The onset of the COVID-19 pandemic has changed consumer usage behavior towards mobile payment (m-... more The onset of the COVID-19 pandemic has changed consumer usage behavior towards mobile payment (m-payment) services. Consumer usage behavior towards m-payment services continues to increase due to access to usage experiences shared through online consumer reviews (OCRs). The proliferation of massive OCRs, coupled with quick and effective decisions concerning the evaluation and selection of m-payment services, is a practical issue for research. This paper develops a novel decision evaluation model that integrates OCRs and multiattribute decision-making (MADM) with probabilistic linguistic information to identify m-payment usage attributes and utilize these attributes to evaluate and rank m-payment services. First and foremost, the attributes of m-payment usage discussed by consumers in OCRs are extracted using the Latent Dirichlet Allocation (LDA) topic modeling approach. These key attributes are used as the evaluation scales in the MADM. Based on an unsupervised sentiment algorithm, the sentiment scores of the text reviews regarding the attributes are calculated. We convert the sentiment scores into probabilistic linguistic elements based on the probabilistic linguistic term set (PLTS) theory and statistical analysis. Furthermore, we construct a novel technique known as probabilistic linguistic indifference threshold-based attribute ratio analysis (PL-ITARA) to discover the weight importance of the usage attributes. Subsequently, the positive and negative ideal-based PL-ELECTRE I methodology is proposed to evaluate and rank m-payment services. Finally, a case study on selecting appropriate m-payment services in Ghana is examined to authenticate the validity and applicability of our proposed decision evaluation methodology.
Stakeholders have become worried about the environmental problems of agricultural production acti... more Stakeholders have become worried about the environmental problems of agricultural production activities. Therefore, there is pressure on smallholder farmers to observe environmental regulations and embed sustainable green technologies in their production. The literature on green production has thoroughly emphasized the critical role of behavioral factors in adopting environmental sustainability practices. We develop a probabilistic linguistic preference selection index method to assess the behavioral constructs that promote the adoption of agricultural green production technologies (AGPTs) among smallholder rice farmers in an emerging economy. The result shows that the five most-important factors promoting the adoption of AGPTs include knowledge (0.828), perceived cost and benefit (0.819), descriptive norm (0.810), moral and environmental concern (0.809), and injunctive norm (0.807). The study findings offer insightful directions for examining rice farmers’ decisions on the adoption...
The emergence of sports tourism has compelled sports managers to rethink the management and impro... more The emergence of sports tourism has compelled sports managers to rethink the management and improvement of sports facilities. Through service quality analysis, sports managers can identify the strengths and weaknesses of their activities for possible advancement. Hence, this study aims to develop a decision support model based on integrating online reviews and data envelopment analysis to measure the degree of tourist satisfaction and provide benchmarking goals for service improvement. The proposed model employs text mining techniques to discover service quality attributes from text reviews. According to the discovered service quality attributes, we conduct sentiment analysis to reveal the sentiment polarities of the text reviews. Then, we refine the polarities and ratings of online reviews into linguistic distribution assessments. Furthermore, we develop a linguistic distribution output-oriented non-discretionary bestpoint slack-based measure (BP-SBM) to compute the degree of tourist satisfaction and benchmarking goals. The linguistic distribution output-oriented non-discretionary BP-SBM can handle both positive and negative data values, thus overcoming the flaws of the traditional model. Meanwhile, the proposed decision support model investigates how the service-quality attributes interact to provide improvement pathways for an underperforming stadium based on association rule mining. We test the applicability of the proposed decision support model on some Elite stadia in Europe.
One of the main aims of a theory of three-way decisions is to model a cohort of human ways of dea... more One of the main aims of a theory of three-way decisions is to model a cohort of human ways of dealing with problems and how to go about information processing considering applications in designing and implementing intelligent systems. Threeway decision with decision-theoretic rough sets is a new model characterized by the conditional risk, the loss functions and the minimum-risk decision rules. We provide a three-way decisions approach using loss functions evaluated by multiple experts based on the Bayesian decision theory. In this paper, we propose the methodologies of the aggregation of loss functions of decision-theoretic rough sets under group decision-making environment. Then we further compare them with that of the existing papers, which focus on the aggregation of the thresholds. We also construct basic model of three-way group decisions. Finally, an empirical study of evaluating the loss functions validates the reasonability and effectiveness of the proposed models. The contributions of the study are as follows: group decision-making is regarded as a knowledge based, which makes the decision more convincing as compared to single-person methods. Considering the different situations, we mainly design the corresponding aggregation operators of loss functions. Our new approach provides the methodologies of the aggregation of loss functions which in turn are used to compute the thresholds for the determination or construction of the basic rules of three-way group decision-making.
Ghana's demand for crude oil and refined petroleum products has been growing over the past decade... more Ghana's demand for crude oil and refined petroleum products has been growing over the past decade. This growth has been driven by socio-economic and technical factors that have influenced each category of final energy use. The growing urban population is demanding new vehicles and new roads, raising the demand for energy in the transportation and all other sectors of the economy. Consequently, Oil prices rose from 2004 to historic highs in mid-2008, only to fall precipitously in the last four months of 2008 and lose all the gains of the preceding four and a half years. The steep price increase was challenging for all economies including Ghana. The high price of oil will invariably affect revenue mobilisation, expenditure, and therefore the fiscal position of government and inflation. The study is an attempt to forecast and analyse the macroeconomic impact of oil price fluctuations in Ghana using annual data from 2000-2011. It focuses on studying the feasibility forecast using nested conditional mean (ARIMA) and conditional variance (GARCH, GJR, EGARCH) family of models under such volatile market conditions. A regression based forecast filtering simulation is proposed and studied for any improvements in the forecasted results.
On consideration of the effectiveness of group decision making (GDM) in practical complex decisio... more On consideration of the effectiveness of group decision making (GDM) in practical complex decision problems, we introduce GDM into three-way decisions with decision-theoretic rough sets (DTRSs) and propose GDM-based three-way decisions. GDM-based three-way decisions extend the range of applications of three-way decisions with DTRSs and provide a novel interpretation of the determination of loss functions. Based on DTRSs, we firstly focus on analyzing the determination for the loss functions under the GDM environment. With the aid of the principle of justifiable granularity, we adopt the important and majority suggestions of experts to measure each loss function, which supports a coherent way of designing information granules in presence of numerics. In this case, the loss functions are determined in the form of interval-valued information granule. By using the interval comparison method, we further deduce the three-way decisions and design a corresponding decision procedure of GDM-based three-way decisions. Then, an example of strategy supply selection is given to elaborate the GDM-based three-way decisions. Finally, we validate the performance of our proposed method by experimental analysis.
The objective of this paper was to empirically characterize the volatility in the growth rate of ... more The objective of this paper was to empirically characterize the volatility in the growth rate of real Gross Domestic Product (GDP) for Ghana in three sectors using data spanning from 2000 to 2012. The GARCH-type models(GARCH, EGARCH and GJR-GARCH) were used for the analysis of data. The results of the study present evidence that the symmetric GARCH(1, 1) structure applies reasonably well to GDP when quarterly observations are used.. As expected from financial time series, the data for the study exhibit characteristics such as leptokurtosis, clustering, asymmetric and leverage effects. It was found that there was a significant increase in volatility and leverage effect.
The purpose of the research was to determine if SSCE scores, session and sex of students imparts ... more The purpose of the research was to determine if SSCE scores, session and sex of students imparts negatively or positively on each student FCGPA score at the tertiary level. Data were compiled from the student records of various departments. The information sought were on gender, the session (morning or evening), the cumulative grade points average and the Senior Secondary School Certificate Examination(SSCE) scores of the 2006 to 2009 year group of students. The multiple linear regression with interaction was used to analysis the data. It was found that students who to attend the morning session on the average obtain higher FCGPA than their evening counterparts. It was also identified that there is no relation between a student’s sex and his or her cumulative grade points average (CGPA) at 5% significance level. Also a student who enters Koforidua Polytechnic with the “best SSCE” scores obtains the highest cumulative grade point average (CGPA). Keywords : multiple linear regression...
Probability modeling has a wide range of applications in the field of insurance and finance. Over... more Probability modeling has a wide range of applications in the field of insurance and finance. Over the years, its applications have been modified to include simulation techniques which in most cases are engaged to enhanced or validate the desired estimates. This study investigates the probability distributions that best fit a number of insurance claims. In particular, it compares the Poisson distribution and the negative binomial distribution models to determine which distribution best fits insurance claim data obtained from two Insurance Companies in Ghana. Data on number of claims of a funeral policy spanning from 2006 to 2010 were used for the study. Probability distribution models and the parametric bootstrap methods were employed in analyzing the data collected. The result of the study revealed that on the average, the number of claims tends to increase as the year go by. Also the Negative Binomial Distribution was found to be superior to the Poisson distribution in fitting the ...
Probability modeling has a wide range of applications in the field of insurance and finance. Over... more Probability modeling has a wide range of applications in the field of insurance and finance. Over the years, its applications have been modified to include simulation techniques which in most cases are engaged to enhanced or validate the desired estimates. This study investigates the probability distributions that best fit a number of insurance claims. In particular, it compares the Poisson distribution and the negative binomial distribution models to determine which distribution best fits insurance claim data obtained from two Insurance Companies in Ghana. Data on number of claims of a funeral policy spanning from 2006 to 2010 were used for the study. Probability distribution models and the parametric bootstrap methods were employed in analyzing the data collected. The result of the study revealed that on the average, the number of claims tends to increase as the year go by. Also the Negative Binomial Distribution was found to be superior to the Poisson distribution in fitting the ...
One of the major problems of varied knowledge-based systems has to do with aggregation and fusion... more One of the major problems of varied knowledge-based systems has to do with aggregation and fusion. Pang’s probabilistic linguistic term sets denotes aggregation of fuzzy information and it has attracted tremendous interest from researchers recently. The purpose of this article is to deal investigating methods of information aggregation under the probabilistic linguistic environment. In this situation we defined certain Einstein operational laws on probabilistic linguistic term elements (PLTESs) based on Einstein product and Einstein sum. Consequently, we develop some probabilistic linguistic aggregation operators, notably the probabilistic linguistic Einstein average (PLEA) operators, probabilistic linguistic Einstein geometric (PLEG) operators, weighted probabilistic linguistic Einstein average (WPLEA) operators, weighted probabilistic linguistic Einstein geometric (WPLEG) operators. These operators extend the weighted averaging operator and the weighted geometric operator for the ...
As an effective aggregation tool, power average (PA) allows the input arguments being aggregated ... more As an effective aggregation tool, power average (PA) allows the input arguments being aggregated to support and reinforce each other, which provides more versatility in the information aggregation process. Under the probabilistic linguistic term environment, we deeply investigate the new power aggregation (PA) operators for fusing the probabilistic linguistic term sets (PLTSs). In this paper, we firstly develop the probabilistic linguistic power average (PLPA), the weighted probabilistic linguistic power average (WPLPA) operators, the probabilistic linguistic power geometric (PLPG) and the weighted probabilistic linguistic power geometric (WPLPG) operators. At the same time, we carefully analyze the properties of these new aggregation operators. With the aid of the WPLPA and WPLPG operators, we further design the approaches for the application of multi-criteria group decision-making (MCGDM) with PLTSs. Finally, we use an illustrated example to expound our proposed methods and verify their performances.
The onset of the COVID-19 pandemic has changed consumer usage behavior towards mobile payment (m-... more The onset of the COVID-19 pandemic has changed consumer usage behavior towards mobile payment (m-payment) services. Consumer usage behavior towards m-payment services continues to increase due to access to usage experiences shared through online consumer reviews (OCRs). The proliferation of massive OCRs, coupled with quick and effective decisions concerning the evaluation and selection of m-payment services, is a practical issue for research. This paper develops a novel decision evaluation model that integrates OCRs and multiattribute decision-making (MADM) with probabilistic linguistic information to identify m-payment usage attributes and utilize these attributes to evaluate and rank m-payment services. First and foremost, the attributes of m-payment usage discussed by consumers in OCRs are extracted using the Latent Dirichlet Allocation (LDA) topic modeling approach. These key attributes are used as the evaluation scales in the MADM. Based on an unsupervised sentiment algorithm, the sentiment scores of the text reviews regarding the attributes are calculated. We convert the sentiment scores into probabilistic linguistic elements based on the probabilistic linguistic term set (PLTS) theory and statistical analysis. Furthermore, we construct a novel technique known as probabilistic linguistic indifference threshold-based attribute ratio analysis (PL-ITARA) to discover the weight importance of the usage attributes. Subsequently, the positive and negative ideal-based PL-ELECTRE I methodology is proposed to evaluate and rank m-payment services. Finally, a case study on selecting appropriate m-payment services in Ghana is examined to authenticate the validity and applicability of our proposed decision evaluation methodology.
Stakeholders have become worried about the environmental problems of agricultural production acti... more Stakeholders have become worried about the environmental problems of agricultural production activities. Therefore, there is pressure on smallholder farmers to observe environmental regulations and embed sustainable green technologies in their production. The literature on green production has thoroughly emphasized the critical role of behavioral factors in adopting environmental sustainability practices. We develop a probabilistic linguistic preference selection index method to assess the behavioral constructs that promote the adoption of agricultural green production technologies (AGPTs) among smallholder rice farmers in an emerging economy. The result shows that the five most-important factors promoting the adoption of AGPTs include knowledge (0.828), perceived cost and benefit (0.819), descriptive norm (0.810), moral and environmental concern (0.809), and injunctive norm (0.807). The study findings offer insightful directions for examining rice farmers’ decisions on the adoption...
The emergence of sports tourism has compelled sports managers to rethink the management and impro... more The emergence of sports tourism has compelled sports managers to rethink the management and improvement of sports facilities. Through service quality analysis, sports managers can identify the strengths and weaknesses of their activities for possible advancement. Hence, this study aims to develop a decision support model based on integrating online reviews and data envelopment analysis to measure the degree of tourist satisfaction and provide benchmarking goals for service improvement. The proposed model employs text mining techniques to discover service quality attributes from text reviews. According to the discovered service quality attributes, we conduct sentiment analysis to reveal the sentiment polarities of the text reviews. Then, we refine the polarities and ratings of online reviews into linguistic distribution assessments. Furthermore, we develop a linguistic distribution output-oriented non-discretionary bestpoint slack-based measure (BP-SBM) to compute the degree of tourist satisfaction and benchmarking goals. The linguistic distribution output-oriented non-discretionary BP-SBM can handle both positive and negative data values, thus overcoming the flaws of the traditional model. Meanwhile, the proposed decision support model investigates how the service-quality attributes interact to provide improvement pathways for an underperforming stadium based on association rule mining. We test the applicability of the proposed decision support model on some Elite stadia in Europe.
One of the main aims of a theory of three-way decisions is to model a cohort of human ways of dea... more One of the main aims of a theory of three-way decisions is to model a cohort of human ways of dealing with problems and how to go about information processing considering applications in designing and implementing intelligent systems. Threeway decision with decision-theoretic rough sets is a new model characterized by the conditional risk, the loss functions and the minimum-risk decision rules. We provide a three-way decisions approach using loss functions evaluated by multiple experts based on the Bayesian decision theory. In this paper, we propose the methodologies of the aggregation of loss functions of decision-theoretic rough sets under group decision-making environment. Then we further compare them with that of the existing papers, which focus on the aggregation of the thresholds. We also construct basic model of three-way group decisions. Finally, an empirical study of evaluating the loss functions validates the reasonability and effectiveness of the proposed models. The contributions of the study are as follows: group decision-making is regarded as a knowledge based, which makes the decision more convincing as compared to single-person methods. Considering the different situations, we mainly design the corresponding aggregation operators of loss functions. Our new approach provides the methodologies of the aggregation of loss functions which in turn are used to compute the thresholds for the determination or construction of the basic rules of three-way group decision-making.
Ghana's demand for crude oil and refined petroleum products has been growing over the past decade... more Ghana's demand for crude oil and refined petroleum products has been growing over the past decade. This growth has been driven by socio-economic and technical factors that have influenced each category of final energy use. The growing urban population is demanding new vehicles and new roads, raising the demand for energy in the transportation and all other sectors of the economy. Consequently, Oil prices rose from 2004 to historic highs in mid-2008, only to fall precipitously in the last four months of 2008 and lose all the gains of the preceding four and a half years. The steep price increase was challenging for all economies including Ghana. The high price of oil will invariably affect revenue mobilisation, expenditure, and therefore the fiscal position of government and inflation. The study is an attempt to forecast and analyse the macroeconomic impact of oil price fluctuations in Ghana using annual data from 2000-2011. It focuses on studying the feasibility forecast using nested conditional mean (ARIMA) and conditional variance (GARCH, GJR, EGARCH) family of models under such volatile market conditions. A regression based forecast filtering simulation is proposed and studied for any improvements in the forecasted results.
On consideration of the effectiveness of group decision making (GDM) in practical complex decisio... more On consideration of the effectiveness of group decision making (GDM) in practical complex decision problems, we introduce GDM into three-way decisions with decision-theoretic rough sets (DTRSs) and propose GDM-based three-way decisions. GDM-based three-way decisions extend the range of applications of three-way decisions with DTRSs and provide a novel interpretation of the determination of loss functions. Based on DTRSs, we firstly focus on analyzing the determination for the loss functions under the GDM environment. With the aid of the principle of justifiable granularity, we adopt the important and majority suggestions of experts to measure each loss function, which supports a coherent way of designing information granules in presence of numerics. In this case, the loss functions are determined in the form of interval-valued information granule. By using the interval comparison method, we further deduce the three-way decisions and design a corresponding decision procedure of GDM-based three-way decisions. Then, an example of strategy supply selection is given to elaborate the GDM-based three-way decisions. Finally, we validate the performance of our proposed method by experimental analysis.
The objective of this paper was to empirically characterize the volatility in the growth rate of ... more The objective of this paper was to empirically characterize the volatility in the growth rate of real Gross Domestic Product (GDP) for Ghana in three sectors using data spanning from 2000 to 2012. The GARCH-type models(GARCH, EGARCH and GJR-GARCH) were used for the analysis of data. The results of the study present evidence that the symmetric GARCH(1, 1) structure applies reasonably well to GDP when quarterly observations are used.. As expected from financial time series, the data for the study exhibit characteristics such as leptokurtosis, clustering, asymmetric and leverage effects. It was found that there was a significant increase in volatility and leverage effect.
The purpose of the research was to determine if SSCE scores, session and sex of students imparts ... more The purpose of the research was to determine if SSCE scores, session and sex of students imparts negatively or positively on each student FCGPA score at the tertiary level. Data were compiled from the student records of various departments. The information sought were on gender, the session (morning or evening), the cumulative grade points average and the Senior Secondary School Certificate Examination(SSCE) scores of the 2006 to 2009 year group of students. The multiple linear regression with interaction was used to analysis the data. It was found that students who to attend the morning session on the average obtain higher FCGPA than their evening counterparts. It was also identified that there is no relation between a student’s sex and his or her cumulative grade points average (CGPA) at 5% significance level. Also a student who enters Koforidua Polytechnic with the “best SSCE” scores obtains the highest cumulative grade point average (CGPA). Keywords : multiple linear regression...
Probability modeling has a wide range of applications in the field of insurance and finance. Over... more Probability modeling has a wide range of applications in the field of insurance and finance. Over the years, its applications have been modified to include simulation techniques which in most cases are engaged to enhanced or validate the desired estimates. This study investigates the probability distributions that best fit a number of insurance claims. In particular, it compares the Poisson distribution and the negative binomial distribution models to determine which distribution best fits insurance claim data obtained from two Insurance Companies in Ghana. Data on number of claims of a funeral policy spanning from 2006 to 2010 were used for the study. Probability distribution models and the parametric bootstrap methods were employed in analyzing the data collected. The result of the study revealed that on the average, the number of claims tends to increase as the year go by. Also the Negative Binomial Distribution was found to be superior to the Poisson distribution in fitting the ...
Probability modeling has a wide range of applications in the field of insurance and finance. Over... more Probability modeling has a wide range of applications in the field of insurance and finance. Over the years, its applications have been modified to include simulation techniques which in most cases are engaged to enhanced or validate the desired estimates. This study investigates the probability distributions that best fit a number of insurance claims. In particular, it compares the Poisson distribution and the negative binomial distribution models to determine which distribution best fits insurance claim data obtained from two Insurance Companies in Ghana. Data on number of claims of a funeral policy spanning from 2006 to 2010 were used for the study. Probability distribution models and the parametric bootstrap methods were employed in analyzing the data collected. The result of the study revealed that on the average, the number of claims tends to increase as the year go by. Also the Negative Binomial Distribution was found to be superior to the Poisson distribution in fitting the ...
One of the major problems of varied knowledge-based systems has to do with aggregation and fusion... more One of the major problems of varied knowledge-based systems has to do with aggregation and fusion. Pang’s probabilistic linguistic term sets denotes aggregation of fuzzy information and it has attracted tremendous interest from researchers recently. The purpose of this article is to deal investigating methods of information aggregation under the probabilistic linguistic environment. In this situation we defined certain Einstein operational laws on probabilistic linguistic term elements (PLTESs) based on Einstein product and Einstein sum. Consequently, we develop some probabilistic linguistic aggregation operators, notably the probabilistic linguistic Einstein average (PLEA) operators, probabilistic linguistic Einstein geometric (PLEG) operators, weighted probabilistic linguistic Einstein average (WPLEA) operators, weighted probabilistic linguistic Einstein geometric (WPLEG) operators. These operators extend the weighted averaging operator and the weighted geometric operator for the ...
As an effective aggregation tool, power average (PA) allows the input arguments being aggregated ... more As an effective aggregation tool, power average (PA) allows the input arguments being aggregated to support and reinforce each other, which provides more versatility in the information aggregation process. Under the probabilistic linguistic term environment, we deeply investigate the new power aggregation (PA) operators for fusing the probabilistic linguistic term sets (PLTSs). In this paper, we firstly develop the probabilistic linguistic power average (PLPA), the weighted probabilistic linguistic power average (WPLPA) operators, the probabilistic linguistic power geometric (PLPG) and the weighted probabilistic linguistic power geometric (WPLPG) operators. At the same time, we carefully analyze the properties of these new aggregation operators. With the aid of the WPLPA and WPLPG operators, we further design the approaches for the application of multi-criteria group decision-making (MCGDM) with PLTSs. Finally, we use an illustrated example to expound our proposed methods and verify their performances.
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