Stephen Nabareseh

Tracking progress of African Peer Review Mechanism (APRM) using fuzzy comprehensive evaluation method

Purpose – The purpose of this paper is to propose a new assessment methodology for the African Peer Review Mechanism (APRM) using fuzzy comprehensive evaluation method (FCEM) and the Delphi technique. The proposed approach by its design simplifies the review processes and also quantifies the outcome of the assessment result for easier interpretation and benchmarking among member countries. The proposed hybrid method demonstrates how the subjective APRM thematic areas and their objectives can be efficiently tracked country by country while addressing the key identified challenges. Design/methodology/approach – Using a numerical example, a demonstration of how the APRM assessment could be carried is shown using the FCEM and the Delphi method. The APRMs own thematic areas are used as the evaluation factors and the weights are assigned using Delphi technique. A novel remark set is constructed to linguistically describe the performance of a country against each or all of the thematic areas. Then in line with ...

Selecting start-up businesses in a public Venture capital financing using Fuzzy PROMETHEE

Abstract Public Venture Capital financing often fail rigorous scrutiny in their selection of high-potential start-ups as compared to Private Venture capital. In some developing countries, decision making on final selection for financial support of early stage but high potential Small and Medium sized Enterprises (SMEs) are often ‘clouded’ by several factors including consideration of political party affiliations. This results in low capital recovery rate and a mischance in choosing deserving start-ups. This paper applies Fuzzy Preference Ranking Organization METHod for Enrichment Evaluation (Fuzzy PROMETHEE) method to evaluate and select early-stage but high potential start-up businesses in a government high priority area such as in Information and Communications Technology. A numerical example with pre-defined linguistic terms parameterized by triangular fuzzy numbers is provided. The framework could serve as a useful tool for decision makers in scrutinizing selection of start-ups in other government priority areas.

Fuzzy VIKOR approach: Evaluating quality of internet health information

Proliferation of health related information on the Internet is both welcoming and a concern. For instance when solicited information goes wrong, it tends to have dire consequences on the general public. Assessing the quality of Internet health information is often difficult but a rational and systematic approach can be useful in evaluating the quality of the services they render to the public. The paper proposes a fuzzy VIKOR framework for evaluating and ranking Internet health information providers under a fuzzy environment where uncertainties and subjectivities are catered for with linguistic variables. Linguistic variables with triangular fuzzy numbers (TFN) are used to evaluate weights of the evaluation criteria and the rankings of each Internet health information provider. A numerical example is demonstrated using HIV/AIDS online information providers in the most adult prevalent country in the world. The proposed method is compared with TOPSIS and can be applied in evaluating the quality of other specific Internet health information providers.

A comparative study of consumers’ readiness for internet shopping in two African emerging economies: Some preliminary findings

This research seeks to empirically investigate factors that could either inhibit or facilitate consumers’ readiness for Internet shopping in two highly influential countries in the African continent. In this study, a structured questionnaire-based cross-sectional convenience sampling was used to elicit information from respondents in Ghana and Nigeria respectively. We have identified six cogent factors that are significantly influencing consumers’ readiness for Internet shopping in both countries, these six influential factors were all subjected to hypotheses testing using non-parametric statistical methods. Based on some of our findings, we found out that demographic variables, perceived level of distrust, Internet access availability, the proliferation of social media site usage amongst the younger population all have an important role to play in the uptake of Internet shopping in both countries. We also found out that the female gender compared to the male gender in Ghana would most likely have a higher perception level of distrust in Internet shopping. It is also interesting to note that perceived level of distrust is positively correlated with the demand for the promulgation (and implementation) of Internet transactions’ laws in Nigeria. By and large, we have equally pointed out some limitations of the present study and also provided some relevant future research directions given that this study is, arguably, the first of its kind in Africa to compare consumers’ readiness for Internet shopping in any two African emerging economies. We are optimistic that Internet shopping offers an emerging business opportunity for retail businesses to fully take advantage of the rising digitally literate African youth populace, who constantly crave for speed of service delivery, convenience and a mutually beneficial trust based relationship. DOI: 10.5901/mjss.2014.v5n23p1882

Exploring Roles of Females in Contemporary Socio-Politico-Economic Governance: An Association Rule Approach

Undeniably, the engagement of females in socio-politico-economic activities of most countries in the world, especially in developing economies, is far less than males. Although females form the majority in most developing countries, they are rarely engaged in the discourse of cogent developmental issues. The rising interest of females in political and socio-economic discourse, especially in the western world, has sparked female interest in the governance structure of developing countries. Subsequently, with an increased penetration of the Internet and social media, the contribution of females to governance has even assumed a new level. Using primary data collected from six Sub-Saharan African (SSA) countries, the paper identifies relationships of females’ interest in socio-politico-economic governance on the countries surveyed. This paper equally digested a repertoire of data from relevant secondary sources on female involvement in the political landscape of SSA countries. To unravel some key relationships amongst the variables of interest in the study, we have used association rules (data mining technique). One of our key findings appears to indicate that the interest of females in political discourse is highly associated with the level of trust respondents have in the governance and leadership of the countries. DOI: 10.5901/mjss.2014.v5n23p2178

Using Fuzzy PROMETHEE to Select Countries for Developmental Aid

Wealthy nations continue to demonstrate their unwavering support to improving conditions and the general well-being of poor countries in spite of the recent economic crises. However, as developmental aid relatively shrinks, both Aid donors and recipient countries have shown keen interest in methodologies used in evaluating developmental assistance programs. Evaluation of aid programs is seen as a complex task mainly because of the several non-aid factors that tend to affect overall outcomes. Adding to the complexity are the subjective sets of criteria used in Aid evaluations programs. This paper proposes a two stage framework of fuzzy TOPSIS and sensitivity analysis to demonstrate how aid-recipient countries can be evaluated to deepen transparency, fairness, value for money and sustainability of such aid programs. Using the Organisation for Economic Co-operation and Development (OECD) set of subjective criteria for evaluating aid programs; a numerical example pre-defined by linguistic terms parameterized by triangular fuzzy numbers is provided to evaluate aid programs. Fuzzy PROMETHEE is used in the first stage to evaluate and rank aid-recipients followed by a comparative analysis with Fuzzy VIKOR and Fuzzy TOPSIS to ascertain an accurateness of the method used. A sensitivity analysis is further added that anticipates possible influences from lobbyists and examines the effect of that bias in expert ratings on the evaluation process. The result shows a framework that can be employed in evaluating aid effectiveness of recipient-countries.

Development Aid Decision Making Framework Based on Hybrid MCDM

Developmental Aid Programs or what is normally referred to as Official Development Assistance (ODA), plays a key role in the growth process of many underdeveloped and developing countries. However, with a recent growing scarcity of resources and a general call for strict accountability from aid-recipient countries, there has been some interests in the design of aid performance evaluation methodologies or tools. To deepen such interests, this paper proposes a hybrid Fuzzy AHP Synthetic Extent—PROMETHEE framework of how aid-recipient countries could be evaluated and selected in developmental aid programs. With the use of the Organization for Economic Co-operation and Development (OECD) set of subjective criteria for evaluating aid programs, a decision framework pre-defined by linguistic terms of triangular fuzzy number format is provided for such selection decision problem. The framework serves to deepen transparency, fairness, value for money and sustainability of development aid programs.

Investigating Web Based Marketing in the Context of Micro and Small-Scale Enterprises (MSEs): A Decision Tree Classification Technique

This paper presents the findings of an exploratory study of web based marketing (WBM) usage predictor variables in the context of micro and small-scale enterprises (MSEs). By means of a cross-sectional field study, a structured questionnaire was used to elicit responses from 267 enterprises situated in the South East Region of Nigeria. The main rationale for this study is to provide a vivid description of pertinent variables that are most likely to influence an enterprise’s consideration of the relevance and/or implementation of WBM. Against this backdrop, the authors used the decision tree classification technique of data mining to build a predictive model. One of the interesting findings in this study seems to show that service-oriented enterprises that have a social media presence and are equally headed by highly educated women have a higher proclivity of engaging in WBM. By and large, our findings provide an understanding of idiosyncratic factors that impact on WBM non (usage) by enterprises. Lastly, our findings have implications for practitioners and policy makers in developing countries, particularly that of Nigeria.

Enterprise Competitive Analysis and Consumer Sentiments on Social Media

The utilization of Social media tools in business enterprises has tremendously increased with an increased number of users and a corresponding upsurge in time spent online. Online social media services such as Facebook and Twitter are used by companies to introduce new products and services, provide various supports and interact with customers on daily basis. This regular interaction of businesses and consumers results in huge amount of customer-generated content which is becoming a source of insight in analysing the often erratic consumer behaviour. For companies to harness the business potential of social media to increase competitive advantage, sentiments behind textual data of both their customers and that of their competitors must be keenly monitored and analysed. This paper demonstrates how companies especially those in the Telecommunication industry can seize the opportunity presented by social media to mine textual data to gain advantage over competitors by cumulatively understanding consumer opinions, frustrations and satisfaction. Using Facebook and Twitter sites of the top three telecommunication companies in Ghana: MTN, Vodafone and Tigo the paper reveals insights from unstructured texts of customers of these three companies. The results show (1) the exponential growth of social media users in Ghana (2) impact and numbers behind active social media participation in the telecommunication industry (3) the power of social media opinion mining for competitive analysis (4) how business value could be extracted from the huge unstructured textual data available on social media and (5) the company that is more responsive to customer concerns.

Patterns and trends in the concept of green economy: A text mining approach

The term ‘green economy’ has recently become a topical issue that has engaged the attention of Governments, International bodies and the media. The understanding of this concept and policy concentration is carved in various ways depending on the body that is engaged. There exist varied definitions of the ‘green economy’ with many associating it directly to agriculture since it has the ‘green’ connotation. However, despite the varied definitions, one principle that stands out most is the term “Sustainable development” or simply “sustainability. It has 3 pillars namely; social sustainability, economic and environment sustainability. Based on the in-depth of knowledge of the concept of green economy and the commitment of Governments and other international organizations, several policy documents and articles have been published on the web for global consumption. This paper uses the web mining algorithms in-built in the R programming language to mine over 402 English articles on the internet on green economy. It identifies relevant terms and patterns, reveals frequent associative words and gives a conglomerate understanding of the concept. It also brings out the most active participants in the green economic drive and sought to find if by chance any of the three pillars of sustainability would be found in the most frequent terms.