in apparel industry exists. This research was aimed to provide a systematic approach to make decisions on maintenance management in the apparel industry in Sri Lanka.

The purpose of this paper is twofold: first, to examine whether polychronicity, an individual difference variable that involves a preference for multitasking, moderates the relationships between work-family conflict (WFC) and two work criteria, job satisfaction and work engagement; second, to examine two measures of polychronicity (the multitasking preference inventory (MPI) and the inventory of polychronic values (IPV)) and investigate whether polychronicity moderates the relationships between WFC and work criteria differently when measured by the MPI or the IPV.

The study’s sample included 257 respondents from the Amazon Mechanical Turk service who completed an online survey. Multiple regression analyses were conducted to test whether polychronicity moderated the relationships between WFC and two work criteria, job satisfaction and work engagement.

Polychronicity was found to significantly moderate the relationship between the work engagement and WFC. Follow-up analyses indicated that those who were lower in polychronicity had a significant decrease in work engagement as WFC increased, whereas those who were higher in polychronicity had relatively the same work engagement level regardless of changes in WFC. The results suggest that individuals higher in polychronicity have more personal resources and may be more resilient than those lower in polychronicity when it comes to not letting conflicts between their work and family lives affect how engaged they feel in their work.

This study extends the application of polychronicity to new domains of WFC and work engagement. The current study also contributed to the literature by investigating two measures of polychronicity (MPI and IPV) and finding that the MPI significantly moderated the relationship between WFC and work engagement, but the IPV did not. These findings indicate that there are important differences between the MPI and the IPV, and additional research is needed in comparing these two polychronicity measures.

The paper's aim is to assess performance of firms in the UK retail sector.

Economic efficiencies of 41 retail companies working in the UK between 2000 and 2005 are examined in this study using three related methodologies: data envelopment analysis (DEA), Malmquist productivity index (MPI), a bootstrapped Tobit regression model. DEA is used to calculate technical and scale efficiencies of companies. Two outputs (turnover, profit before taxation) and three inputs (total assets, shareholders funds, and number of employees) are employed for the efficiency measurement. MPI is used to analyze the patterns of efficiency change over the six year period 2000‐2005. DEA efficiencies are then used to test important hypotheses on the impact of environmental variables, namely head office location, type of ownership, years of incorporation, legal form and retail characteristic, on the functioning of the UK retail sector using bootstrapped Tobit regression.

DEA analysis has shown that only ten retail companies are considered as efficient under CRS assumption, and 16 firms under VRS assumption in 2005. MPI results have indicated that about 50 percent of retail companies have registered progress in terms of MPI during 2000 and 2005. Twenty out of 41 retail companies have adopted advanced and efficient retailing technologies during this period. Three environmental variables, namely the type of ownership, legal form and retail characteristic, have been found to play significant roles influencing retail efficiency using bootstrapped Tobit regression.

Data availability has limited the level of analysis in some parts of this study, especially in the bootstrapped Tobit regression.

This study seems to be the first in applying productivity analysis using DEA for the UK retail sector.

The purpose of this paper is to find the best solver for parallelizing particle methods based on solving Pressure Poisson Equation (PPE) by taking Moving Particle Semi-Implicit (MPS) method as an example because the solution for PPE is usually the most time-consuming part difficult to parallelize.

To find the best solver, the authors compare six Krylov solvers, namely, Conjugate Gradient method (CG), Scaled Conjugate Gradient method (SCG), Bi-Conjugate Gradient Stabilized (BiCGStab) method, Conjugate Gradient Squared (CGS) method with Symmetric Lanczos Algorithm (SLA) method and Incomplete Cholesky Conjugate Gradient method (ICCG) in terms of convergence, time consumption, parallel efficiency and memory consumption for the semi-implicit particle method. The MPS method is parallelized by the hybrid Open Multi-Processing (OpenMP)/Message Passing Interface (MPI) model. The dam-break flow and channel flow simulations are used to evaluate the performance of different solvers.

It is found that CG converges stably, runs fastest in the serial way, uses the least memory and has highest OpenMP parallel efficiency, but its MPI parallel efficiency is lower than SLA because SLA requires less synchronization than CG.

With all these criteria considered and weighed, the recommended parallel solver for the MPS method is CG.