International Journal of Business Forecasting and Marketing Intelligence http://www.inderscience.com/browse/index.php?journalID=156&year=2010&vol=1&issue=3/4 Inderscience Publishers Ltd en-uk International Journal of Business Forecasting and Marketing Intelligence 1744-6635 1744-6643 © 2010 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijbfmi_scoverijbfmi.jpg http://www.inderscience.com/browse/index.php?journalID=156&year=2010&vol=1&issue=3/4 http://www.inderscience.com/link.php?id=36004 Genetic algorithms (GAs) have been used in the clustering subject. Also, a clustering ensemble as one acceptable clustering method combines the results of multiple clustering methods on a given dataset and creates final clustering on the dataset. In this paper, genetic algorithm base on clustering ensemble (GACE) is introduced for finding optimal clusters. The most important property of our method is the ability to extract the number of clusters. With this ability, the need for data examination is removed, and then solving related problems will not be time consuming. GACE is applied to eight series of databases. Experimental results were compared with other four clustering methods. Data envelopment analysis (DEA) is used to compare methods. The results of DEA indicate that GACE is the best method. The four methods are co-association function and average link (CAL), co-association function and K-means (CK), hypergraph-partitioning algorithm (HGPA) and cluster-based similarity partitioning (CSPA). Genetic algorithm-based clustering ensemble: determination number of clusters
Mehdi Mohammadi, Ali Azadeh, Morteza Saberi, Amir Azaron
International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 201 - 216
Genetic algorithms (GAs) have been used in the clustering subject. Also, a clustering ensemble as one acceptable clustering method combines the results of multiple clustering methods on a given dataset and creates final clustering on the dataset. In this paper, genetic algorithm base on clustering ensemble (GACE) is introduced for finding optimal clusters. The most important property of our method is the ability to extract the number of clusters. With this ability, the need for data examination is removed, and then solving related problems will not be time consuming. GACE is applied to eight series of databases. Experimental results were compared with other four clustering methods. Data envelopment analysis (DEA) is used to compare methods. The results of DEA indicate that GACE is the best method. The four methods are co-association function and average link (CAL), co-association function and K-means (CK), hypergraph-partitioning algorithm (HGPA) and cluster-based similarity partitioning (CSPA).

]]> 10.1504/IJBFMI.2010.036004 International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 201 - 216 Mehdi Mohammadi Ali Azadeh Morteza Saberi Amir Azaron Department of Computer Engineering, Iran University of Science and Technology, University Road, Hengam Street, Resalat Square, Tehran, Iran. ' Department of Industrial Engineering, Department of Engineering Optimization Research, Research Institute of Energy Management and Planning, Center of Excellence for Intelligent Experimental Mechanics, Faculty of Engineering, University of Tehran, P.O. Box 11365-4563, Iran. ' Department of Industrial Engineering, University of Tafresh, Tafresh, Iran; Institute for Digital Ecosystems & Business Intelligence, CBS, Curtin University of Technology, GPO Box U1987, Perth, WA 6845, Australia. ' Department of Financial Engineering and Engineering Management, School of Science and Engineering, Reykjavik University, Reykjavik, Iceland genetic algorithms GAs clustering ensembles data envelopment analysis DEA co-association function average link K-means hypergraph-partitioning algorithms HGPA cluster-based similarity partitioning CSPA. 2010-10-12T23:20:50-05:00 1 3/4 201 216 2010-10-12T23:20:50-05:00 http://www.inderscience.com/link.php?id=36005 Understanding the current business cycle of a nation is essential for individuals, enterprises, and the government in order to make appropriate strategic decisions and take advantage of business opportunities. At a specific period of economic activities, the business cycle develops moderately and may lead to negative growth or economic recession when the economic activity expands to the peak. Business cycle functions as an indicator for the economic development of a nation and thus, it is an important tool for decision-makers. For example, the situation of the business cycle in Taiwan is acquired from the cyclical indicators, economic monitoring indicator, and reference dates of business cycles in Taiwan periodically announced by the Council of Economic Planning and Development (CEPD). This information provides a reference for individuals and investors to make decisions. Since business cycle is fuzzy in nature, this study uses the fuzzy regression analysis method to establish a regression model in order to provide a reference for enterprises and decision-makers to make the right investments. Strategic prediction of the business cycle using the fuzzy regression model: a study of the Council of Economic Planning and Development in Taiwan
Lisa Y. Chen, Bahaudin G. Mujtaba
International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 217 - 233
Understanding the current business cycle of a nation is essential for individuals, enterprises, and the government in order to make appropriate strategic decisions and take advantage of business opportunities. At a specific period of economic activities, the business cycle develops moderately and may lead to negative growth or economic recession when the economic activity expands to the peak. Business cycle functions as an indicator for the economic development of a nation and thus, it is an important tool for decision-makers. For example, the situation of the business cycle in Taiwan is acquired from the cyclical indicators, economic monitoring indicator, and reference dates of business cycles in Taiwan periodically announced by the Council of Economic Planning and Development (CEPD). This information provides a reference for individuals and investors to make decisions. Since business cycle is fuzzy in nature, this study uses the fuzzy regression analysis method to establish a regression model in order to provide a reference for enterprises and decision-makers to make the right investments.

]]> 10.1504/IJBFMI.2010.036005 International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 217 - 233 Lisa Y. Chen Bahaudin G. Mujtaba Department of Information Management, I-Shou University, 1, Sec. 1 Syuecheng Road, Dashu Township, Kaohsiung County 840, Taiwan. ' H. Wayne Huizenga School of Business and Entrepreneurship, Nova Southeastern University, 3301 College Avenue, Fort Lauderdale FL 33314-7796, USA strategic decisions economic activities business cycles economic monitoring indicators fuzzy regression Taiwan regression models. 2010-10-12T23:20:50-05:00 1 3/4 217 233 2010-10-12T23:20:50-05:00 http://www.inderscience.com/link.php?id=36006 In September 2001, Malaysia has officially launched the world's first smart identity card, known as MyKad. The MyKad utilises the security enhanced 64K microprocessor chip and biometric technology, ensuring a high level of accuracy, enabling more than 27.73 million Malaysians to transact conveniently and securely with the government and private sectors through the use of a single smartcard. A modified technology acceptance model (TAM) was used in this study to predict the Malaysians' acceptance of using MyKad as an e-commerce tool in Malaysia. The sample for this study consisted of MyKad owners who are able to support themselves financially. Using a survey method, data were collected from 351 respondents in three designated zones in Peninsular Malaysia (northern, central and southern zone). Results showed that the modified TAM was found to be useful in explaining the Malaysians' acceptance of using MyKad as an e-commerce tool. Awareness of MyKad as an e-commerce tool in Malaysia
Farrah Fadil, Kok-Wai Chew, Hezlin Harris
International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 234 - 246
In September 2001, Malaysia has officially launched the world's first smart identity card, known as MyKad. The MyKad utilises the security enhanced 64K microprocessor chip and biometric technology, ensuring a high level of accuracy, enabling more than 27.73 million Malaysians to transact conveniently and securely with the government and private sectors through the use of a single smartcard. A modified technology acceptance model (TAM) was used in this study to predict the Malaysians' acceptance of using MyKad as an e-commerce tool in Malaysia. The sample for this study consisted of MyKad owners who are able to support themselves financially. Using a survey method, data were collected from 351 respondents in three designated zones in Peninsular Malaysia (northern, central and southern zone). Results showed that the modified TAM was found to be useful in explaining the Malaysians' acceptance of using MyKad as an e-commerce tool.

]]> 10.1504/IJBFMI.2010.036006 International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 234 - 246 Farrah Fadil Kok-Wai Chew Hezlin Harris Faculty of Management, Multimedia University, 63100 Cyberjaya, Selangor, Malaysia. ' Faculty of Management, Multimedia University, 63100 Cyberjaya, Selangor, Malaysia. ' Faculty of Management, Multimedia University, 63100 Cyberjaya, Selangor, Malaysia MyKad smart cards national identification cards awareness technology acceptance model TAM Malaysia e-commerce electronic commerce identity cards security biometrics. 2010-10-12T23:20:50-05:00 1 3/4 234 246 2010-10-12T23:20:50-05:00 http://www.inderscience.com/link.php?id=36007 This study examines the influence of equity carve-out (ECO) announcements on the share prices of parent firms using a hand-collected sample of 64 ECO announcements made within the time period from year 2000 to year 2008. It is found that ECOs have a positive impact on parent firms' share prices around the announcement period. This suggests that investors in Malaysian stock market welcome ECOs as good news. The results of the entire sample of this study are generally consistent with other researchers' findings. However, using the subsamples grouped by the ultimate consequence of the proposed listing in the ECO announcements, the market responses of two subgroups are not the same. The cumulate average abnormal returns of a subsample, which consists of the parent firms that ultimately carved out their subsidiaries, are significant positive before the announcement and then decrease soon after the announcement date. On the other hand, the uptrend of the cumulative average abnormal returns of another subgroup, which consists of parent firms that failed to carve out their subsidiaries, continues for a longer period after the announcement date. The market response of equity carve-out announcements in Malaysian stock market
Ken Chin-Chong Lee
International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 247 - 261
This study examines the influence of equity carve-out (ECO) announcements on the share prices of parent firms using a hand-collected sample of 64 ECO announcements made within the time period from year 2000 to year 2008. It is found that ECOs have a positive impact on parent firms' share prices around the announcement period. This suggests that investors in Malaysian stock market welcome ECOs as good news. The results of the entire sample of this study are generally consistent with other researchers' findings. However, using the subsamples grouped by the ultimate consequence of the proposed listing in the ECO announcements, the market responses of two subgroups are not the same. The cumulate average abnormal returns of a subsample, which consists of the parent firms that ultimately carved out their subsidiaries, are significant positive before the announcement and then decrease soon after the announcement date. On the other hand, the uptrend of the cumulative average abnormal returns of another subgroup, which consists of parent firms that failed to carve out their subsidiaries, continues for a longer period after the announcement date.

]]> 10.1504/IJBFMI.2010.036007 International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 247 - 261 Ken Chin-Chong Lee Faculty of Business and Accountancy, INTI International University, Persiaran Perdana BBN, Putra Nilai, 71800 Nilai, Negeri Sembilan, Malaysia equity carve-out announcements ECO event study market model method Malaysia market response Malaysian stock market share prices parent firms subsidiaries. 2010-10-12T23:20:50-05:00 1 3/4 247 261 2010-10-12T23:20:50-05:00 http://www.inderscience.com/link.php?id=36008 The purpose of this study is to examine the short- and long-run relationships between stock market performance and economic growth for six emerging countries (Malaysia, Turkey, Mexico, Korea, India, and Brazil). To this end, the bounds testing approach to cointegration and Granger and Toda-Yamamoto causality tests are conducted for quarterly data. The results imply that there is a close relationship between stock market performance and economic growth in the long-run and that stock market performance is an impetus for economic growth in the short-run. The key finding of this study is that the relationship between stock market performance and economic growth is sensitive to the size of stock market. Stock market and economic growth nexus in emerging markets: cointegration and causality analysis
Ekrem Erdem, Onur Gozbasi, M. Fatih Ilgun, Saban Nazlioglu
International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 262 - 274
The purpose of this study is to examine the short- and long-run relationships between stock market performance and economic growth for six emerging countries (Malaysia, Turkey, Mexico, Korea, India, and Brazil). To this end, the bounds testing approach to cointegration and Granger and Toda-Yamamoto causality tests are conducted for quarterly data. The results imply that there is a close relationship between stock market performance and economic growth in the long-run and that stock market performance is an impetus for economic growth in the short-run. The key finding of this study is that the relationship between stock market performance and economic growth is sensitive to the size of stock market.

]]> 10.1504/IJBFMI.2010.036008 International Journal of Business Forecasting and Marketing Intelligence, Vol. 1, No. 3/4 (2010) pp. 262 - 274 Ekrem Erdem Onur Gozbasi M. Fatih Ilgun Saban Nazlioglu Department of Economics, Erciyes University, 38039, Kayseri, Turkey. ' Department of Business, Erciyes University, 38039, Kayseri, Turkey. ' Department of Public Finance, Erciyes University, 38039, Kayseri, Turkey. ' Institute of Social Sciences, Erciyes University, 38039, Kayseri, Turkey stock markets economic growth emerging markets cointegration causality short term long term stock market performance Malaysia Turkey Mexico Korea India Brazil stock market size. 2010-10-12T23:20:50-05:00 1 3/4 262 274 2010-10-12T23:20:50-05:00