Developing a supplier selection system through integrating fuzzy AHP and fuzzy DEA: a case study on an auto lighting system company in Taiwan

Supplier selection plays a very important role in supply chain management. This study intends to develop a novel performance evaluation method, which integrates both fuzzy analytical hierarchy process (AHP) method and fuzzy data envelopment analysis (DEA) for assisting organisations to make the supplier selection decision. Fuzzy AHP method is first applied to find the indicators’ weights through expert questionnaire survey. Then, these weights are integrated with fuzzy DEA. We use α -cut set and extension principle of fuzzy set theory to simplify the fuzzy DEA as a pair of traditional DEA model. Finally, fuzzy ranking using maximising and minimising set method is able to rank the evaluation samples. A case study on an internationally well-known auto lighting OEM company shows that the proposed method is very suitable for practical applications.     

Evaluation of safety stock methods in multilevel material requirements planning (MRP) systems

This paper evaluates alternative methods of establishing the safety stock level taking into consideration of historical measures of forecasting accuracy and the needs for master production scheduling and material requirement planning under a rolling time horizon. A computer model is used to simulate the forecasting, master production scheduling and material planning activities in a company that produces to stock and the production activities are managed by multilevel MRP systems. The simulation output is analysed to evaluate the impact of safety stock methods on MRP system performance. The result of the study shows that using safety stock can help to reduce total cost, schedule instability and improve service level in the MRP systems. Guidelines are developed to help managers select methods to determine safety stock in MRP system operations.     

Assembly block storage location assignment at a shipyard: a case of Hyundai Heavy Industries

It is not a trivial issue how to manage assembly blocks at a shipyard. Based on the project experience in Hyundai Heavy Industries, currently the largest shipbuilding company in the world and the leader in the Korean merchant shipbuilding industry, this study points out the difficulties on the block stockyard operations, formalises the assembly block storage location assignment problem, and develops the assembly block storage location assignment algorithm, the purpose of which is to reduce the number of unproductive block moves. Through simulation experiments for various situations, this study demonstrates the usefulness of the assembly block storage location assignment algorithm. In addition, this study examines the impacts of block move sequence rules and of block stockyard layouts on the block stockyard operations.     

Manufacturing bill-of-material planning

The bill-of-material BOM in the machine tool industry takes two different forms in design and manufacturing functions: Engineering BOM E BOM , which is used by the design engineer to represent designed product structure; and manufacturing BOM M BOM , which is used by MRPII system for MRP explosion. The designer constructs the E BOM after the product has been designed. Next, the E BOM is transformed into the M BOM by considering assembly sequence and constraints. Constructing a M BOM simply involves compressing the E BOM into a three-level M BOM. Planning of a M BOM still depends primarily on the experience input of a manufacturing engineer and is performed manually. This trial and error and time consuming approach creates an inconsistent method for planning the M BOM. Therefore, in this study, a three-stage M BOM planning method is developed. Stage one plans the initial M BOM, stage two improves the M BOM and stage three tunes the M BOM. Concepts and algorithms of each stage are highlighted in this study. Moreover, an illustration is presented to demonstrate the feasibility of M BOM planning.     

Aspects of quality . . . and world domination!

Training, learning and development tend to be regarded as central to the success of every organization and the nation. However, not all organizations are able or willing to invest resources in such processes. The paper presents a view that training, learning and development occur as a consequence of successful persuasive actions in a chain of talk, which draw on the discursive and rhetorical resources of an emerging learning movement. Utilizing the findings from an examination of data from the UK Department of Education and Skills-sponsored National Training Award winners, the paper provides an employment of actor-network theory and the sociology of translation to show how some organizations make the case for training, learning and development as a virtuous endeavour. It concludes by suggesting that what is needed is a more detailed understanding of how the case for the adoption of training, learning and development, or not, within organizations is made meaningful.     

Liked on Facebook,liked for real?: Nonprofits' online popularity and financial performance

Despite the increasing strategic importance of online popularity, there remain uncertainties about the direct link between nonprofits' online popularity and organizational outcomes and performance. This study examines the relationship between the number of “likes” on a nonprofit arts organization's Facebook page and its financial performance, focusing on how online popularity may reduce the information asymmetry between an organization and its stakeholders. The results show a positive correlation between the number of “likes” and nonprofits' charitable contributions and earned income while controlling for various organizational characteristics, including size. The findings also reveal that the correlation is twice as strong for earned income as for donations.     

西晋末期王浚集团、张轨集团兴衰之比较

本文选择分析王浚集团、张轨集团两个汉族地方武装势力 ,比较它们不同的形成、发展过程 ,探讨它们不同命运的原因 ,进而从一个侧面加深对西晋末期历史的认识     

Nonparametric testing for long-horizon predictability with persistent covariates

We propose a testing procedure for long-horizon predictability via kernel-based nonparametric estimators of long-run covariances between multiperiod returns and persistent covariates. Asymptotic properties of the proposed tests are studied. As for implementation of the test, sieve bootstrap methods are employed to obtain reasonable approximation to the sample distribution of the test statistics. Monte Carlo simulations are conducted to verify the theoretical conjecture. Empirical analysis, using US monthly data from 1929 to 2011, are presented for testing stock return predictability of some forecasting financial variables. Long-term interest rates, unlike default spreads or price-earning ration, are found to show some forecasting power.     

Estimating the probability of simultaneous rainfall extremes within a region: a spatial approach

In this paper we investigate the impact of model mis-specification, in terms of the dependence structure in the extremes of a spatial process, on the estimation of key quantities that are of interest to hydrologists and engineers. For example, it is often the case that severe flooding occurs as a result of the observation of rainfall extremes at several locations in a region simultaneously. Thus, practitioners might be interested in estimates of the joint exceedance probability of some high levels across these locations. It is likely that there will be spatial dependence present between the extremes, and this should be properly accounted for when estimating such probabilities. We compare the use of standard models from the geostatistics literature with max-stables models from extreme value theory. We find that, in some situations, using an incorrect spatial model for our extremes results in a significant under-estimation of these probabilities which – in flood defence terms – could lead to substantial under-protection.