Identification of Demand through Statistical Distribution Modeling for Improved Demand Forecasting

Demand functions for goods are generally cyclical in nature with characteristics such as trend or stochasticity. Most existing demand forecasting techniques in literature are designed to manage and forecast this type of demand functions. However, if the demand function is lumpy in nature, then the general demand forecasting techniques may fail given the unusual characteristics of the function. Proper identification of the underlying demand function and using the most appropriate forecasting technique becomes critical. In this paper, we will attempt to explore the key characteristics of the different types of demand function and relate them to known statistical distributions. By fitting statistical distributions to actual past demand data, we are then able to identify the correct demand functions, so that the the most appropriate forecasting technique can be applied to obtain improved forecasting results. We applied the methodology to a real case study to show the reduction in forecasting errors obtained

A Greedy Double Swap Heuristic for Nurse Scheduling

One of the key challenges of nurse scheduling problem (NSP) is the number of constraints placed on preparing the timetable, both from the regulatory requirements as well as the patients' demand for the appropriate nursing care specialists. In addition, the preferences of the nursing staffs related to their work schedules add another dimension of complexity. Most solutions proposed for solving nurse scheduling involve the use of mathematical programming and generally considers only the hard constraints. However, the psychological needs of the nurses are ignored and this resulted in subsequent interventions by the nursing staffs to remedy any deficiency and often results in last minute changes to the schedule. In this paper, we present a staff preference optimization framework which is solved with a greedy double swap heuristic. The heuristic yields good performance in speed at solving the problem. The heuristic is simple and we will demonstrate its performance by implementing it on open source spreadsheet software

BANKING ON PERFORMANCE: EMPLOYEE ENHANCEMENT STRATEGIES IN MALAYSIA'S MERGERS AND ACQUISITIONS LANDSCAPE

This study analyses how communication, training and development, and organisational culture affect bank employees' post-merger and acquisition (M&A) performance. The study used convenience sampling to gather data from Malaysian investment banking sector employees. A total of 257 responses provided the data for this study. The sampling locations included investment banks in Malaysia that have undergone M&A, such as Aseambankers, Maybank Securities, RHB, OSK, Affin, Hwang DBS, ECM Libra, and Kenanga Investment Bank. This study's results show that all three predictor variables (Communication, Training and Development, and Organizational Culture) positively influence the Outcome variable (Employee Performance), albeit to varying degrees. Communication emerges as the most dominant factor, followed closely by Organizational Culture, while Training and Development's influence, although positive, is comparatively subdued. This underscores the crucial role these strategies play in determining employee performance outcomes in the mergers and acquisitions sphere of Malaysia. Therefore, this study can help the banking sector boost employee morale, job satisfaction, and productivity during transitions.  Article visualizations

Data-Driven Dietary Patterns, Nutrient Intake and Body Weight Status in a Cross-Section of Singaporean Children Aged 6–12 Years

Pattern analysis of children’s diet may provide insights into chronic disease risk in adolescence and adulthood. This study aimed to assess dietary patterns of young Singaporean children using cluster analysis. An existing dataset included 15,820 items consumed by 561 participants (aged 6–12 years) over 2 days of dietary recall. Thirty-seven food groups were defined and expressed as a percentage contribution of total energy. Dietary patterns were identified using k-means cluster analysis. Three clusters were identified, “Western”, “Convenience” and “Local/hawker”, none of which were defined by more prudent dietary choices. The “Convenience” cluster group had the lowest total energy intake (mean 85.8 ± SD 25.3 of Average Requirement for Energy) compared to the other groups (95.4 ± 25.9 for “Western” and 93.4 ± 25.3 for “Local/hawker”, p < 0.001) but also had the lowest calcium intake (66.3 ± 34.7 of Recommended Dietary Allowance), similar to intake in the “Local/hawker” group (69.5 ± 38.9) but less than the “Western” group (82.8 ± 36.1, p < 0.001). These findings highlight the need for longitudinal analysis of dietary habit in younger Singaporeans in order to better define public health messaging targeted at reducing risk of major noncommunicable disease

US Presidential election 2012 prediction using census corrected Twitter model

Unpublished Reports</p