In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and ta...In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.展开更多
Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying ...Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.展开更多
This study examines the effects of e-banking service quality on customer satisfaction in the Commercial Bank of Ethiopia(CBE)branches in Wolaita Sodo town.Using a causal research design,the study explored the cause-an...This study examines the effects of e-banking service quality on customer satisfaction in the Commercial Bank of Ethiopia(CBE)branches in Wolaita Sodo town.Using a causal research design,the study explored the cause-and-effect relationship between service quality dimensions and customer satisfaction.A sample of 385 customers was selected using convenience sampling,with 365 questionnaires returned.Data were collected through questionnaires and analyzed using SPSS V.21.The Cronbach’s alpha value of 0.72 from a pilot study confirmed reliability.Descriptive and inferential statistics,including multiple linear regression and one-way ANOVA,were employed.Results revealed that three service quality dimensions-responsiveness,reliability,and assurance-were statistically significant and positively influenced customer satisfaction,while two dimensions showed negative associations.The regression model’s coefficient of determination(R²)was 0.621,indicating a moderate explanatory power.Findings suggest that CBE managers and stakeholders should prioritize improving responsiveness,reliability,and assurance by providing prompt,dependable,and trustworthy services.Due to limitations in time and resources,this study was confined to CBE branches in Wolaita Sodo town;future research could expand to a national level or other service sectors.展开更多
This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn...This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn in the face of digital disruption.The research uses a quantitative approach focusing on empirical customer data to accurately predict buying trends and adapt marketing techniques.Demand forecasts in the health sector are important,as in every sector.In particular,the material forecast and stock forecasting of the purchasing unit of hospitals are among the areas that receive significant attention.Four classifiers(Random Forest,Logistic Regression,Gradient Boosting and XGBoost)are trained and evaluated using various performance indicators as part of a systematic approach involving Kaggle data collection,preparation and model selection.The results show excellent accuracy in predicting customer attrition,but there are limitations in precision and recall,indicating room for improvement.Confusion matrices provide information about the performance of each classifier,allowing for continuous improvement of predictive analytics techniques.Ethical concerns are rigorously addressed throughout the work process to guarantee appropriate data and machine learning methodologies.The proposals emphasize the proactive use of predictive analytics to identify at-risk customers and implement targeted retention strategies.Incorporating new data sources,improving customer experience,and utilizing collaborative churn management methods are recommended to increase forecast accuracy and business outcomes.Finally,this research provides important insights into the usefulness of predictive analytics for customer churn forecasting as well as practical recommendations for businesses seeking to increase customer retention and reduce churn risk.By leveraging empirical research findings and implementing ethical and rigorous churn control strategies,businesses can achieve long-term success in today’s changing market environment.展开更多
Facial recognition payment(FRP),a new method of contactless payment,has attracted considerable attention over the past few years.However,the research on this topic remains nascent.This study assessed the drivers of cu...Facial recognition payment(FRP),a new method of contactless payment,has attracted considerable attention over the past few years.However,the research on this topic remains nascent.This study assessed the drivers of customers’FRP continuance intention from the perspectives of coolness and inspiration.We use online survey data from 610 Chinese FRP customers as the basis for our conceptual model.The results show that the coolness factors of subculture,attractiveness,utility,and originality have positive and significant effects on customers’inspired-by states and that subculture and utility also promote inspired-to.Inspired-by is positively associated with inspiredto,which in turn enhances customers’FRP continuance intention.Furthermore,the relationship between inspired-to and FRP continuance intention is negatively moderated by financial risk.In addition to contributing to the literature on FRP,coolness,and customer inspiration,this study offers several suggestions for implementing and developing FRP systems.展开更多
The jewelry industry faces intense competition,making customer loyalty essential for sustained success.This paper examines customer loyalty through the lens of the ABC attitude model,which encompasses cognitive,affect...The jewelry industry faces intense competition,making customer loyalty essential for sustained success.This paper examines customer loyalty through the lens of the ABC attitude model,which encompasses cognitive,affective,and behavioral dimensions.Cognitive factors,such as perceived quality and brand reputation,establish the foundation of trust,while affective factors,including emotional attachment and trust,strengthen customer relationships.Behavioral factors,such as repeat purchases and advocacy,reflect observable loyalty actions.The study proposes strategies to enhance loyalty,including delivering superior products and services,strengthening customer relationship management,and leveraging word-of-mouth and digital marketing.These approaches provide actionable insights for building long-term customer relationships in a competitive market.Future research could explore emerging technologies and cultural influences to further refine loyalty strategies.This research highlights the multidimensional nature of customer loyalty and offers practical recommendations for jewelry enterprises.展开更多
This paper aims to develop a customer satisfaction model for bus rapid transit （BRT）. Both the socio-economic and travel characteristics of passengers were considered to be independent variables. Changzhou BRT was t...This paper aims to develop a customer satisfaction model for bus rapid transit （BRT）. Both the socio-economic and travel characteristics of passengers were considered to be independent variables. Changzhou BRT was taken as an example and on which on-board surveys were conducted to collect data. Ordinal logistic regression （OLR） was used as the modeling approach. The general OLR-based procedure for modeling customer satisfaction is proposed and based on which the customer satisfaction model of Changzhou BRT is developed. Some important findings are concluded： Waiting sub-journey affects customer satisfaction the most, riding sub- journey comes second and arriving station sub-journey has relatively fewer effects. The availability of shelter and benches at stations imposes heavy influence on customer satisfaction. Passengers＇ socio-economic characteristics have heavy impact on customer satisfaction.展开更多
A two-period duopoly model is developed to examine the competitive effects of targeted advertising with customer recognition （TACR）. In the model, two competing firms sell goods to end consumers in the first period,...A two-period duopoly model is developed to examine the competitive effects of targeted advertising with customer recognition （TACR）. In the model, two competing firms sell goods to end consumers in the first period, during which customer recognition is obtained. In the second period, advertising can be targeted toward different consumer types. Advertising is assumed to be persuasive in the way that consumer valuation is increased. Equilibrium decisions and profits in each period are derived, showing that the firm who loses the current competition will win in the future. As a result, forward-looking firms price less aggressively so that their long-term profits can be enhanced with the help of TACR. Particularly, TACR improves profits through three important effects： valuation increasing, customer poaching, and anti-competition. Finally, this paper investigates the welfare issues, showing that firms enhance profits at the expense of consumer surplus. It is, therefore, suggested that public sectors take a step to protect consumers with the rapid development of targeting technology.展开更多
The discipline of business intelligence addresses a broad range of functional activities from data mining and statistical analysis to predictive modeling and reporting, and customer intelligence is the actionable outp...The discipline of business intelligence addresses a broad range of functional activities from data mining and statistical analysis to predictive modeling and reporting, and customer intelligence is the actionable output from an intelligence eco-system. In order to focus enterprise's attention on their customers satisfaction in the customer relationship management and make CRM system run more efficiently, a new concept of customer intelligence engine(CIE) is proposed at first time in the paper, the architecture of CIE is structured, the trigger of CIE is defined and described, the CIE-based CRM eco-system is also discussed.展开更多
The coupling of data and digital innovation opens the way for new business in the financial services sector,where customers are placed at the centre of decisions and data can help to develop customer knowledge.To carr...The coupling of data and digital innovation opens the way for new business in the financial services sector,where customers are placed at the centre of decisions and data can help to develop customer knowledge.To carry out our research,we adopted a multi-case study approach to explore how a data strategy is developed in the retail banking industry,together with its relationship with customer value,paying particular attention to the heterogeneity between traditional banks and financial technology companies(FinTechs).Two main points emerged from the study.Firstly,there are three possible approaches to Open Finance,which are mainly defined by their different corporate cultures,organisational configurations,technological architecture and data value.Secondly,it is not enough to be a FinTech to be best placed to exploit the market,as some traditional banks share the FinTechs’approach to Open Finance.Designing new tailored products,customising their prices and offering them over the right channels through targeted communication are all data-driven initiatives that stem from cross-or up-selling potential,core to the retail banking industry for turning a customer into a cash flow,thus enabling value to be created for customers.Our findings additionally revealed that there is a form of external information asymmetry between the customer and the bank,and that there is also an internal asymmetry between bank departments,as their visibility on information about the same customer may differ.展开更多
The central construct of customer lock-in （CL） is measured and its role along with that of consumer loyalty in influencing the brand-customer relationship is tested. Using data collected from focus groups, a measure...The central construct of customer lock-in （CL） is measured and its role along with that of consumer loyalty in influencing the brand-customer relationship is tested. Using data collected from focus groups, a measurement model for CL is developed, and a structural equation model consisted based on literature review and our own theory is established. Moreover, the moderating effects of CL on the relationship between perceived value （PV） and brand relationship quality （BRQ） , as well as that between BRQ and brand loyalty （BL） based on data collected through a survey have been tested. Results indicate that consumer satisfaction is a critical factor in establishing brand-customer relationship, and the attitudinal brand loyalty is the key to obtain brand behavioral loyalty. Furthermore, CL tactics, such as decreasing consumers＇ learning cost and transactional cost facilitate the relationship building between customer and brand, while involuntary lock-in may have an adverse effect in the relationship building process. In addition, involuntary lock-in and loyalty program help in obtaining consumers＇ behavioral brand loyalty but not their attitudinal loyalty.展开更多
Recent research and studies have shown that Information Technology(IT)has a significant impact on service quality,customer satisfaction,and customer relationship development.With the proliferation and penetration of t...Recent research and studies have shown that Information Technology(IT)has a significant impact on service quality,customer satisfaction,and customer relationship development.With the proliferation and penetration of technology in all aspects of life,organizations are responding to the implications and opportunities that IT creates in relation to customer services.The main objective of using information technology in organizations is to increase customer satisfaction,service quality,and customer relationship management,which the authors will focus on here.Enhancing service quality,improving customer satisfaction,and establishing close and sustainable customer relationships are key advantages of leveraging information technology in this field.This article examines the impact of information technology on service quality,customer satisfaction,and customer relationship development and provides strategies and models for organizations to improve customer satisfaction and establish closer connections with them through the use of information technology.Seventy individuals from the IT field were used to evaluate the proposed model.The proposed model was compared with three models:SEM,regression,and decision tree,and the results demonstrated better performance of this approach.展开更多
The purpose of this research is to examine the impact of artificial intelligence(AI)on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,specifically ...The purpose of this research is to examine the impact of artificial intelligence(AI)on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,specifically the partial least squares method,to test the hypotheses and explore the relationships between various variables.The findings indicate that effective business practices and successful AI assimilation have a positive impact on customer performance.Additionally,the results of this study provide valuable insights for both academic and practical communities.This study highlights the importance of specific variables,such as organizational and customer agility,customer experience,customer relationship quality,and customer performance in AI assimilation.By exploring these variables,it contributes significantly to the academic,managerial,and social aspects of AI and its impact on customer performance.展开更多
As the demand for customer service continues to increase,more companies are attempting to apply artificial intelligence technology in the field of customer service,enabling intelligent customer service,reducing custom...As the demand for customer service continues to increase,more companies are attempting to apply artificial intelligence technology in the field of customer service,enabling intelligent customer service,reducing customer service pressure,and reducing operating costs.Currently,the existing intelligent customer service has a limited degree of intelligence and can only answer simple user questions,and complex user expressions are difficult to understand.To solve the problem of low accuracy of multi-round dialogue semantic understanding,this paper proposes a semantic understanding model based on the fusion of a convolutional neural network(CNN)and attention.The model builds an“intention-slot”joint model based on the“encoding–decoding”framework and uses hidden semantic information that combines intent recognition and slot filling,avoiding the problem of information loss in traditional isolated tasks,and achieving end-to-end semantic understanding.Additionally,an improved attention mechanism based on CNNs is introduced in the decoding process to reduce the interference of redundant information in the original text,thereby increasing the accuracy of semantic understanding.Finally,by applying the model to electric power intelligent customer service,we verified through an experimental comparison that the proposed fusion model improves the performance of intent recognition and slot filling and can improve the user experience of electric power intelligent customer services.展开更多
With the development of society, customers are having an increasing expectation on bus service. Problems such as bus being late all the time seem to become common. It usually annoys the customers and have a bad influe...With the development of society, customers are having an increasing expectation on bus service. Problems such as bus being late all the time seem to become common. It usually annoys the customers and have a bad influence on bus companies.It's crucial to improve the bus service. This report adapts and applies a modified SERVQUAL approach to estimate the service quality in public transport. Wessex Red servcie, bus service in England UK, operated in partnership with the University of the West of England and the University of Bristol, is evaluated in the report being representative for bus service. In this study, the author has applied the SERVQUAL questionnaire among the three groups of customers in Bristol UK based on these five dimensions of SERVQUAL:"Tangibles, Responsiveness, Assurance, Reliability and Empathy"(Parasuraman, 1988). The results illustrates a high degree of importance placed on reliability, in which bus being late is an issue most concerned. The author analyzes the problem and finally provides suggestions and recommendation for the issue. This study is to provide a quality evaluation tool readily usable by transport operators willing to certify the service offered and it also offers a tool for practioners characterized by flexibility so as to fit individual needs. In addition, this study is beneficial to students who are learning Marketing. The study provides students a methodology in their marketing research. It also gives students a tool to evaluate services so as to set up their marketing plan and could give a better horizon to understand marketing.展开更多
Advancements in the internet technology triggered a line of developments in the field of marketing. As an alternative to the conventional shopping, online shopping over the internet has gained substantial share of ret...Advancements in the internet technology triggered a line of developments in the field of marketing. As an alternative to the conventional shopping, online shopping over the internet has gained substantial share of retail market. Customers get used to this new shopping venue and nowadays prefer it more and more according to the researchers, ten percent of the global population now uses internet for shopping. In this research, the author explored the relationship between the security measures implemented by a company, very active in the online shopping domain, and the customer trust and loyalty on the online services provided by this company. Findings of this research are based on survey data analyzed in SPSS. This research supports the existence of a relationship between the security of a company＇s website and customer trust and loyalty on the online services of this company When the perception of security measures improves, customer trust and loyalty increases accordingly展开更多
The current study represents an attempt at experiential value, perceived quality and customer satisfaction influence on customer lifetime value. The sampling frame consisted of Star Cruises purchases in Taiwan. The au...The current study represents an attempt at experiential value, perceived quality and customer satisfaction influence on customer lifetime value. The sampling frame consisted of Star Cruises purchases in Taiwan. The authors have collected yield 268 questionnaires, by screening out 13 questionnaires, including those missing value or incomplete answer, and finally a usable sample of 255 questionnaires were utilized in this study. The results show that experiential value, perceived quality and customer satisfaction have positive effects to customer lifetime value. Especially, experiential value has the strongest direct effect. Therefore, if resources are limited, the manager should focus on shaping the experiential value to increase customer lifetime value. Implications for marketing theory and practitioners are discussed, and possible directions for future research are sketched.展开更多
In this article, the results were presented of research concerning the visual and functional aspects of the websites of three largest logistics operators in Poland. The research was carried out with the participation ...In this article, the results were presented of research concerning the visual and functional aspects of the websites of three largest logistics operators in Poland. The research was carried out with the participation of the following three groups： institutional customers, individual customers and marketing management students. The article covers an attempt to evaluate cooperation through virtual contacts with the company. The analysis also concerned such issues as information on corporate social responsibility （CSR）, information on job offers and the position of the company on the market.展开更多
文摘In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.
文摘Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.
文摘This study examines the effects of e-banking service quality on customer satisfaction in the Commercial Bank of Ethiopia(CBE)branches in Wolaita Sodo town.Using a causal research design,the study explored the cause-and-effect relationship between service quality dimensions and customer satisfaction.A sample of 385 customers was selected using convenience sampling,with 365 questionnaires returned.Data were collected through questionnaires and analyzed using SPSS V.21.The Cronbach’s alpha value of 0.72 from a pilot study confirmed reliability.Descriptive and inferential statistics,including multiple linear regression and one-way ANOVA,were employed.Results revealed that three service quality dimensions-responsiveness,reliability,and assurance-were statistically significant and positively influenced customer satisfaction,while two dimensions showed negative associations.The regression model’s coefficient of determination(R²)was 0.621,indicating a moderate explanatory power.Findings suggest that CBE managers and stakeholders should prioritize improving responsiveness,reliability,and assurance by providing prompt,dependable,and trustworthy services.Due to limitations in time and resources,this study was confined to CBE branches in Wolaita Sodo town;future research could expand to a national level or other service sectors.
文摘This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn in the face of digital disruption.The research uses a quantitative approach focusing on empirical customer data to accurately predict buying trends and adapt marketing techniques.Demand forecasts in the health sector are important,as in every sector.In particular,the material forecast and stock forecasting of the purchasing unit of hospitals are among the areas that receive significant attention.Four classifiers(Random Forest,Logistic Regression,Gradient Boosting and XGBoost)are trained and evaluated using various performance indicators as part of a systematic approach involving Kaggle data collection,preparation and model selection.The results show excellent accuracy in predicting customer attrition,but there are limitations in precision and recall,indicating room for improvement.Confusion matrices provide information about the performance of each classifier,allowing for continuous improvement of predictive analytics techniques.Ethical concerns are rigorously addressed throughout the work process to guarantee appropriate data and machine learning methodologies.The proposals emphasize the proactive use of predictive analytics to identify at-risk customers and implement targeted retention strategies.Incorporating new data sources,improving customer experience,and utilizing collaborative churn management methods are recommended to increase forecast accuracy and business outcomes.Finally,this research provides important insights into the usefulness of predictive analytics for customer churn forecasting as well as practical recommendations for businesses seeking to increase customer retention and reduce churn risk.By leveraging empirical research findings and implementing ethical and rigorous churn control strategies,businesses can achieve long-term success in today’s changing market environment.
基金This study was supported by the National Natural Science Foundation of China(72202185,72302145)the Postdoctoral Science Foundation of China(2023M742232)the Innovation Research 2035 Pilot Plan of Southwest University(SWUPilotPlan026).
文摘Facial recognition payment(FRP),a new method of contactless payment,has attracted considerable attention over the past few years.However,the research on this topic remains nascent.This study assessed the drivers of customers’FRP continuance intention from the perspectives of coolness and inspiration.We use online survey data from 610 Chinese FRP customers as the basis for our conceptual model.The results show that the coolness factors of subculture,attractiveness,utility,and originality have positive and significant effects on customers’inspired-by states and that subculture and utility also promote inspired-to.Inspired-by is positively associated with inspiredto,which in turn enhances customers’FRP continuance intention.Furthermore,the relationship between inspired-to and FRP continuance intention is negatively moderated by financial risk.In addition to contributing to the literature on FRP,coolness,and customer inspiration,this study offers several suggestions for implementing and developing FRP systems.
文摘The jewelry industry faces intense competition,making customer loyalty essential for sustained success.This paper examines customer loyalty through the lens of the ABC attitude model,which encompasses cognitive,affective,and behavioral dimensions.Cognitive factors,such as perceived quality and brand reputation,establish the foundation of trust,while affective factors,including emotional attachment and trust,strengthen customer relationships.Behavioral factors,such as repeat purchases and advocacy,reflect observable loyalty actions.The study proposes strategies to enhance loyalty,including delivering superior products and services,strengthening customer relationship management,and leveraging word-of-mouth and digital marketing.These approaches provide actionable insights for building long-term customer relationships in a competitive market.Future research could explore emerging technologies and cultural influences to further refine loyalty strategies.This research highlights the multidimensional nature of customer loyalty and offers practical recommendations for jewelry enterprises.
基金The National Natural Science Foundation of China(No.61573098)the Scientific Research Projects in Universities of Inner Mongolia(No.NJZY16022)
文摘This paper aims to develop a customer satisfaction model for bus rapid transit （BRT）. Both the socio-economic and travel characteristics of passengers were considered to be independent variables. Changzhou BRT was taken as an example and on which on-board surveys were conducted to collect data. Ordinal logistic regression （OLR） was used as the modeling approach. The general OLR-based procedure for modeling customer satisfaction is proposed and based on which the customer satisfaction model of Changzhou BRT is developed. Some important findings are concluded： Waiting sub-journey affects customer satisfaction the most, riding sub- journey comes second and arriving station sub-journey has relatively fewer effects. The availability of shelter and benches at stations imposes heavy influence on customer satisfaction. Passengers＇ socio-economic characteristics have heavy impact on customer satisfaction.
基金The National Natural Science Foundation of China(No.71071033)the Research and Innovation Project for College Graduates of Jiangsu Province(No.CXZZ-0186)
文摘A two-period duopoly model is developed to examine the competitive effects of targeted advertising with customer recognition （TACR）. In the model, two competing firms sell goods to end consumers in the first period, during which customer recognition is obtained. In the second period, advertising can be targeted toward different consumer types. Advertising is assumed to be persuasive in the way that consumer valuation is increased. Equilibrium decisions and profits in each period are derived, showing that the firm who loses the current competition will win in the future. As a result, forward-looking firms price less aggressively so that their long-term profits can be enhanced with the help of TACR. Particularly, TACR improves profits through three important effects： valuation increasing, customer poaching, and anti-competition. Finally, this paper investigates the welfare issues, showing that firms enhance profits at the expense of consumer surplus. It is, therefore, suggested that public sectors take a step to protect consumers with the rapid development of targeting technology.
基金Supported by the Special Scientific Research Fund for Doctoral Education Base of Higher School (20030614011)National Science Fund of Excellent Youth (79725002)
文摘The discipline of business intelligence addresses a broad range of functional activities from data mining and statistical analysis to predictive modeling and reporting, and customer intelligence is the actionable output from an intelligence eco-system. In order to focus enterprise's attention on their customers satisfaction in the customer relationship management and make CRM system run more efficiently, a new concept of customer intelligence engine(CIE) is proposed at first time in the paper, the architecture of CIE is structured, the trigger of CIE is defined and described, the CIE-based CRM eco-system is also discussed.
文摘The coupling of data and digital innovation opens the way for new business in the financial services sector,where customers are placed at the centre of decisions and data can help to develop customer knowledge.To carry out our research,we adopted a multi-case study approach to explore how a data strategy is developed in the retail banking industry,together with its relationship with customer value,paying particular attention to the heterogeneity between traditional banks and financial technology companies(FinTechs).Two main points emerged from the study.Firstly,there are three possible approaches to Open Finance,which are mainly defined by their different corporate cultures,organisational configurations,technological architecture and data value.Secondly,it is not enough to be a FinTech to be best placed to exploit the market,as some traditional banks share the FinTechs’approach to Open Finance.Designing new tailored products,customising their prices and offering them over the right channels through targeted communication are all data-driven initiatives that stem from cross-or up-selling potential,core to the retail banking industry for turning a customer into a cash flow,thus enabling value to be created for customers.Our findings additionally revealed that there is a form of external information asymmetry between the customer and the bank,and that there is also an internal asymmetry between bank departments,as their visibility on information about the same customer may differ.
基金Sponsored by the National Natural Science Foundation of China (70772089)Program for New Century Excellent Talents in University (2006)
文摘The central construct of customer lock-in （CL） is measured and its role along with that of consumer loyalty in influencing the brand-customer relationship is tested. Using data collected from focus groups, a measurement model for CL is developed, and a structural equation model consisted based on literature review and our own theory is established. Moreover, the moderating effects of CL on the relationship between perceived value （PV） and brand relationship quality （BRQ） , as well as that between BRQ and brand loyalty （BL） based on data collected through a survey have been tested. Results indicate that consumer satisfaction is a critical factor in establishing brand-customer relationship, and the attitudinal brand loyalty is the key to obtain brand behavioral loyalty. Furthermore, CL tactics, such as decreasing consumers＇ learning cost and transactional cost facilitate the relationship building between customer and brand, while involuntary lock-in may have an adverse effect in the relationship building process. In addition, involuntary lock-in and loyalty program help in obtaining consumers＇ behavioral brand loyalty but not their attitudinal loyalty.
文摘Recent research and studies have shown that Information Technology(IT)has a significant impact on service quality,customer satisfaction,and customer relationship development.With the proliferation and penetration of technology in all aspects of life,organizations are responding to the implications and opportunities that IT creates in relation to customer services.The main objective of using information technology in organizations is to increase customer satisfaction,service quality,and customer relationship management,which the authors will focus on here.Enhancing service quality,improving customer satisfaction,and establishing close and sustainable customer relationships are key advantages of leveraging information technology in this field.This article examines the impact of information technology on service quality,customer satisfaction,and customer relationship development and provides strategies and models for organizations to improve customer satisfaction and establish closer connections with them through the use of information technology.Seventy individuals from the IT field were used to evaluate the proposed model.The proposed model was compared with three models:SEM,regression,and decision tree,and the results demonstrated better performance of this approach.
文摘The purpose of this research is to examine the impact of artificial intelligence(AI)on customer performance and identify the factors contributing to its effectiveness by employing a quantitative approach,specifically the partial least squares method,to test the hypotheses and explore the relationships between various variables.The findings indicate that effective business practices and successful AI assimilation have a positive impact on customer performance.Additionally,the results of this study provide valuable insights for both academic and practical communities.This study highlights the importance of specific variables,such as organizational and customer agility,customer experience,customer relationship quality,and customer performance in AI assimilation.By exploring these variables,it contributes significantly to the academic,managerial,and social aspects of AI and its impact on customer performance.
基金supported by National Natural Science Foundation of China(No.2018YFB0905000).
文摘As the demand for customer service continues to increase,more companies are attempting to apply artificial intelligence technology in the field of customer service,enabling intelligent customer service,reducing customer service pressure,and reducing operating costs.Currently,the existing intelligent customer service has a limited degree of intelligence and can only answer simple user questions,and complex user expressions are difficult to understand.To solve the problem of low accuracy of multi-round dialogue semantic understanding,this paper proposes a semantic understanding model based on the fusion of a convolutional neural network(CNN)and attention.The model builds an“intention-slot”joint model based on the“encoding–decoding”framework and uses hidden semantic information that combines intent recognition and slot filling,avoiding the problem of information loss in traditional isolated tasks,and achieving end-to-end semantic understanding.Additionally,an improved attention mechanism based on CNNs is introduced in the decoding process to reduce the interference of redundant information in the original text,thereby increasing the accuracy of semantic understanding.Finally,by applying the model to electric power intelligent customer service,we verified through an experimental comparison that the proposed fusion model improves the performance of intent recognition and slot filling and can improve the user experience of electric power intelligent customer services.
文摘With the development of society, customers are having an increasing expectation on bus service. Problems such as bus being late all the time seem to become common. It usually annoys the customers and have a bad influence on bus companies.It's crucial to improve the bus service. This report adapts and applies a modified SERVQUAL approach to estimate the service quality in public transport. Wessex Red servcie, bus service in England UK, operated in partnership with the University of the West of England and the University of Bristol, is evaluated in the report being representative for bus service. In this study, the author has applied the SERVQUAL questionnaire among the three groups of customers in Bristol UK based on these five dimensions of SERVQUAL:"Tangibles, Responsiveness, Assurance, Reliability and Empathy"(Parasuraman, 1988). The results illustrates a high degree of importance placed on reliability, in which bus being late is an issue most concerned. The author analyzes the problem and finally provides suggestions and recommendation for the issue. This study is to provide a quality evaluation tool readily usable by transport operators willing to certify the service offered and it also offers a tool for practioners characterized by flexibility so as to fit individual needs. In addition, this study is beneficial to students who are learning Marketing. The study provides students a methodology in their marketing research. It also gives students a tool to evaluate services so as to set up their marketing plan and could give a better horizon to understand marketing.
文摘Advancements in the internet technology triggered a line of developments in the field of marketing. As an alternative to the conventional shopping, online shopping over the internet has gained substantial share of retail market. Customers get used to this new shopping venue and nowadays prefer it more and more according to the researchers, ten percent of the global population now uses internet for shopping. In this research, the author explored the relationship between the security measures implemented by a company, very active in the online shopping domain, and the customer trust and loyalty on the online services provided by this company. Findings of this research are based on survey data analyzed in SPSS. This research supports the existence of a relationship between the security of a company＇s website and customer trust and loyalty on the online services of this company When the perception of security measures improves, customer trust and loyalty increases accordingly
文摘The current study represents an attempt at experiential value, perceived quality and customer satisfaction influence on customer lifetime value. The sampling frame consisted of Star Cruises purchases in Taiwan. The authors have collected yield 268 questionnaires, by screening out 13 questionnaires, including those missing value or incomplete answer, and finally a usable sample of 255 questionnaires were utilized in this study. The results show that experiential value, perceived quality and customer satisfaction have positive effects to customer lifetime value. Especially, experiential value has the strongest direct effect. Therefore, if resources are limited, the manager should focus on shaping the experiential value to increase customer lifetime value. Implications for marketing theory and practitioners are discussed, and possible directions for future research are sketched.
文摘In this article, the results were presented of research concerning the visual and functional aspects of the websites of three largest logistics operators in Poland. The research was carried out with the participation of the following three groups： institutional customers, individual customers and marketing management students. The article covers an attempt to evaluate cooperation through virtual contacts with the company. The analysis also concerned such issues as information on corporate social responsibility （CSR）, information on job offers and the position of the company on the market.
