International Journal of Society Systems Science (12 papers in press)
An Analysis of Wine Retail Sector: A Case for Improving the Nigeria Market
by Osadebamwen Ogbeide
Abstract: The objective of the study was to determine how best to improve the Nigeria wine retail market. The approach of the study was to compare the Nigeria and Australia wine retail markets. The samples of wine consumers were drawn from the two countries. A survey questionnaire was used to obtain information relevant to the objectives of the study. The result of the study showed wine consumers from the two countries were similar in consumption pattern, socio-demographics and involvement with wine. However while wine consumption was a usual drinking behaviour of Australian consumers, it evoked a sense of high social status for the Nigerian drinkers. The study found that the retailing of wine was more developed in Australia than in Nigeria. The opportunities to acquire wine knowledge, taste before purchase and engage in wine related activities were limited in Nigeria but widely available in Australia as an effective market strategy. Going forward, these opportunities must be provided by wine retailers, importers/distributors of foreign wines and the local producers to be explored by consumers in the Nigerian wine market. Free pre-purchase wine tasting must be encouraged to booster consumers involvement with wine, consumption of assorted wines and development of palate by potential wine drinkers.
Keywords: Wine; Wine consumer; Wine consumer behaviour; Wine retailing; Nigeria wine market.
Multi-criteria based Prioritization of B2C E-Commerce Website
by Anu G. Aggarwal, Aakash Sharma
Abstract: The advent of the internet has led to the establishment of e-commerce and its greater part of the revenue comes from business-to-consumer (B2C). The efficiency of B2C e-commerce systems depends on critical success factors and the customers priority for available B2C e-commerce websites. Thus, prioritizing the alternatives of B2C e-commerce websites is important, which is a problem based on multiple-criteria-decision-making (MCDM). This paper developed an extended B2C e-commerce success model by including criteria such as refund policy, online reviews, valance, helpfulness and personalization so as to represent new e-commerce world challenges. Numerical illustration is presented for prioritizing the alternatives of B2C e-commerce websites on basis of extended B2C e-commerce success model using integrated analytical hierarchal process with technique of order preference by similarity to ideal solution (AHP-TOPSIS) technique. The analytical hierarchal process (AHP) is used to calculate the weights of the e-commerce success factors criteria and TOPSIS is used to obtain the final preferences.
Keywords: E-commerce; Critical Success Factors; Personalization; Customer Feedback; Refund Policy; Online Marketing; MCDM; AHP; TOPSIS.
Facilitate Decision making in Higher Educational Institutions (HEIs) by linking Course taking pattern and Student Performance Characterized by Contextual Knowledge
by Subhashini Bhaskaran
Abstract: Preliminary literature study and actual observation of student performance in HEIs showed that time to degree and GPA of students can be enhanced using the phenomenon of knowledge discovery pertaining to course taking pattern from student dataset characterized by contextual knowledge. The main objective of this research was to investigate this phenomenon. Literature shows that knowledge about course taking patterns is useful for decision making about enhancement of student performance in HEIs. Hence this research helps to discover course taking pattern as well as its association to time to degree and GPA characterized by contextual knowledge using the modified process. Apriori Algorithm was used and it was found that there is relationship between course taking pattern and time to degree characterized by Contextual knowledge.
Keywords: HEIs; Contextual knowledge; Student Performance; Time-to-degree; Course Taking Patterns.
A Fuzzy Classification Model for Identification of Potential Areas of Urban Sprawl
by Pushpendra Sisodia
Abstract: The worlds urban population has increased 2% to over 50% in last two centuries. It is estimated that it will reach over 75% by 2030. Due to increase in urban population developing countries like India are facing more problems in mega cities like uncontrolled, unauthorised, uncoordinated, and unplanned urban growth; which is often termed as urban sprawl. Urban sprawl is generally spread between urban and rural areas, which we cant consider either in urban nor in rural. The areas, which lie between urban and rural can be considered as semi-urban areas. The semi-urban areas are in the phase of new development from rural to urban hence it attracts more urban sprawl. In this regards, we have proposed, a fuzzy pixel classification model for identification of potential areas of urban sprawl using fuzzy logic along with GIS and remote sensing technique. We have collected 256 pixel samples according to the resolution of different bands (red, green and blue) of Landsat 8 satellite image. This sample is used in fuzzy pixel classification of Landsat 8 satellite image. The degree of membership has been calculated by taking mean of particular bands like red, green, and blue. We have made IF-THEN rules for assigning a unique class to particular pixels for fuzzy classification. IF-THEN rules areas used to separate urban, semi-urban pixels from non-urban pixels. The results of fuzzy pixel classification have been calculated using producer accuracy, user accuracy, and overall kappa. We have compared results of Fuzzy Pixel Classification Model to existing models like Maximum Likelihood Classification, Mahalanobis Classification, and Minimum Distance Classification. The results are clearly showing that Fuzzy Pixel Classification Model has given better results over existing techniques.
Keywords: Fuzzy Logic; GIS and Remote Sensing Image Classification; Fuzzy Pixel Classification.
Modelling Urban Sprawl Using Fuzzy Cellular Automata Model For The City Jaipur
by Pushpendra Sisodia
Abstract: The unorganised, unplanned, uncontrolled, and unauthorised development of urban growth has been termed as urban sprawl and often referring as complex pattern of transportation, social, economic, and land use development. The rapid increase in population and economic development are the primary influences of urban sprawl. Urban sprawl is the major problem of metropolitan areas in all over the world especially developing countries. The impact of urban sprawl can be noted as pollution, traffic, loss of prime agricultural land, deforestation, congestion of places, and water pollution. The proper planning of metropolitan areas is major concern of stockholders, especially for those, who are involved in forecasting, modelling, and policy making related to sustainable development. Urban sprawl is a major obstacle for urban planner to achieve sustainable development. In this paper, we have proposed a Fuzzy-CA-Markov model for modelling urban sprawl. We have chosen the city Jaipur as study area. The factors which affect the urban sprawl is considered as fuzzy parameter like accessibility from local road, accessibility from main road, accessibility from major road, slop, altitude, and density. The Fuzzy-CA-Markov model has also been used to measure the future urban sprawl. The future prediction of urban sprawl was measured through Markovs cellular automata model. The output of Markov model is used by CA model. Suitability maps were prepared by setting fuzzy transition rules from a land use state to another state. The best results have been received by using 14 iteration and 15*15 neighbourhood (Maximum Kappa = 0.78). LULC map of year 2015 is prepared using transformation matrix, and predicted for the same 2015 year for validation. By comparing both images, there is close similarity in both images that is confirmed by kappa coefficient as 0.89. Using the same assessment procedure, and parameter, we have projected the future urban sprawl pattern for the year 2025.
Keywords: Keywords: Remote sensing; GIS; Fuzzy Logic; Image Classification.
Comparing different Classifiers and Feature Selection techniques for Emotion Classification
by Satish M. Srinivasan, Prashanth Ramesh
Abstract: In this study, we have explored the potentiality of six different supervised machine learning approaches and feature selection filters to recognize four basic emotions (anger, happy, sadness and surprise) using three different heterogeneous emotion-annotated dataset which combines sentences from news headlines, fairy tales and blogs. For classification purpose, we have chosen the feature set to include the bag-of-words. Our study reveals the fact that the use of the resampling filter and other various feature selection filters together contribute towards boosting the prediction accuracies of the classifiers. However, the boosting capabilities are more profound in the resampling filter in comparison to the use of the different feature selection filters.
Keywords: Text Mining; Feature selection filters; supervised classifiers; emotion classification; accuracy.
PROTECTING THE RIGHTS OF PEOPLE DISPLACED BY DAMS: AN ASSESSMENT OF THE DEVELOPMENT OF GHANAS BUI DAM
by Mahmud Mukhtar Muhammed
Abstract: For over a half century now, large-scale dams and other large infrastructure projects have been pursued to advance the socioeconomic transformation of various countries and regions. However, adverse effects sometimes arise through the execution of the projects including the violations of the rights of affected communities and persons as a result of development-induced displacement and resettlement activities. One of the theoretical approaches that advocate for processes that lead to positive outcomes in the implementation of such development projects is the rights-based approach. Using primary data from Ghanas Bui Dam Project, the perceptions and views of the displaced people, their leaders, the dam managers and other relevant stakeholders are analysed with the view to unmasking the extent to which the rights of the displaced people were safeguarded and promoted throughout the project cycle. While the paper reveals that some positive outcomes have been attained in the Bui Dam Project, more favourable outcomes would have been realised if international covenants relating to the rights of infrastructure-affected-people were mainstreamed into local legal frameworks instead of heavily relying on best practice standards which are only hortatory and prescriptive.
Keywords: Development-induced displacement and resettlement (DIDR); Rights-Based Approach (RBA); large-scale dams; Bui Dam Project; Free Prior and Informed Consent (FPIC); Ghana.
Messaging techniques (MPI) in grid environment: a survey
by Hamid Yasinian, Mansour Esmaeilpour, Mohammadmehdi Shirmohammadi, Mahshid Jamshidi
Abstract: The newfangled phenomenon of grid, meaning to share the heterogeneous calculative sources and data between the independent organizations which are geographically disjoined. Grid functional programs usually need a great volume of distributed data or calculative sources for applying which does not usually exist in a single organisation. Nevertheless, due to the existence of the heterogeneous sources and the dynamic nature of grid, reaching a high level of functioning in this environment is so difficult. Regarding the grid environment's being heterogeneous and dynamic performing, these acts are not easy at all. Applying a MPI functional program on calculative grids needs fault tolerance and designing a middleware which conceals the nodes' being dynamic in grid for programmer. Applying the functional programs under grid is extremely susceptible of errors. So in this article all methods of tolerance including diagnosing the fault and improving fault have been surveyed as a key feature in grid contexts.
Keywords: grid; distributed computing; MPI; fault tolerance.
Discovering the optimal set of ratios to use in accounting-based models
by Duarte Trigueiros, Carolina Sam
Abstract: Ratios are the prime tool of financial analysis. In predictive modelling tasks, however, the use of ratios raises difficulties, the most obvious being that, in a multivariate setting, there is no guarantee that the collection of ratios eventually selected as predictors will be optimal in any sense. Using, as starting-point, a formal characterisation of cross-sectional accounting numbers, the paper shows how the multilayer perceptron can be trained to create internal representations which are an optimal set of ratios for a given modelling task. Experiments suggest that, when such ratios are utilised as predictors in well-known modelling tasks, performance improves on that reported by the extant literature.
Keywords: knowledge extraction; financial analysis; financial ratios; financial technology; fintech; accounting models; bankruptcy prediction; financial misstatement detection; earnings forecasting.
Influence of police stations' location on crime incidence in developing countries like Nigeria
by Olayinka Akinsumbo Ajala, Banji Raphael Owabumoye
Abstract: Studies on crime incidence believed that presence of police station in an area could reduce crime incidence. Without spatially based study, it might be erroneous to agree with their belief. This study was to ascertain this belief. Geographic information system (GIS) techniques were used to analyse both primary and secondary data acquired in the study area, Akure, Southwestern Nigeria. It was shown that crime incidence continued to increase as distance from police stations increased and started to decrease as distance increased to two kilometres due to reduction in police coverage. Also, the results showed that there was clustered pattern of crimes, the clustering was located at the central part of the study area where the police stations are located. The study concluded that spatial distribution of police stations could influence the pattern of crime incidence in cities.
Keywords: Akure; cities; coldspot; crime incidence; geographic information system; GIS; hotspot; insecurity; location; Nigeria; police station.
Qualitative data analysis and its nature: debates and discussion
by Pratap Chandra Mandal
Abstract: Qualitative data analysis (QDA) involves data collection and data analysis which comprises of coding, sorting, and sifting of qualitative data. QDA involves a style of data collection and analysis which is considered as non-scientific by some critics. It is believed that this challenges or weakens the robustness and the reliability of qualitative research. Critics frequently ignore the extraordinary set of strengths and potentiality that QDA has in the field of social science research. This paper aims to address this debate by analysing the nature and quality of the methods employed in qualitative research. It analyses and evaluates the different approaches and perspectives of QDA. The paper argues and establishes that QDA has significantly broader perspectives and research capacity, and involves more than coding, sorting, and sifting of qualitative data.
Keywords: qualitative data analysis; QDA; coding; sorting; sifting.
The effect of bad road on crime reportage in Southwestern Nigeria: Akure
by Banji Raphael Owabumoye, Olayinka Akinsumbo Ajala
Abstract: This study examined the impact of roads conditions (good and bad) on crime reportage to the police in Akure, Southwestern Nigeria. Coordinate points of crime scenes and information from key informants were the primary data. Secondary data used were administrative map and SPOT 6 satellite imagery. The results revealed that roads that were good or fair were found at the central part of the study area while roads that were bad were found toward the outskirts. Crime incidences were highly significant in areas where good roads were and insignificant in areas where bad roads were. This implied that victims were able to report crime incidence to police quickly and police were able to respond to distress call and thereby to high rate of apprehension of offenders in areas with good roads. While opposite is the situation in areas with bad roads. The study concluded that governments at all levels in Nigeria (federal, state and local governments) need to do more in road reconstruction and rehabilitation to help security agencies to perform better.
Keywords: Akure; coldspot; crime; geodatabase; geographic information system; GIS; hotspot; Nigeria; police; remote sensing; road.