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
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
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
To address the current situation where many small enterprises lack efficient management of customer data, this paper proposes a design and implementation plan of a customer relationship management (CRM) system based o...To address the current situation where many small enterprises lack efficient management of customer data, this paper proposes a design and implementation plan of a customer relationship management (CRM) system based on email service. It aims to solve the problems of data dispersion, untimely update and information redundancy in customer management of small and medium-sized enterprises. The system includes four core functional modules: historical email analysis, lead pool management, customer management and email archiving. Through email mining and web crawler technology, the system can extract potential customer information from historical emails and enrich lead data;the lead pool management module supports lead information maintenance, status tracking and conversion of high-value leads;the customer management module realizes the maintenance and dynamic tracking of customer information;the email management module provides the archiving of emails and attachments and the structured storage of basic email information. The system provides automated and intelligent customer information management, improves the work efficiency of sales staff, and provides an efficient customer relationship management solution for enterprises.展开更多
Purpose:Service convenience explores how consumers perceive the time and effort associated with purchasing or using a service.It examines the impact of convenience on customer satisfaction,loyalty,and behavioral inten...Purpose:Service convenience explores how consumers perceive the time and effort associated with purchasing or using a service.It examines the impact of convenience on customer satisfaction,loyalty,and behavioral intentions,often considering various dimensions like access,search,and transaction convenience.The reviews also investigate how service convenience interacts with other factors like service quality,perceived value,and customer satisfaction.Therefore,this paper seeks to analyze the dispersed academic literature on service convenience research.This paper reviews the existing literature on service convenience and examines the directions in which the past studies have focused.It highlights the gap in existing literature to identify future research directions in service convenience domain.Through this review,this study aims to gain insights into various aspects including research methodology,framework,trends,important factors related to service convenience.Design/methodology/approach:Data were collected from an objective overview of service convenience research.This study used a systematic literature review approach.A total of 13 papers were published between 2012 and 2024.Selected from the Scopus database,and Emerald Insight,following specific criteria outlined in the PRISMA process.Findings:In the context of customer satisfaction research,analysis often reveals that satisfaction can be organized into several main themes.Here are five variables that frequently appear in on customer satisfaction,customer loyalty,behavioral intentions,often considering various dimensions like access,search,and transaction convenience.The analysis shows a significant spike in conveniencebased accounting research from 2012 to 2024,indicating growing interest in the topic.展开更多
The Italian textile machinery sector,renowned for its technological excellence and innovative capacity,continues to navigate a complex global market with a strategic emphasis on digitalization,sustainability,and stron...The Italian textile machinery sector,renowned for its technological excellence and innovative capacity,continues to navigate a complex global market with a strategic emphasis on digitalization,sustainability,and strong customer partnerships.Marco Salvade’,President of ACIMIT,provided insights into the industry’s performance,key trends,and future directions.In the first quarter of 2025,Italian textile machinery exports saw a 6%decrease compared to the same period in 2024,totaling€363 million.This dip reflects ongoing geopolitical tensions and a cautious approach among global clients toward new investments.Despite these challenges,Italian manufacturers maintain a strong reputation for technological leadership and resilience.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
Dove’s 2017 advertising incident,which sparked widespread debate regarding perceived cultural insensitivity,highlighted a disconnect between the brand’s“Real Beauty”positioning and public reception.In response,thi...Dove’s 2017 advertising incident,which sparked widespread debate regarding perceived cultural insensitivity,highlighted a disconnect between the brand’s“Real Beauty”positioning and public reception.In response,this study proposes a strategic digital recovery framework,including revised campaign content,transparent communication through social media,and data-driven customer segmentation based on diverse skincare needs and cultural backgrounds.A PESTLE analysis underscores the importance of digital transformation and rising social consciousness in brand management.Findings suggest that inclusive messaging,precision targeting,and omnichannel digital engagement are key to restoring brand trust and reputation in the digital landscape.展开更多
Hidden champions play a critical role in China’s efforts to overcome technological and industrial“chokepoints”.These enterprises are pivotal for breaking free from Western technological embargoes,avoiding entrapmen...Hidden champions play a critical role in China’s efforts to overcome technological and industrial“chokepoints”.These enterprises are pivotal for breaking free from Western technological embargoes,avoiding entrapment in low-value-added production,and driving industrial upgrading.Given the distinct market environment in which China’s hidden champions have emerged,it is both timely and practically significant to examine their growth trajectories and underlying mechanisms.This study adopts a resource allocation perspective to investigate the development path of Chinese manufacturing enterprises into hidden champions,using a vertical case study of Hailiya Group.The findings reveal that such enterprises achieve hidden champion status by vertically concentrating on niche markets while harnessing technological potential and horizontally diversifying their technology application scenarios.Their growth follows a“T-shaped”strategy,combining vertical specialization in a focused market with horizontal expansion into new applications.Four critical mechanisms underpin the rise of manufacturing hidden champions:market niche positioning,innovation-driven focus,application scenario expansion,and ecosystem development.Specifically,these enterprises strategically target niche markets,establish a technology-oriented competitive edge,broaden technology applications to unlock new profit opportunities,and develop collaborative ecosystems to share resources and drive industrial advancement.This paper not only extends the interpretive boundaries of resource allocation theory but also offers fresh insights into the emergence of Chinese manufacturing enterprises as hidden champions,enriching our understanding of their unique growth dynamics.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
“This durian smells amazing!What variety is it?”“Do you offer any discounts for buying ice cream in bulk?”“One durian pizza and one portion of fresh durian,please!”At a tropical-themed shop in Nanning East Stati...“This durian smells amazing!What variety is it?”“Do you offer any discounts for buying ice cream in bulk?”“One durian pizza and one portion of fresh durian,please!”At a tropical-themed shop in Nanning East Station,a chorus of customer questions filled the air.Student clerks smiled as they answered inquiries,swiftly packing each order.展开更多
Imagine a place where you can enjoy your favorite cup of coffee in the company of dozens of koi fish as they swim through ankledeep water that covers the entire floor.That's Thailand's koi fish café.Remem...Imagine a place where you can enjoy your favorite cup of coffee in the company of dozens of koi fish as they swim through ankledeep water that covers the entire floor.That's Thailand's koi fish café.Remember Amix Coffee,the“flooded café”of Ho Chi Minh City,where hundreds of decorative fish of all shapes and sizes lived on the watercovered floor as customers walked among them?展开更多
Objectives:The objective of this study was to examine communication effectiveness(CE)in conjunction with participant satisfaction in a multicultural fitness program.Methods:Adults from a fitness program site with part...Objectives:The objective of this study was to examine communication effectiveness(CE)in conjunction with participant satisfaction in a multicultural fitness program.Methods:Adults from a fitness program site with participant diversity and multicultural backgrounds were selected and asked to complete a three-part Fitness CE Evaluation Scale questionnaire:CE Questionnaire and Customer Satisfaction(CS)Scale plus a short demographic survey.A sample of 95 participants was recruited from a Midwest Functional 45 Fitness Training Program site in the U.S.A.Multivariate Analysis of Variance(MANOVA)tests were conducted for CE and CS variable vectors.Results:The results showed that there were significant main effects on CE and CS for nationality(p=0.001;p<0.001)and language(p=0.006;p<0.001),but no effect for participation frequency,respectively;there were also significant main effects on CS for gender(p=0.006)and membership type(p=0.019).Univariate tests revealed that domestics and/or first language participants scored significantly higher on reactionto strangers(p=0.001;p=0.001),uncertainty(p<0.001;p<0.001),facilities/services(p<0.001;p<0.001),individual/psychological factor(p=0.009;p=0.034),relaxation(p=0.018;p=0.021),social factor(p<0.001;p=0.002),and health/fitness(p<0.001;p=0.001),respectively.Conclusions:Being highly aware of fitness participants’uncertainty and reaction to strangers can help multicultural fitness program managers or trainers improve their communication effectiveness,which will continue improving their customers’satisfaction.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
In the rapidly evolving landscape of natural language processing(NLP)and sentiment analysis,improving the accuracy and efficiency of sentiment classification models is crucial.This paper investigates the performance o...In the rapidly evolving landscape of natural language processing(NLP)and sentiment analysis,improving the accuracy and efficiency of sentiment classification models is crucial.This paper investigates the performance of two advanced models,the Large Language Model(LLM)LLaMA model and NLP BERT model,in the context of airline review sentiment analysis.Through fine-tuning,domain adaptation,and the application of few-shot learning,the study addresses the subtleties of sentiment expressions in airline-related text data.Employing predictive modeling and comparative analysis,the research evaluates the effectiveness of Large Language Model Meta AI(LLaMA)and Bidirectional Encoder Representations from Transformers(BERT)in capturing sentiment intricacies.Fine-tuning,including domain adaptation,enhances the models'performance in sentiment classification tasks.Additionally,the study explores the potential of few-shot learning to improve model generalization using minimal annotated data for targeted sentiment analysis.By conducting experiments on a diverse airline review dataset,the research quantifies the impact of fine-tuning,domain adaptation,and few-shot learning on model performance,providing valuable insights for industries aiming to predict recommendations and enhance customer satisfaction through a deeper understanding of sentiment in user-generated content(UGC).This research contributes to refining sentiment analysis models,ultimately fostering improved customer satisfaction in the airline industry.展开更多
This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy dema...This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.展开更多
Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a ...Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.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
To deal with the data mining problem of asymmetry misclassification cost, an innovative churn prediction method is proposed based on existing churn prediction research. This method adjusts the misclassification cost b...To deal with the data mining problem of asymmetry misclassification cost, an innovative churn prediction method is proposed based on existing churn prediction research. This method adjusts the misclassification cost based on the C4. 5 decision tree as a baseline classifier, which can obtain the prediction model with a minimum error rate based on the assumption that all misclassifications have the same cost, to realize cost-sensitive learning. Results from customer data of a certain Chinese telecommunication company and the fact that the churners and the non-churners have different misclassification costs demonstrate that by altering the sampling ratio of churners and non-churners, this cost-sensitive learning method can considerably reduce the total misclassification cost produced by traditional classification methods. This method can also play an important role in promoting core competence of Chinese telecommunication industry.展开更多
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To address the current situation where many small enterprises lack efficient management of customer data, this paper proposes a design and implementation plan of a customer relationship management (CRM) system based on email service. It aims to solve the problems of data dispersion, untimely update and information redundancy in customer management of small and medium-sized enterprises. The system includes four core functional modules: historical email analysis, lead pool management, customer management and email archiving. Through email mining and web crawler technology, the system can extract potential customer information from historical emails and enrich lead data;the lead pool management module supports lead information maintenance, status tracking and conversion of high-value leads;the customer management module realizes the maintenance and dynamic tracking of customer information;the email management module provides the archiving of emails and attachments and the structured storage of basic email information. The system provides automated and intelligent customer information management, improves the work efficiency of sales staff, and provides an efficient customer relationship management solution for enterprises.
文摘Purpose:Service convenience explores how consumers perceive the time and effort associated with purchasing or using a service.It examines the impact of convenience on customer satisfaction,loyalty,and behavioral intentions,often considering various dimensions like access,search,and transaction convenience.The reviews also investigate how service convenience interacts with other factors like service quality,perceived value,and customer satisfaction.Therefore,this paper seeks to analyze the dispersed academic literature on service convenience research.This paper reviews the existing literature on service convenience and examines the directions in which the past studies have focused.It highlights the gap in existing literature to identify future research directions in service convenience domain.Through this review,this study aims to gain insights into various aspects including research methodology,framework,trends,important factors related to service convenience.Design/methodology/approach:Data were collected from an objective overview of service convenience research.This study used a systematic literature review approach.A total of 13 papers were published between 2012 and 2024.Selected from the Scopus database,and Emerald Insight,following specific criteria outlined in the PRISMA process.Findings:In the context of customer satisfaction research,analysis often reveals that satisfaction can be organized into several main themes.Here are five variables that frequently appear in on customer satisfaction,customer loyalty,behavioral intentions,often considering various dimensions like access,search,and transaction convenience.The analysis shows a significant spike in conveniencebased accounting research from 2012 to 2024,indicating growing interest in the topic.
文摘The Italian textile machinery sector,renowned for its technological excellence and innovative capacity,continues to navigate a complex global market with a strategic emphasis on digitalization,sustainability,and strong customer partnerships.Marco Salvade’,President of ACIMIT,provided insights into the industry’s performance,key trends,and future directions.In the first quarter of 2025,Italian textile machinery exports saw a 6%decrease compared to the same period in 2024,totaling€363 million.This dip reflects ongoing geopolitical tensions and a cautious approach among global clients toward new investments.Despite these challenges,Italian manufacturers maintain a strong reputation for technological leadership and resilience.
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.
文摘Dove’s 2017 advertising incident,which sparked widespread debate regarding perceived cultural insensitivity,highlighted a disconnect between the brand’s“Real Beauty”positioning and public reception.In response,this study proposes a strategic digital recovery framework,including revised campaign content,transparent communication through social media,and data-driven customer segmentation based on diverse skincare needs and cultural backgrounds.A PESTLE analysis underscores the importance of digital transformation and rising social consciousness in brand management.Findings suggest that inclusive messaging,precision targeting,and omnichannel digital engagement are key to restoring brand trust and reputation in the digital landscape.
基金supported by the following projects:The Youth Project of the National Natural Science Foundation of China(NSFC)“Research on Chinese Multinational Companies’Componovation under Resource Constraint:From a Dynamic Circulation Logic of Home and Host Countries”(Grant No.72102030)The Research Project of Humanities and Social Sciences of the Ministry of Education“Research on Chinese Multinational Companies’Learning by Doing Mechanism under Resource Constraint”(Grant No.21C10173022)The General Project of the China Postdoctoral Science Foundation“Research on the Realization Path and Motivations for the Domestic Replacement of Core Technologies for Chinese Manufacturing Enterprises”(Grant No.2022M720975).
文摘Hidden champions play a critical role in China’s efforts to overcome technological and industrial“chokepoints”.These enterprises are pivotal for breaking free from Western technological embargoes,avoiding entrapment in low-value-added production,and driving industrial upgrading.Given the distinct market environment in which China’s hidden champions have emerged,it is both timely and practically significant to examine their growth trajectories and underlying mechanisms.This study adopts a resource allocation perspective to investigate the development path of Chinese manufacturing enterprises into hidden champions,using a vertical case study of Hailiya Group.The findings reveal that such enterprises achieve hidden champion status by vertically concentrating on niche markets while harnessing technological potential and horizontally diversifying their technology application scenarios.Their growth follows a“T-shaped”strategy,combining vertical specialization in a focused market with horizontal expansion into new applications.Four critical mechanisms underpin the rise of manufacturing hidden champions:market niche positioning,innovation-driven focus,application scenario expansion,and ecosystem development.Specifically,these enterprises strategically target niche markets,establish a technology-oriented competitive edge,broaden technology applications to unlock new profit opportunities,and develop collaborative ecosystems to share resources and drive industrial advancement.This paper not only extends the interpretive boundaries of resource allocation theory but also offers fresh insights into the emergence of Chinese manufacturing enterprises as hidden champions,enriching our understanding of their unique growth dynamics.
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“This durian smells amazing!What variety is it?”“Do you offer any discounts for buying ice cream in bulk?”“One durian pizza and one portion of fresh durian,please!”At a tropical-themed shop in Nanning East Station,a chorus of customer questions filled the air.Student clerks smiled as they answered inquiries,swiftly packing each order.
文摘Imagine a place where you can enjoy your favorite cup of coffee in the company of dozens of koi fish as they swim through ankledeep water that covers the entire floor.That's Thailand's koi fish café.Remember Amix Coffee,the“flooded café”of Ho Chi Minh City,where hundreds of decorative fish of all shapes and sizes lived on the watercovered floor as customers walked among them?
基金funded by Department of Education of Guangdong Province(NO.2022GXJK239,2024SQXX_025)Guangzhou Sport University(NO.XGQN202410).
文摘Objectives:The objective of this study was to examine communication effectiveness(CE)in conjunction with participant satisfaction in a multicultural fitness program.Methods:Adults from a fitness program site with participant diversity and multicultural backgrounds were selected and asked to complete a three-part Fitness CE Evaluation Scale questionnaire:CE Questionnaire and Customer Satisfaction(CS)Scale plus a short demographic survey.A sample of 95 participants was recruited from a Midwest Functional 45 Fitness Training Program site in the U.S.A.Multivariate Analysis of Variance(MANOVA)tests were conducted for CE and CS variable vectors.Results:The results showed that there were significant main effects on CE and CS for nationality(p=0.001;p<0.001)and language(p=0.006;p<0.001),but no effect for participation frequency,respectively;there were also significant main effects on CS for gender(p=0.006)and membership type(p=0.019).Univariate tests revealed that domestics and/or first language participants scored significantly higher on reactionto strangers(p=0.001;p=0.001),uncertainty(p<0.001;p<0.001),facilities/services(p<0.001;p<0.001),individual/psychological factor(p=0.009;p=0.034),relaxation(p=0.018;p=0.021),social factor(p<0.001;p=0.002),and health/fitness(p<0.001;p=0.001),respectively.Conclusions:Being highly aware of fitness participants’uncertainty and reaction to strangers can help multicultural fitness program managers or trainers improve their communication effectiveness,which will continue improving their customers’satisfaction.
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.
文摘In the rapidly evolving landscape of natural language processing(NLP)and sentiment analysis,improving the accuracy and efficiency of sentiment classification models is crucial.This paper investigates the performance of two advanced models,the Large Language Model(LLM)LLaMA model and NLP BERT model,in the context of airline review sentiment analysis.Through fine-tuning,domain adaptation,and the application of few-shot learning,the study addresses the subtleties of sentiment expressions in airline-related text data.Employing predictive modeling and comparative analysis,the research evaluates the effectiveness of Large Language Model Meta AI(LLaMA)and Bidirectional Encoder Representations from Transformers(BERT)in capturing sentiment intricacies.Fine-tuning,including domain adaptation,enhances the models'performance in sentiment classification tasks.Additionally,the study explores the potential of few-shot learning to improve model generalization using minimal annotated data for targeted sentiment analysis.By conducting experiments on a diverse airline review dataset,the research quantifies the impact of fine-tuning,domain adaptation,and few-shot learning on model performance,providing valuable insights for industries aiming to predict recommendations and enhance customer satisfaction through a deeper understanding of sentiment in user-generated content(UGC).This research contributes to refining sentiment analysis models,ultimately fostering improved customer satisfaction in the airline industry.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.
基金The National Natural Science Foundation of China(No.61074147)the Natural Science Foundation of Guangdong Province(No.S2011010005059)+2 种基金the Foundation of Enterprise-University-Research Institute Cooperation from Guangdong Province and Ministry of Education of China(No.2012B091000171,2011B090400460)the Science and Technology Program of Guangdong Province(No.2012B050600028)the Science and Technology Program of Huadu District,Guangzhou(No.HD14ZD001)
文摘Considering that the vehicle routing problem （VRP） with many extended features is widely used in actual life, such as multi-depot, heterogeneous types of vehicles, customer service priority and time windows etc., a mathematical model for multi-depot heterogeneous vehicle routing problem with soft time windows （MDHVRPSTW） is established. An improved ant colony optimization （IACO） is proposed for solving this model. First, MDHVRPSTW is transferred into different groups according to the nearest principle, and then the initial route is constructed by the scanning algorithm （SA）. Secondly, genetic operators are introduced, and crossover probability and mutation probability are adaptively adjusted in order to improve the global search ability of the algorithm. Moreover, the smooth mechanism is used to improve the performance of the ant colony optimization （ACO）. Finally, the 3-opt strategy is used to improve the local search ability. The proposed IACO was tested on three new instances that were generated randomly. The experimental results show that IACO is superior to the other three existing algorithms in terms of convergence speed and solution quality. Thus, the proposed method is effective and feasible, and the proposed model is meaningful.
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.
文摘To deal with the data mining problem of asymmetry misclassification cost, an innovative churn prediction method is proposed based on existing churn prediction research. This method adjusts the misclassification cost based on the C4. 5 decision tree as a baseline classifier, which can obtain the prediction model with a minimum error rate based on the assumption that all misclassifications have the same cost, to realize cost-sensitive learning. Results from customer data of a certain Chinese telecommunication company and the fact that the churners and the non-churners have different misclassification costs demonstrate that by altering the sampling ratio of churners and non-churners, this cost-sensitive learning method can considerably reduce the total misclassification cost produced by traditional classification methods. This method can also play an important role in promoting core competence of Chinese telecommunication industry.
