Experimenting with Supply Chain Learning (SCL): Supplier Diversity and Ethnic Minority Businesses

This paper reports on an innovative UK-based ‘Supply Chain Learning’ (SCL) initiative to encourage the corporate sector to consider supplier diversity in respect of ethnic minority businesses. This follows academic and policy interest in programmes to empower ethnic minority enterprises to achieve breakout to mainstream markets and business growth. The first phase of the initiative, entitled Supplier Development East Midlands (SDEM) is examined. By adopting an inter-organisational action learning approach, some of the key attributes of the programme are delineated, focusing on the recurrent action-reflection cycle taking place in a learning group comprising SDEM, LPOs (Large Purchasing Organisations) and small EMSs (Ethnic Minority Suppliers).     

Determining the Optimum Guarantee Period for a One-Life Retirement Annuity

Abstract

We consider a risk averse retiree from a defined contribution plan who decides to purchase a onelife annuity with a guarantee period. Given the retiree has a bequest motive, we focus on the problem of determining the optimum length of the guarantee period. Assuming the retiree’s bequest function is proportional to his or her utility function, we determine necessary and/or sufficient conditions under which the retiree would choose an annuity with (i) no guarantee period, (ii) the maximum guarantee period, or (iii) an intermediate guarantee period.     

Exchange-rate variability and industry trade flows between Malaysia and Japan

This research investigates the exchange-rate risk sensitivity of Malaysian bilateral trade flows with its important trading partner, Japan. To this end, bounds testing approach to co-integration is applied using industry level data over the monthly period 2000–2013. Findings suggest that above the one-third of the total co-integrated export (43.86%) and import (34.54%), industries experiences the ringgit/yen variability effect in the short run. However, this effect sustains in relatively less number of export (14.03%) and import (32.73%) industries in the long run. It is interesting to note that exchange-rate risk boosts trade flows in the majority of these affected industries.     

Inter-firm scalar linkage in India: A class within the small scale industry

Along with the growing industrial sector, functional complementarity between large and small scale enterprises has become a widely prevalent phenomenon. Expanding the base of the industrial production leads to division of processes where large and small scale units operate as complementary to each other. Such complementarity and division of labour between the different sized units results into cost minimization, and acceleration in growth of the manufacturing sector.However the extent and the pattern of functional complementarity (between large and small scale enterprises) is likely to be conditioned by market as well as institutional factors. Therefore, in order to examine the impact of interscale complementarity in terms of growth as well as of distribution of gains across large and small scale enterprises it is very important to learn about the nature of interfirm linkages and the process through which linkages get established. It is in this context, the present paper furnishes details based on a case study of Textile Machinery Parts Manufacturing (TMP) industry in a metropolitan city (Ahmedabad). The industry represented is constituted by a large number of small scale firms that are engaged in fabricating replacement parts for the users of machinery equipments (i.e. Textile Mills) who operate on a large scale. Owing to wide range of products, and in case of some parts higher frequency of replacement, the TMP industry, at least till recently, has sustained a large number of small firms.The major findings of the analysis are: (i) The incidence of inter-firm linkages is limited to about a third of the small scale firms; (ii) Among various forms of linkages the marketing linkages are the most predominant (iii) The linkage relationship has been a positive factor in determining the performance of the small scale firms; (iv) Personal contacts play an important role in inter-firm linkages, thus benefits of linkage relationship are mainly confined to a small social-group of industrialists; (v) While the small scale suppliers operate under a highly competitive market, the buyers often enjoy oligopsonist's advantage; hence the gains of competitive efficiency tend to favour the large scale sector.     

The Impact Of Business Intelligence Systems on an Organization’s Effectiveness: The Role of Metadata Quality From a Developing Country’S View

ABSTRACT

Business Intelligence (BI) systems are extensively used by large hotels in Jordan; however their effectiveness has not yet been researched. The aim of this research is to explore the relationships among definitional metadata quality, data quality metadata quality, navigational metadata quality, lineage metadata quality, perceived ease of use, perceived usefulness and system effectiveness in enhancing organizational effectiveness of five star hotels in Aqaba, Jordan. To test the research hypotheses, 225 usable responses containing 37 items were analyzed using structural equation modeling (SEM) and a Machine Learning technique. Results suggest that organizational effectiveness was directly and positively affected by perceived usefulness and BI systems effectiveness. Nevertheless, perceived usefulness did not impact BI systems effectiveness.     

Analysing the correlation between social network analysis measures and performance of students in social network-based engineering education

Social network-based engineering education (SNEE) is designed and implemented as a model of Education 3.0 paradigm. SNEE represents a new learning methodology, which is based on the concept of social networks and represents an extended model of project-led education. The concept of social networks was applied in the real-life experiment, considering two different dimensions: (1) to organize the education process as a social network-based process; and (2) to analyze the students’ interactions in the context of evaluation of the students learning performance. The objective of this paper is to present a new model for students evaluation based on their behavior during the course and its validation in comparison with the traditional model of students’ evaluation. The validation of the new evaluation model is made through an analysis of the correlation between social network analysis measures (degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, and average tie strength) and the grades obtained by students (grades for quality of work, grades for volume of work, grades for diversity of work, and final grades) in a social network-based engineering education. The main finding is that the obtained correlation results can be used to make the process of the students’ performance evaluation based on students interactions (behavior) analysis, to make the evaluation partially automatic, increasing the objectivity and productivity of teachers and allowing a more scalable process of evaluation. The results also contribute to the behavioural theory of learning performance evaluation. More specific findings related to the correlation analysis are: (1) the more different interactions a student had (degree centrality) and the more frequently the student was between the interaction paths of other students (betweenness centrality), the better was the quality of the work; (2) all five social network measures had a positive and strong correlation with the grade for volume of work and with the final grades; and (3) a student with high average tie strength had a higher grade for diversity of work than those with low ties.     

Model selection in univariate time series forecasting using discriminant analysis

When a large number of time series are to be forecast on a regular basis, as in large scale inventory management or production control, the appropriate choice of a forecast model is important as it has the potential for large cost savings through improved accuracy. A possible solution to this problem is to select one best forecast model for all the series in the dataset. Alternatively one may develop a rule that will select the best model for each series. Fildes (1989) calls the former an aggregate selection rule and the latter an individual selection rule. In this paper we develop an individual selection rule using discriminant analysis and compare its performance to aggregate selection for the quarterly series of the M-Competition data. A number of forecast accuracy measures are used for the evaluation and confidence intervals for them are constructed using bootstrapping. The results indicate that the individual selection rule based on discriminant scores is more accurate, and sometimes significantly so, than any aggregate selection method.     

The Impact of Single Stock Futures on Market Efficiency and Volatility: A Dynamic CAPM Approach

The concerns regarding regulations of futures markets and their destabilizing ability are unresolved in both developed and developing markets. Following stringent regulations of single stock futures (SSFs) for resumption episode after financial crises, this study addresses this concern and investigates the destabilizing impact of SSFs on the underlying stocks in an emerging economy using data of companies listed in the Karachi Stock Exchange between 1999 and 2008. Specifically, the study explores whether SSFs have caused a simultaneous increase in the volatility and operational efficiency of their underlying spot market counterparts. The results reported in the study show that the introduction of SSFs has no significant impact on market efficiency and volatility of SSFs underlying stocks and non-SSFs stocks. The results affirm that SSFs have, at least, no destabilizing impact on the underlying stocks.