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
“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
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
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 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
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
In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to...In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to measure customer lifetime value(CLV)as the basis for determining long-term firm performance,and we provide an empirical analysis of the relationship between omni-channel retailing and CLV.The results suggest that omni-channel retailing may effectively enhance CLV.Further analysis reveals that this process is influenced by heterogeneous consumer requirements and that significant differences exist in the extent to which the omni-channel transition may influence CLV depending on consumer preferences for diversity of commodities,sensitivity to the cost of contract performance,and sensitivity to warehousing costs.Hence,retailers should provide consumers with a complete portfolio of goods and services based on target consumers’heterogeneous requirements in order to increase omni-channel efficiency.展开更多
Urging avowed appreciation of peace and people-to-people ties among folk through the stark images compiled in a World War II photo album is the personal mission of one American man.Ashiver ran through Evan Kail at the...Urging avowed appreciation of peace and people-to-people ties among folk through the stark images compiled in a World War II photo album is the personal mission of one American man.Ashiver ran through Evan Kail at the sight of photos-in an album sent to him by a customer in 2022-of corpses,some scattered,others in piles,on a city street.The caption,“Nanjing Road”instantly evoked for him the infamous Nanjing Massacre of 1937-38,when the Japanese soldiers murdered 300,000 or more Chinese civilians and soldiers.Cognizant of the Japanese government’s obdurate denial of this atrocity,Kail took it upon himself to publicize and preserve these images by donating the album to China.展开更多
The aviation industry is a sector that is developing, changing and growing every day in terms of technological and legal framework. There are generally three factors that enable airlines to hold on to the market. Thes...The aviation industry is a sector that is developing, changing and growing every day in terms of technological and legal framework. There are generally three factors that enable airlines to hold on to the market. These factors are safety, service quality and price. Airline companies can analyze the customers in the market with a focus on price and quality and develop a business model according to their expectations. For example, business class and economy class passenger expectations are different from each other, so the service and price to be offered to them will be different. However, all customers have one common expectation and that is safety. No matter how high quality the service is or how cheap the price is, no one wants to fly with an airline or plane that is not safe. From an airline company’s point of view, an accident or breakdown of one of the company’s aircraft can cause irreparable image loss and financial damage. If we look at past examples, we see that there are many airline companies or maintenance organizations that could not recover after an accident and went bankrupt. Safety is an indispensable factor. Therefore, there is a unit in the sector called the safety management system (SMS), which collects data by taking a proactive and reactive approach. The way and purpose of the safety management system is to take a proactive approach to recognize and prevent unsafe situations before they cause accidents or breakdowns, or to take a reactive approach to find the causes of accidents and breakdowns that have occurred as a result of certain factors and to take the necessary measures to prevent the same situations from happening again in the sector. The field of data mining, which is necessary to predict the future behavior of customers in the field of marketing, is an area that marketing also values. In this study, data mining studies to ensure safety in the aviation industry and the security of customer information in marketing will be emphasized, firstly, the concept and importance of data mining will be mentioned.展开更多
Even though people approach a new technological development with distance, they have to use these technologies in order to keep up with the requirements of the age. As a result of the rapidly developing artificial int...Even though people approach a new technological development with distance, they have to use these technologies in order to keep up with the requirements of the age. As a result of the rapidly developing artificial intelligence and technology sector, the concept of metaverse is a virtual world that can be used in the health, tourism, marketing, advertising, education and gaming industries. When the literature is reviewed, it is seen that there are many domestic and foreign sources on the subject, but most of these sources are generally related to developments in the gaming and entertainment sectors. But apart from this, studies are being carried out to make it possible to use it in many sectors, including its use in the health sector. With this study, it is aimed to briefly mention what the existing metaverse studies are and to prepare a detailed research result for its use in the health sector. This study consists of five chapters. In the first part, information on the definition of the metaverse concept and how it has developed is given, and the infrastructure requirements necessary for the formation of the metaverse universe are mentioned. In the second section, it is discussed what kind of hardware and software tools may be needed if metaverse technology is possible. In the third section, research on the areas in which metaverse technology can be used in the health sector and current studies and future studies are included. In the fourth section, the legal aspects of this situation when a metaverse-based health service is to be initiated with twin avatars are discussed. In the last section, the advantages and disadvantages of metaverse technology are discussed. It can be seen from the study that the positive aspects of this kind of activity in the field of health will be more positive. As a result, the study constitutes an important value that will be a source for similar studies to be conducted in the future.展开更多
Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and,after that,end their connection with the bank.Therefore,customer retention is es...Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and,after that,end their connection with the bank.Therefore,customer retention is essential in today’s extremely competitive banking market.Additionally,having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele.These factors make reducing client attrition a crucial step that banks must pursue.In our research,we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers.We use various machine learning algorithms to analyze the data and show comparative analysis on different evaluation metrics.In addition,we developed a Data Visualization RShiny app for data science and management regarding customer churn analysis.Analyzing this data will help the bank indicate the trend and then try to retain customers on the verge of attrition.展开更多
Managing customer retention is critical to a company’s profitability and firm value.However,predicting customer churn is challenging.The extant research on the topic mainly focuses on the type of model developed to p...Managing customer retention is critical to a company’s profitability and firm value.However,predicting customer churn is challenging.The extant research on the topic mainly focuses on the type of model developed to predict churn,devoting little or no effort to data preparation methods.These methods directly impact the identification of patterns,increasing the model’s predictive performance.We addressed this problem by(1)employing feature engineering methods to generate a set of potential predictor features suitable for the banking industry and(2)preprocessing the majority and minority classes to improve the learning of the classification model pattern.The framework encompasses state-of-the-art data preprocessing methods:(1)feature engineering with recency,frequency,and monetary value concepts to address the imbalanced dataset issue,(2)oversampling using the adaptive synthetic sampling algorithm,and(3)undersampling using NEASMISS algorithm.After data preprocessing,we use XGBoost and elastic net methods for churn prediction.We validated the proposed framework with a dataset of more than 3 million customers and about 170 million transactions.The framework outperformed alternative methods reported in the literature in terms of precision-recall area under curve,accuracy,recall,and specificity.From a practical perspective,the framework provides managers with valuable information to predict customer churn and develop strategies for customer retention in the banking industry.展开更多
The ideal solution for the production of classic polo shirts is Belairo air spun yarn,produced on the Autoairo 11 air-spinning machine.It fulfils all customer requirements in terms of durability and environmental comp...The ideal solution for the production of classic polo shirts is Belairo air spun yarn,produced on the Autoairo 11 air-spinning machine.It fulfils all customer requirements in terms of durability and environmental compatibility and significantly reduces the costs of spinning mills.展开更多
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.
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?
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.
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.
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the National Social Science Foundation of China(NSSFC)“Study on the Digital Transition of China’s Retail Business”(Grant No.18BJY176).
文摘In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to measure customer lifetime value(CLV)as the basis for determining long-term firm performance,and we provide an empirical analysis of the relationship between omni-channel retailing and CLV.The results suggest that omni-channel retailing may effectively enhance CLV.Further analysis reveals that this process is influenced by heterogeneous consumer requirements and that significant differences exist in the extent to which the omni-channel transition may influence CLV depending on consumer preferences for diversity of commodities,sensitivity to the cost of contract performance,and sensitivity to warehousing costs.Hence,retailers should provide consumers with a complete portfolio of goods and services based on target consumers’heterogeneous requirements in order to increase omni-channel efficiency.
文摘Urging avowed appreciation of peace and people-to-people ties among folk through the stark images compiled in a World War II photo album is the personal mission of one American man.Ashiver ran through Evan Kail at the sight of photos-in an album sent to him by a customer in 2022-of corpses,some scattered,others in piles,on a city street.The caption,“Nanjing Road”instantly evoked for him the infamous Nanjing Massacre of 1937-38,when the Japanese soldiers murdered 300,000 or more Chinese civilians and soldiers.Cognizant of the Japanese government’s obdurate denial of this atrocity,Kail took it upon himself to publicize and preserve these images by donating the album to China.
文摘The aviation industry is a sector that is developing, changing and growing every day in terms of technological and legal framework. There are generally three factors that enable airlines to hold on to the market. These factors are safety, service quality and price. Airline companies can analyze the customers in the market with a focus on price and quality and develop a business model according to their expectations. For example, business class and economy class passenger expectations are different from each other, so the service and price to be offered to them will be different. However, all customers have one common expectation and that is safety. No matter how high quality the service is or how cheap the price is, no one wants to fly with an airline or plane that is not safe. From an airline company’s point of view, an accident or breakdown of one of the company’s aircraft can cause irreparable image loss and financial damage. If we look at past examples, we see that there are many airline companies or maintenance organizations that could not recover after an accident and went bankrupt. Safety is an indispensable factor. Therefore, there is a unit in the sector called the safety management system (SMS), which collects data by taking a proactive and reactive approach. The way and purpose of the safety management system is to take a proactive approach to recognize and prevent unsafe situations before they cause accidents or breakdowns, or to take a reactive approach to find the causes of accidents and breakdowns that have occurred as a result of certain factors and to take the necessary measures to prevent the same situations from happening again in the sector. The field of data mining, which is necessary to predict the future behavior of customers in the field of marketing, is an area that marketing also values. In this study, data mining studies to ensure safety in the aviation industry and the security of customer information in marketing will be emphasized, firstly, the concept and importance of data mining will be mentioned.
文摘Even though people approach a new technological development with distance, they have to use these technologies in order to keep up with the requirements of the age. As a result of the rapidly developing artificial intelligence and technology sector, the concept of metaverse is a virtual world that can be used in the health, tourism, marketing, advertising, education and gaming industries. When the literature is reviewed, it is seen that there are many domestic and foreign sources on the subject, but most of these sources are generally related to developments in the gaming and entertainment sectors. But apart from this, studies are being carried out to make it possible to use it in many sectors, including its use in the health sector. With this study, it is aimed to briefly mention what the existing metaverse studies are and to prepare a detailed research result for its use in the health sector. This study consists of five chapters. In the first part, information on the definition of the metaverse concept and how it has developed is given, and the infrastructure requirements necessary for the formation of the metaverse universe are mentioned. In the second section, it is discussed what kind of hardware and software tools may be needed if metaverse technology is possible. In the third section, research on the areas in which metaverse technology can be used in the health sector and current studies and future studies are included. In the fourth section, the legal aspects of this situation when a metaverse-based health service is to be initiated with twin avatars are discussed. In the last section, the advantages and disadvantages of metaverse technology are discussed. It can be seen from the study that the positive aspects of this kind of activity in the field of health will be more positive. As a result, the study constitutes an important value that will be a source for similar studies to be conducted in the future.
文摘Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and,after that,end their connection with the bank.Therefore,customer retention is essential in today’s extremely competitive banking market.Additionally,having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele.These factors make reducing client attrition a crucial step that banks must pursue.In our research,we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers.We use various machine learning algorithms to analyze the data and show comparative analysis on different evaluation metrics.In addition,we developed a Data Visualization RShiny app for data science and management regarding customer churn analysis.Analyzing this data will help the bank indicate the trend and then try to retain customers on the verge of attrition.
文摘Managing customer retention is critical to a company’s profitability and firm value.However,predicting customer churn is challenging.The extant research on the topic mainly focuses on the type of model developed to predict churn,devoting little or no effort to data preparation methods.These methods directly impact the identification of patterns,increasing the model’s predictive performance.We addressed this problem by(1)employing feature engineering methods to generate a set of potential predictor features suitable for the banking industry and(2)preprocessing the majority and minority classes to improve the learning of the classification model pattern.The framework encompasses state-of-the-art data preprocessing methods:(1)feature engineering with recency,frequency,and monetary value concepts to address the imbalanced dataset issue,(2)oversampling using the adaptive synthetic sampling algorithm,and(3)undersampling using NEASMISS algorithm.After data preprocessing,we use XGBoost and elastic net methods for churn prediction.We validated the proposed framework with a dataset of more than 3 million customers and about 170 million transactions.The framework outperformed alternative methods reported in the literature in terms of precision-recall area under curve,accuracy,recall,and specificity.From a practical perspective,the framework provides managers with valuable information to predict customer churn and develop strategies for customer retention in the banking industry.
文摘The ideal solution for the production of classic polo shirts is Belairo air spun yarn,produced on the Autoairo 11 air-spinning machine.It fulfils all customer requirements in terms of durability and environmental compatibility and significantly reduces the costs of spinning mills.
