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Singapore is positioning itself as a key operational excellence hub in Asia for manufacturing in order to compete with other neighbouring developing countries with advantages such as lower costs of production. Hence, there is clearly a need for an Operational Excellence Framework for companies in Singapore to be able to assess their capability level in terms of operations. This paper presents a study of existing frameworks such as The Shingo Model, LESAT, CMMI and SQA, analyzing the strengths and weaknesses and concluding with the key barriers of adoption for Small and Medium Enterprises (SMEs) in Singapore. Results point to a gap between what is currently available and what SMEs require, suggesting a need to develop a customized simple yet effective Operational Excellence Framework and assessment toolkit specifically for SMEs in Singapore.

A case-control study among Singapore Armed Forces' newly enlisted Servicemen was conducted to examine factors associated with male obesity. Four hundred and fifty-nine individuals from the Obese Basic Military Training program were selected as "cases" (average age: 19.5, body mass index: 30.4) and another 340 individuals were selected from the Normal Basic Military Training program as "controls" (average age: 19.3, body mass index: 21.4). Information such as family background, socioeconomic factors, and lifestyle practices were captured using facilitator-led questionnaires. Several variables were significantly associated with obesity after adjustments for possible confounders. These include childhood obesity (odds ratio [OR] = 2.06), less than an hour of exercise per day (OR = 2.97), Indian ethnicity (OR = 2.22), specific education backgrounds (especially that of Institute of Technical Education-OR = 2.75), father's employment at nonmanagerial/professional jobs (OR = 1.52), mother's employment at managerial/professional jobs (OR = 2.02), regular smoking (OR = 1.73) and alcohol consumption (OR = 2.26), 6 hours or less of sleep (OR = 3.73), obesity among family members (OR = 1.86 for mother; OR = 2.98 for siblings), parental history of diabetes mellitus (OR = 2.22 for father; OR = 2.70 for mother), and eating at inexpensive local food stalls (OR = 1.82). Our study found that a number of factors, ranging from personal and family backgrounds to lifestyle choices, were significantly associated with obesity among male youths.

This paper provides empirical estimates for the impact of R&D on economic growth in Singapore. The Cobb–Douglas based analysis found that R&D investment had a significant impact on total factor productivity performance in the last 20 years and established a long-term equilibrium relationship between R&D investments and TFP. However, compared to OECD countries, the impact of R&D on growth in Singapore is not as strong. To catch up with the developed nations in terms of R&D productivity not only requires increasing R&D intensity in Singapore but also more efficient exploitation of domestic R&D activity.