Defining the business ecosystem of peer-to-peer electricity trading

Purpose: The purpose of this paper is to introduce the value proposition and structure of the business ecosystem of peer-to-peer electricity trading through a future oriented approach. Design/Methodology/Approach: This study follows a qualitative approach. It conducts conceptual analyses by utilizing previously validated tools in similar contexts. First, different views on business ecosystems are introduced and an argument is made to justify an ecosystem perspective for peerto-peer electricity trading. Second, the value proposition of the peer-to-peer electricity trading ecosystem is identified by utilising a meta-model which consists of four elements: end customer value, business value (shareholder value), collaborative value (business value to the supply chain) and societal value (value creation in the supply chain and control of negative externalities). Third, based on the structural view of business ecosystems, the study identifies actors, positions, links, and activities in the traditional electricity trading. And last, (structural) changes of the ecosystem for peer-to-peer electricity trading are discussed. Findings: This paper elaborates the business ecosystem of peer-to-peer electricity trading and highlights the structural changes it imposes to the status quo. Practical and social implications: The ecosystem construct adds insights into actors’ ecosystem strategy regarding their business models for peer-to-peer electricity trading as well as into the governance of this type of trading. It provides a comprehensive view for policy makers. It enhances the research designs in detailed aspects of the peer-to-peer electricity trading by providing a wide lense. Originality/Value: The identified business ecosystem of peer-to-peer electricity trading provides a comprehensive, multi-stakeholder perspective to incorporate complexities and include externalities

How Smart Cities Transform Operations Models: A New Research Agenda for Operations Management in the Digital Economy

The notion of smart cities is growing in prominence in the digital economy. The integration of urban infrastructures with information and communication technologies (ICT) enables the development of new operations models. Digitised infrastructures offer opportunities for public and private organisations to design and deliver more customer-centric products or services, particularly for those that require geographical proximity with consumers in the O2O (online to offline) context. A framework is developed and used to analyse three case examples. These cases illustrate the emergence of new operations models and, demonstrate how smart cities are re-defining the characteristics of operations models around their scalability, analytical output and, connectivity. We also explore the feasibility, vulnerability and acceptability of each new operation. This paper contributes to our understanding of how smart cities can potentially transform operational models, and sets out a research agenda for operations management in smart cities in the digital economy

Small business economics: A perspective from The Netherlands

In the analysis of economic phenomena either within or across industries there is room for integrating the role of small business. This contribution can be made by aggregation or generalization of the findings at the meso level, which again are partly based upon analyses at the micro level. The Netherlands has a long history in macro model building. A recent discussion among Dutch macro-economists considered the future of econometric model building at the macro level, and considered how best to improve this model building. The explicit integration of scale effects, however, was not mentioned. I am convinced that improvements in this respect are possible. In particular, I have in mind the role which small businesses play in certain areas such as wage structure, employment or investments. The dissection of macro prognoses into a small business component and a remaining component is a traditional practice in The Netherlands.1 Finally, there is much concern in The Netherlands for the calculation of regulatory effects, decomposed into effects for small and large businesses. If anywhere in the world there is a solid foundation for studying scale effects in both macro and sectoral models, it most certainly has been in The Netherlands. There is a strong tradition of macro-econometric model building; groups of econometricians specialized in small business research exist; Dutch policymakers show concern and the required research apparatus is available

Micronutrient fortification of food and its impact on woman and child health: A systematic review

Background: Vitamins and minerals are essential for growth and metabolism. The World Health Organization estimates that more than 2 billion people are deficient in key vitamins and minerals. Groups most vulnerable to these micronutrient deficiencies are pregnant and lactating women and young children, given their increased demands. Food fortification is one of the strategies that has been used safely and effectively to prevent vitamin and mineral deficiencies.Methods: A comprehensive search was done to identify all available evidence for the impact of fortification interventions. Studies were included if food was fortified with a single, dual or multiple micronutrients and impact of fortification was analyzed on the health outcomes and relevant biochemical indicators of women and children. We performed a meta-analysis of outcomes using Review Manager Software version 5.1.Results: Our systematic review identified 201 studies that we reviewed for outcomes of relevance. Fortification for children showed significant impacts on increasing serum micronutrient concentrations. Hematologic markers also improved, including hemoglobin concentrations, which showed a significant rise when food was fortified with vitamin A, iron and multiple micronutrients. Fortification with zinc had no significant adverse impact on hemoglobin levels. Multiple micronutrient fortification showed non-significant impacts on height for age, weight for age and weight for height Z-scores, although they showed positive trends. The results for fortification in women showed that calcium and vitamin D fortification had significant impacts in the post-menopausal age group. Iron fortification led to a significant increase in serum ferritin and hemoglobin levels in women of reproductive age and pregnant women. Folate fortification significantly reduced the incidence of congenital abnormalities like neural tube defects without increasing the incidence of twinning. The number of studies pooled for zinc and multiple micronutrients for women were few, though the evidence suggested benefit. There was a dearth of evidence for the impact of fortification strategies on morbidity and mortality outcomes in women and children.Conclusion: Fortification is potentially an effective strategy but evidence from the developing world is scarce. Programs need to assess the direct impact of fortification on morbidity and mortality

'Healthy living' and sulphonylurea therapy have different effects on glucose tolerance and risk factors for vascular disease in subjects with impaired glucose tolerance.

This study was undertaken to determine whether impaired glucose tolerance and associated risk factors for cardiovascular disease can be improved with 'healthy living' by diet and exercise or with sulphonylurea therapy. Patients were recruited by screening subjects with either a family history of type II diabetes, previous gestational diabetes, or a previously raised plasma glucose (5.6-6.6 mmol/l). Impaired glucose tolerance was defined as hyperglycaemia on two separate tests, an achieved glucose level after a glucose infusion test above the 90th percentile of an age-matched normal population (> 9.3 mmol/l) or a fasting plasma glucose above the 95th percentile (> 5.6 mmol/l). Thirty-seven subjects with impaired glucose tolerance were entered into a randomized, prospective study for 6 months with allocations to healthy living or double blind to sulphonylurea (gliclazide 40 mg twice daily) or placebo tablets. The study took place in an out-patient setting, with three times weekly exercise sessions at a Sports Centre. After 6 months the placebo group showed no change in plasma glucose, cholesterol and blood pressure. The subjects receiving gliclazide showed improved glucose levels (mean fasting plasma glucose levels fell from 5.8 to 5.1 mmol/l, p < 0.05) but no significant change in plasma cholesterol or blood pressure. The healthy living group, after exclusion of four non-compliant subjects, showed no change in glucose levels, but a decreased systolic blood pressure (fall in mean from 124 to 116 mmHg, p < 0.05) and plasma cholesterol levels (fall in mean from 5.2 to 4.5 mmol/l, p < 0.01). with an increase in HDL:LDL ratio (rise in mean from 0.39 to 0.46, p < 0.05). Subjects with impaired glucose tolerance may benefit in different ways from gliclazide and healthy living. The metabolic responses to each therapy may help to decrease the risk of developing diabetes and cardiovascular disease

Detecting false messages in the smartphone fault reporting system

The emergence of the Internet of Things (IoT) in Smart City allows mobile application developers to develop reporting services with an aim for local citizens to interact with municipalities regarding city issues in an efficient manner. However, the credibility of the messages sent rise as a great challenge when users intentionally send false reports through the application. In this research, an evidence detection framework is developed and divided into three parts that are a data source, IoT device’s false text classification engine and output. Text-oriented digital evidence from an IoT mobile reporting service is analyzed to identify suitable text classifier and to build this framework. The Agile model that consists of define, design, build and test is used for the development of the false text classification engine. Focus given on text-based data that does not include encrypted messages. Our proposed framework able to achieve 97% of accuracy and showed the highest detection rate using SVM compared to other classifiers. The result shows that the proposed framework is able to aid digital forensic evidence experts in their initial investigation on detecting false report of a mobile reporting service application in the IoT environment