This paper intends to better understand the pre-exercise of modeling for direct marketing response prediction and assess the predictive performance of machine learning. For this, the authors are using a machine learning technique in a dataset of direct marketing, which is available at IBM Watson Analytics in the IBM community. In the results, first, among all variables, customer lifetime value, coverage, employment status, income, marital status, monthly premium auto, months since last claim, months since policy inception, renew offer type, and the total claim amount is shown to influence direct marketing response. However, others have no significance. Second, for the full model, the accuracy rate is 0.864, which implies that the error rate is 0.136. Among the patients who predicted not having a direct marketing response, the accuracy that would not have a direct marketing response was 87.23%, and the accuracy that had a direct marketing response was 66.34% among the patients predicted to have a direct marketing response.
{"title":"Assessing the Predictive Performance of Machine Learning in Direct Marketing Response","authors":"Youngkeun Choi, Jae W. Choi","doi":"10.4018/ijebr.321458","DOIUrl":"https://doi.org/10.4018/ijebr.321458","url":null,"abstract":"This paper intends to better understand the pre-exercise of modeling for direct marketing response prediction and assess the predictive performance of machine learning. For this, the authors are using a machine learning technique in a dataset of direct marketing, which is available at IBM Watson Analytics in the IBM community. In the results, first, among all variables, customer lifetime value, coverage, employment status, income, marital status, monthly premium auto, months since last claim, months since policy inception, renew offer type, and the total claim amount is shown to influence direct marketing response. However, others have no significance. Second, for the full model, the accuracy rate is 0.864, which implies that the error rate is 0.136. Among the patients who predicted not having a direct marketing response, the accuracy that would not have a direct marketing response was 87.23%, and the accuracy that had a direct marketing response was 66.34% among the patients predicted to have a direct marketing response.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"10 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85240162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In line with marketers' growing use of product placement on YouTube, this study investigates elements of YouTube product placement that can ultimately affect viewers' purchase intention based on the theory of reasoned action framework. Structural equation modeling of data collected from 355 usable respondents demonstrates that three core elements of YouTube product placement affect attitudes toward brands which, in turn, affect purchase intention: relevance of a brand to a YouTuber's content, trustworthiness of the YouTuber, and favorability of the community on the YouTuber channel. The study also provides implications for marketers based on the findings.
{"title":"Ways to Implement Effective Product Placement on YouTube","authors":"Wanmo Koo","doi":"10.4018/ijebr.320232","DOIUrl":"https://doi.org/10.4018/ijebr.320232","url":null,"abstract":"In line with marketers' growing use of product placement on YouTube, this study investigates elements of YouTube product placement that can ultimately affect viewers' purchase intention based on the theory of reasoned action framework. Structural equation modeling of data collected from 355 usable respondents demonstrates that three core elements of YouTube product placement affect attitudes toward brands which, in turn, affect purchase intention: relevance of a brand to a YouTuber's content, trustworthiness of the YouTuber, and favorability of the community on the YouTuber channel. The study also provides implications for marketers based on the findings.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"32 1","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83630654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Alarifi, Mst Farjana Rahman, Md. Shamim Hossain
Businesses must prioritize customer complaints because they highlight critical areas where their products or services may be improved. The goal of this study is to use machine learning approaches to anticipate and evaluate customer complaint data. The current study used logistic regression and support vector machine (SVM) to predict customer complaints, and evaluated the datasets using machine learning techniques after collecting five distinct length datasets from the Consumer Financial Protection Bureau (CFPB) website and cleaning the data. Both logistic regression and SVM can accurately predict customer complaints, according to this study, but SVM gives the greatest accuracy. The current study also found that SVM provides the highest accuracy for a one-month dataset and Logistic regression provides for a three-month dataset. In addition, machine learning codes were utilized to display and tabulate consumer complaints across many dimensions.
{"title":"Prediction and Analysis of Customer Complaints Using Machine Learning Techniques","authors":"G. Alarifi, Mst Farjana Rahman, Md. Shamim Hossain","doi":"10.4018/ijebr.319716","DOIUrl":"https://doi.org/10.4018/ijebr.319716","url":null,"abstract":"Businesses must prioritize customer complaints because they highlight critical areas where their products or services may be improved. The goal of this study is to use machine learning approaches to anticipate and evaluate customer complaint data. The current study used logistic regression and support vector machine (SVM) to predict customer complaints, and evaluated the datasets using machine learning techniques after collecting five distinct length datasets from the Consumer Financial Protection Bureau (CFPB) website and cleaning the data. Both logistic regression and SVM can accurately predict customer complaints, according to this study, but SVM gives the greatest accuracy. The current study also found that SVM provides the highest accuracy for a one-month dataset and Logistic regression provides for a three-month dataset. In addition, machine learning codes were utilized to display and tabulate consumer complaints across many dimensions.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"28 1","pages":"1-25"},"PeriodicalIF":0.0,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87903781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cloud computing adoption and utilization is gaining prominence in most developing countries. Its adoption is influenced by several factors, which can constitute a limitation rather than an advantage for firms. This research, therefore, explored the issues surrounding the adoption of cloud computing by small and medium-sized enterprises (SMEs) in a developing economy. An SME operating in Ghana for over five years was purposively selected as the case for the study. Technology-organization-environment (TOE) framework served as a guiding lens. Interviews were held with selected staff of the case firm. Data were analyzed using the Miles and Huberman's transcendental realism technique. It was discovered that the motivation for cloud computing adoption is the possibility of getting a state-of-the-art IT infrastructure at the lowest cost possible. The study presents the factors that influenced cloud computing adoption in the SME. The study contributes to improving the present understanding of cloud computing as an SME's strategic tool for operating within a developing economy.
{"title":"Reaching for the \"Cloud\": The Case of an SME in a Developing Economy","authors":"Eric Ansong, S. Boateng","doi":"10.4018/ijebr.319324","DOIUrl":"https://doi.org/10.4018/ijebr.319324","url":null,"abstract":"Cloud computing adoption and utilization is gaining prominence in most developing countries. Its adoption is influenced by several factors, which can constitute a limitation rather than an advantage for firms. This research, therefore, explored the issues surrounding the adoption of cloud computing by small and medium-sized enterprises (SMEs) in a developing economy. An SME operating in Ghana for over five years was purposively selected as the case for the study. Technology-organization-environment (TOE) framework served as a guiding lens. Interviews were held with selected staff of the case firm. Data were analyzed using the Miles and Huberman's transcendental realism technique. It was discovered that the motivation for cloud computing adoption is the possibility of getting a state-of-the-art IT infrastructure at the lowest cost possible. The study presents the factors that influenced cloud computing adoption in the SME. The study contributes to improving the present understanding of cloud computing as an SME's strategic tool for operating within a developing economy.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"3 1","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79692136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study is to examine the effect of social media marketing tactics—such as advantageous campaigns, relevant content, popular content, and presence on multiple platforms—on customer satisfaction in travel and tourism offices in Jordan. The study also explores how demographic variables like age, sex, education, and income influence this relationship. The results confirmed that social media marketing drives are positively related to customer satisfaction. The findings showed that all the drives—advantageous campaigns, relevant content, popular content, and presence on multiple social media platforms—have a significant impact on customer satisfaction. The results also suggest that demographic variables like age, sex, education, and income moderate the relationship between social media marketing drives and customer satisfaction, implying that the effect of these drives on customer satisfaction may vary based on demographic factors.
{"title":"The Influence of Social Marketing Drives on Customer Satisfaction via Demographic Variables as Moderating Factors","authors":"R. Al-Dmour, H. Al-dmour, Eatedalameen Ahmadamin","doi":"10.4018/ijebr.319325","DOIUrl":"https://doi.org/10.4018/ijebr.319325","url":null,"abstract":"The purpose of this study is to examine the effect of social media marketing tactics—such as advantageous campaigns, relevant content, popular content, and presence on multiple platforms—on customer satisfaction in travel and tourism offices in Jordan. The study also explores how demographic variables like age, sex, education, and income influence this relationship. The results confirmed that social media marketing drives are positively related to customer satisfaction. The findings showed that all the drives—advantageous campaigns, relevant content, popular content, and presence on multiple social media platforms—have a significant impact on customer satisfaction. The results also suggest that demographic variables like age, sex, education, and income moderate the relationship between social media marketing drives and customer satisfaction, implying that the effect of these drives on customer satisfaction may vary based on demographic factors.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"1 1","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89828389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed to investigate the extent to which financial technology (Fintech) is adopted in Palestine from the perspective of bank customers. The researcher meant to analyze various, significant dimensions such the barriers, advantages, components and risks of adopting the (Fintech). The study adopted a descriptive-analytical approach using a questionnaire as a main tool for the study. The study population consisted of bank clients or customers; and a sample of (500) customers of the most important Palestinian banks was selected randomly. The study concluded that the level of total adoption of financial technology in Palestine is medium; the main findings of the study also showed a high relative significance of both the barriers and risks of using Fintech, especially with regard to the preference of traditional banking operations or transactions over the use of electronic services due to the absence of clear laws and legislations that aim to protect banking transactions and dealings using electronic services. Furthermore, the study results showed that the relative importance of the advantages and components of (Fintech) has decreased despite the reduction in transaction costs by exempting electronic banking services from any commissions and / or fees. With regard to the demographic variables, the researcher found that there were no differences in the adoption of financial (Fintech) in Palestine that could be attributed to participants' gender, age or the bank they work for, while there were differences attributed to the variables of the city in which the bank is located and educational level of the study participants. The study concluded with several recommendations; the most important of which was the need for banks and bank administrations to enhance their customers' confidence in electronic banking services by providing an adequate technical infrastructure for the adoption and use of financial technology in Palestine.
{"title":"FinTech Adoption in Palestine : Bank Customers' Perspectives","authors":"B. Awwad","doi":"10.4018/ijebr.318662","DOIUrl":"https://doi.org/10.4018/ijebr.318662","url":null,"abstract":"This study aimed to investigate the extent to which financial technology (Fintech) is adopted in Palestine from the perspective of bank customers. The researcher meant to analyze various, significant dimensions such the barriers, advantages, components and risks of adopting the (Fintech). The study adopted a descriptive-analytical approach using a questionnaire as a main tool for the study. The study population consisted of bank clients or customers; and a sample of (500) customers of the most important Palestinian banks was selected randomly. The study concluded that the level of total adoption of financial technology in Palestine is medium; the main findings of the study also showed a high relative significance of both the barriers and risks of using Fintech, especially with regard to the preference of traditional banking operations or transactions over the use of electronic services due to the absence of clear laws and legislations that aim to protect banking transactions and dealings using electronic services. Furthermore, the study results showed that the relative importance of the advantages and components of (Fintech) has decreased despite the reduction in transaction costs by exempting electronic banking services from any commissions and / or fees. With regard to the demographic variables, the researcher found that there were no differences in the adoption of financial (Fintech) in Palestine that could be attributed to participants' gender, age or the bank they work for, while there were differences attributed to the variables of the city in which the bank is located and educational level of the study participants. The study concluded with several recommendations; the most important of which was the need for banks and bank administrations to enhance their customers' confidence in electronic banking services by providing an adequate technical infrastructure for the adoption and use of financial technology in Palestine.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"1 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82292029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Digital shopping has been the most imperious facet of e-retailing, and it has become an essential part of consumers' lifestyles. Besides the various advantages offered to digital shoppers, there are certain difficulties faced by them while making an online purchase. Therefore, it is significant to identify the factors influencing the consumer's purchase decision in the digital shopping context. The study empirically investigates the association of various factors related to consumers digital shopping experience on the purchase decision. The results reveal that the seven factors—website aesthetics, accessibility, trust, price offerings, security, delivery, and quality—have a positive association with consumer digital purchase decision. The findings will help the online traders to understand the satisfaction experienced by the consumers in the digital shopping context and develop strategies to attract new consumers and retain existing ones.
{"title":"Consumers' Digital Shopping Experience: A Study of the Factors Influencing Purchase Decision","authors":"C. Patro","doi":"10.4018/ijebr.318475","DOIUrl":"https://doi.org/10.4018/ijebr.318475","url":null,"abstract":"Digital shopping has been the most imperious facet of e-retailing, and it has become an essential part of consumers' lifestyles. Besides the various advantages offered to digital shoppers, there are certain difficulties faced by them while making an online purchase. Therefore, it is significant to identify the factors influencing the consumer's purchase decision in the digital shopping context. The study empirically investigates the association of various factors related to consumers digital shopping experience on the purchase decision. The results reveal that the seven factors—website aesthetics, accessibility, trust, price offerings, security, delivery, and quality—have a positive association with consumer digital purchase decision. The findings will help the online traders to understand the satisfaction experienced by the consumers in the digital shopping context and develop strategies to attract new consumers and retain existing ones.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"43 1","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80247814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Against the backdrop of invariant financial and economic reforms, there are presumptive changes in the confines and speed with which target variables respond to Reserve Bank of India (RBI) policy signals. The result of transmission lags from monetary policy to the real sector is unmistakable. The empirical approach used in this study is a natural progression from the VAR model videlicet, co-integration, and error correction techniques used to overcome the problem of spurious regression associated with non-stationary time-series data. After a shock induces disequilibrium, the speed and degree of adjustment return to a balanced state but with some time lag. The results indicate that in the two-step verification model, it takes approximately 2.851 months for WACMR to fully respond to a change in policy rates, whereas in the second step, it takes approximately 10.33 months for base rates to reach their complete pass-through following changes in call money market and deposit rates.
{"title":"A Policy Rate Channel Testing of Monetary Policy Transmission Mechanism","authors":"F. Malik, Deepanjali Das, L. Janjua, H. Adam","doi":"10.4018/ijebr.317887","DOIUrl":"https://doi.org/10.4018/ijebr.317887","url":null,"abstract":"Against the backdrop of invariant financial and economic reforms, there are presumptive changes in the confines and speed with which target variables respond to Reserve Bank of India (RBI) policy signals. The result of transmission lags from monetary policy to the real sector is unmistakable. The empirical approach used in this study is a natural progression from the VAR model videlicet, co-integration, and error correction techniques used to overcome the problem of spurious regression associated with non-stationary time-series data. After a shock induces disequilibrium, the speed and degree of adjustment return to a balanced state but with some time lag. The results indicate that in the two-step verification model, it takes approximately 2.851 months for WACMR to fully respond to a change in policy rates, whereas in the second step, it takes approximately 10.33 months for base rates to reach their complete pass-through following changes in call money market and deposit rates.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"13 1","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89870574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Social media is an important part of young generations' digital lives and has become much more than a social connection tool. This research offers comprehensions into usage of social media among Gen Y and Gen Z and investigates the usage of social media's features such as socialization, information, entertainment, education, and shopping. Various previous studies are available which attempted to investigate the usage of social media by Gen Z and Gen Y independently. This study is the first that attempted to compare the usage between Gen Z and Gen Y. This is an empirical study comprising 293 respondents from Gen Y and Gen Z, who were selected purposively. The findings suggest that Gen Z use social media more than Gen Y for education, entertainment, shopping, and socialization whereas social media usage of both the generations for information seeking are equal. This study offers recommendations for companies from India to consider incorporating social media marketing actions to encourage their brands and products to specific age groups.
{"title":"Social Media Usage: A Comparison Between Generation Y and Generation Z in India","authors":"Girish Mude, Swapnil Undale","doi":"10.4018/ijebr.317889","DOIUrl":"https://doi.org/10.4018/ijebr.317889","url":null,"abstract":"Social media is an important part of young generations' digital lives and has become much more than a social connection tool. This research offers comprehensions into usage of social media among Gen Y and Gen Z and investigates the usage of social media's features such as socialization, information, entertainment, education, and shopping. Various previous studies are available which attempted to investigate the usage of social media by Gen Z and Gen Y independently. This study is the first that attempted to compare the usage between Gen Z and Gen Y. This is an empirical study comprising 293 respondents from Gen Y and Gen Z, who were selected purposively. The findings suggest that Gen Z use social media more than Gen Y for education, entertainment, shopping, and socialization whereas social media usage of both the generations for information seeking are equal. This study offers recommendations for companies from India to consider incorporating social media marketing actions to encourage their brands and products to specific age groups.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"10 1","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81210767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sales prediction with minute accuracy plays a crucial role for an organization to sustain amidst the global competitive business environment. The use of artificial intelligence (AI) on top of the existing information technology environment has become one of the most exciting and promising area for any organizations in the current era of digital marketing. E-marketing provides customers to share their views with other customers. In this paper, the authors proposed a model which will be helpful to the digital marketers to find out the potential customers to extract value from customer feedback. The proposed model is based on artificial neural network and will make it possible to identify the customer demand depending on previous feedback and to predict the future sales volume of the product. The authors tried to utilize AI, mainly neural networks (NNs), to construct an intelligent sales prediction and also to apply ANNs for prediction regarding sales of mobile phone (Redmi, Note 6 Pro) one month ahead depending on customer feedback on two e-commerce platform, namely Amazon.in and Snapdeal.in.
{"title":"AI-Based Sales Forecasting Model for Digital Marketing","authors":"Biswajit Biswas, M. Sanyal, Tuhin Mukherjee","doi":"10.4018/ijebr.317888","DOIUrl":"https://doi.org/10.4018/ijebr.317888","url":null,"abstract":"Sales prediction with minute accuracy plays a crucial role for an organization to sustain amidst the global competitive business environment. The use of artificial intelligence (AI) on top of the existing information technology environment has become one of the most exciting and promising area for any organizations in the current era of digital marketing. E-marketing provides customers to share their views with other customers. In this paper, the authors proposed a model which will be helpful to the digital marketers to find out the potential customers to extract value from customer feedback. The proposed model is based on artificial neural network and will make it possible to identify the customer demand depending on previous feedback and to predict the future sales volume of the product. The authors tried to utilize AI, mainly neural networks (NNs), to construct an intelligent sales prediction and also to apply ANNs for prediction regarding sales of mobile phone (Redmi, Note 6 Pro) one month ahead depending on customer feedback on two e-commerce platform, namely Amazon.in and Snapdeal.in.","PeriodicalId":13628,"journal":{"name":"Int. J. E Bus. Res.","volume":"9 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77641585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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