Editorial Information 2018

Editorial Information 2018

Principal-agent problems in implementation of Ghana’s health insurance scheme

<p>Principal-agent relationship exists between health service providers and their authority and clients. It asserts that health service providers as ‘imperfect agents’ of the authority and clients will take actions that aim to maximise profits at the expense of authority and clients (principal). The situation is possible when reimbursement is based on fee-for-service or a diagnosis-related groups. It looks at relationships between health service providers as agents and health insurance authority, and clients as principals in areas of provision of health services, supply of drugs, medicines and reimbursement. Results showed the private health service providers prescribed more drugs and medicines for clients towards profit maximisation (agency) than their public counterparts. Also, it was found that the public health service providers continued to provide health services and drugs despite health insurance authority indebtedness to them exhibiting more stewardship towards health insurance authority. It recommends strict regulations in tariffs/vetting claims and prompt reimbursement.</p>

Modeling and optimization of multi-layer aggregate production planning

<p>Aggregate production planning has attracted the attention of researchers for quite a long time now; and the continued researches depict the significance and scope for improvement in this arena. Here, a multi-product, multi-level and multi-period model has been formulated to identify the required aggregate plan for meeting the forecast demand, by regulating production rates, inventory, workforce, various production costs, and other controllable variables. Several new contributing factors, such as costs related to material handling, raw material inventory and worker training have been included in the objective function and constraint equations to make the model more realistic. A case study has been presented for a cosmetics and toiletries manufacturer in Bangladesh. Eventually, the problem has been solved using Genetic Algorithm and Particle Swarm Optimization approach. The solution illustrates that the model can be applied in a real world scenario to enhance productivity and profitability.</p>

The Brazilian ocean freight oscillation: The experts’ explanation to the USA, Europe and China trade

<p>This study aimed to identify the variables that contribute to the oscillation of the international ocean freight of the Brazilian trade of containerized cargoes. The ocean freight from and to East Coast of United States, Northern Europe and China to Brazil was studied by a qualitative approach through in-depth interviews with a panel of seven experts in charge of pricing the international ocean freight in the largest international shipping companies operating in Brazil. After a first round with the experts, a table that tried to capture the causal relationship among variables and their influence in Brazilian ocean freight was developed. In a second round of interviews, the final table was submitted to the judgment of the experts. Considering the experts’ opinion on the trade routes studied, it was noticed that the relationship between supply and demand with ocean freight is the variable that influences freight rates in Brazil’s trade the most. Other variables such as vessels capacity, operating costs and competitors are among the variables that experts have identified as those that most contribute in Brazilian ocean freight oscillation.</p>

Rudimentary causes and impacts of supply chain risks in Sub-Saharan Africa

<p>Identification of the causes of supply chain risks is a logical step towards its effective management. The purpose of this study is to explore the causes of supply chain risks, their impacts, and the mitigating strategies used among the manufacturing firms in Nigeria. An exploratory qualitative multiple case research methodology combined with the quantitative content analysis is used for this study. A sample of ten manufacturing firms cutting across three different sub-sectors (Pharmaceutical &amp; Health, Food &amp; Beverage, and Conglomerate) was chosen for the study. Partial and complete open-ended questions in the interview guide were used for the interviews conducted among the respondents. The study revealed the common causes of supply chain risks in manufacturing firms in Nigeria which include; transportation delays, variation in raw material prices and quantities, unexpected customer demands, and constant power outages.</p>