429 research outputs found
Lead time management in the garment sector of Bangladesh: an avenues for survival and growth
Bangladesh has emerged as an important supplier of quality readymade garments in the global market. The spectacular growth of garment sector in Bangladesh in recent years
has dramatically changed the landscape of export composition of the country. Once heavily dependent on exports of primary products lead by Jute, the economy of Bangladesh is now experiencing almost 76% export contribution from readymade garments (RMG). The sector
has now occupied an important place in Bangladesh national economy. Nevertheless, all is not well in this sector. It faces numerous challenges and it is now on the crossroad with the phasing out of quota system, GSP facilities and new provisions of WTO. In this study attempts have been made to find out the ways to face the competitive business environment by the efficient management process towards the lead time reduction. The main purpose of this article is to analyse the business process of the garment sector to find out it’s lead time minimization process. The study has been concluded by the development of a new diagram of business process with the outcome that the other management process in the supply chain is an important factor rather than process management in the lead time minimization process
The impact of customer perceived service quality on customer satisfaction for private health centre in Malaysia: a structural equation modeling approach
The main purpose of this paper is to develop and test the modified SERVQUAL model to
measure Malaysian private healthcare quality. A total of 131 participants were selected randomly those
visit private hospitals in Malaysia for healthcare facility. Then data were examined using means,
correlations, principal component and exploratory factor analysis to establish the modified SERVQUAL
scale’s reliability, underlying dimensionality and convergent, discriminant validity. This paper than
utilizes the structural equation modeling technique to do confirmatory factor analysis and test the
hypothesized positive inter-relationships between customer’s perception and customer satisfaction. This
paper reviews and identifies essential service quality variables that are associated with the customer
satisfaction in the private hospital. Customer satisfaction should reflect the need of healthcare quality
requested by the customers, as direct and indirect relationships exist between personnel support and
customer satisfaction and attention to customers and hospital facilities and between hospital facilities
and customer satisfaction. The proposed model has been tested on only one private hospital in Malaysia
due to short period. Due to this small sample size and the convenient method of data collection, there is a
possibility of biasness of the authors may play a role in the outcome of the study. The main contribution
of this study is that, it proposes a way to assess quality services in the private hospitals. This study has
proposed a conceptual model that need further investigation and opens a way for future research
Bureaucratic behaviour, and its influence towards competitiveness – analysing the supply chain of Bangladeshi clothing industry
Distribution systems are becoming increasingly complex and dynamic in business in the consumer market of clothing or Readymade Garments (RMG) products. There are many exterior influencing elements like political action (PA), country risk (CR), and bureaucratic behaviours (BB) that are influencing the clothing supply chain and posing threats to its competitiveness. A research question has developed to know how BB activities affect competitiveness. Based on this research question, this research aims to determine BB’s influence on the competitiveness of the clothing supply chain. Stakeholder philosophies and resource dependence theory have been considered to develop a hypothesis in this study. The Quantitative research method was applied in this study. The data were collected through a field survey. Partial Least Squire (PLS) based Structural Equation Modelling (SEM) was used to analyse collected data. Seven hypotheses were developed in this research. Among them, five hypotheses are supported, and two hypotheses are not supported. In addition, mediation test results are not reflected as positive. The findings are discussed in detail in the discussion and implementation part of this study. The clothing (RMG) industry of Bangladesh could implement the result to improve competitiveness
Graphene-based nanocomposites and their fabrication, mechanical properties and applications
Graphene, the thinnest two-dimensional atomic material, has immerged as a revolutionary material and sparked a flurry of research and innovation owing to its outstanding mechanical, electrical, optical and thermal properties as well as high specific surface area. Graphenebased materials and their composites possess promising applications in a wide range of fields such as sensors, actuators, electronics, biomedical aids and membranes. In this review paper, a critical and comprehensive review has been carried out on the synthesis process and mechanical properties of graphene and graphene-based nanocomposites. Firstly, the concept and structure of graphene materials are discussed then different synthesis techniques and their advantages and limitations have been reviewed. The addition of graphene and its derivatives in producing different polymer and metal-based nanocomposite as well as fabricating hybrid nanocomposite has been thoroughly reviewed. Almost all the papers show that the presence of graphene even at very low loadings can provide significant improvement to the final material. Besides, other parameters that affect the nanocomposite are thoroughly reviewed. Furthermore, the perspective application of graphene materials and its nanocomposite in different promising fields has been discussed
Synthesis, Characterization and Bioactivities of Some Novel Oxovanadium(IV) Glycinato Complexes
The novel oxovanadium(IV) complexes, [VIVO(GlyH)(Gly)]+ClO4 - .H2O (1), [VIVO(GlyH)(Gly)]+NO3 - .H2O (2), [VIVO(GlyH)(Gly)]+CH3COO- .H2O (3) were synthesized and characterized by FT-IR, UV-Vis and 1H NMR spectroscopic measurements. The cumulative spectroscopic assessment envisaged that, the complexes adopt a square pyramidal structure, in which the two glycine ligands coordinate to vanadium(IV) center in bidentate fashions conforming a homoleptic structure. The amino nitrogen and a carboxylato oxygen atom coordinate the vanadium(IV) center from both sides making a five members chelate by each side. All the complexes are stable in amorphous state and in aerobic and anaerobic solution. Significantly, all the complexes have the antifungal activities against Aspergillus niger and Penicillium notatum but ineffective against Candida tropicalis. No antibacterial activity was observed for the complexes against tested bacteria and unfortunately, they were found cytotoxic against brine shrimp bioassay
Integrated effects of marketing stimuli on customer loyalty in Palestine grocery supply-chain: does satisfaction perform mediating role?
Grocery stores are a crucial connection in the food delivery system and a fundamental component of the retail industry. Some grocery stores have worked with regional suppliers to benefit the community and the consumer. Palestinian market is uncommon because clients have connected what they manufacture and sell under particular circumstances. This study is, therefore, an integrated examination of the critical influencing factors on the marketing of food products in Palestine. A survey questionnaire was used. An organised, self-administered survey was used to acquire data, and analysis techniques were outlined using Structural Equation Modelling (SEM). According to the findings, relationship marketing and service quality are the crucial brand strategy factors influencing customers’ decisions to purchase groceries and showing how happy and devoted they are to grocery stores. The Palestinian government has greatly benefited from the results of this study of how consumers perceive essential factors that may be considered when formulating future regulations about food and other grocery items
Nuclear transparency and effective kaon-nucleon cross section from the A(e, e'K+) reaction
We have determined the transparency of the nuclear medium to kaons from
measurements on C, Cu, and Au targets.
The measurements were performed at the Jefferson Laboratory and span a range in
four-momentum-transfer squared Q=1.1 -- 3.0 GeV. The nuclear
transparency was defined as the ratio of measured kaon electroproduction cross
sections with respect to deuterium, (). We further
extracted the atomic number () dependence of the transparency as
parametrized by and, within a simple model assumption,
the in-medium effective kaon-nucleon cross sections. The effective cross
sections extracted from the electroproduction data are found to be smaller than
the free cross sections determined from kaon-nucleon scattering experiments,
and the parameter was found to be significantly larger than those
obtained from kaon-nucleus scattering. We have included similar comparisons
between pion- and proton-nucleon effective cross sections as determined from
electron scattering experiments, and pion-nucleus and proton-nucleus scattering
data.Comment: 7 pages, 5 figure
Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment
We present a simulation-based study using deep convolutional neural networks
(DCNNs) to identify neutrino interaction vertices in the MINERvA passive
targets region, and illustrate the application of domain adversarial neural
networks (DANNs) in this context. DANNs are designed to be trained in one
domain (simulated data) but tested in a second domain (physics data) and
utilize unlabeled data from the second domain so that during training only
features which are unable to discriminate between the domains are promoted.
MINERvA is a neutrino-nucleus scattering experiment using the NuMI beamline at
Fermilab. -dependent cross sections are an important part of the physics
program, and these measurements require vertex finding in complicated events.
To illustrate the impact of the DANN we used a modified set of simulation in
place of physics data during the training of the DANN and then used the label
of the modified simulation during the evaluation of the DANN. We find that deep
learning based methods offer significant advantages over our prior track-based
reconstruction for the task of vertex finding, and that DANNs are able to
improve the performance of deep networks by leveraging available unlabeled data
and by mitigating network performance degradation rooted in biases in the
physics models used for training.Comment: 41 page
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