Customer Service Representatives Research Articles

Generating a decision support system for states in the USA via machine learning

In literature, many studies try to analyze healthcare usage and generated decision support systems. In this paper, the aim is to generate a decision support system for insurance companies in the United States according to the federal dataset. The data set contains variables from the United States Healthcare Administration formal data group and they are; group of age, group of healthcare insurance, group of nationality, Corporate Social Responsibility (CSR) usage, and Advance Premium Tax Credit (APTC) usage. The best model for each state in the United States is determined with the dataset from 2014 November to 2015 February. In this study, various statistical models are attempted to generate independent and optimal models for each state. In the model selection process, three different metrics are used. Accuracy rate, f1score and precision score are used in the model selection process and models are compared to each other according to these three metrics for each state uniquely. Consequently, the proposed model is used with a decision support scheme to support customer service workers in healthcare insurance companies. The decision support system under consideration can facilitate a substantial decrease in the duration of interactions between customer service representatives and clients. Additionally, this system can generate more logically sound and efficient customer offers.

Insurance Discourse Analysis: Identifying Register Variables and Generic Stages in English Cross-border Complaint Calls

Interpersonal meaning-making resources are construed by customer service representatives (CSRs) and customers in call center telephone conversations. The purpose of the present study is to explore the contextual features—specifically, register variables and generic stages—that American customers and Filipino CSRs employ to create meaning potentials in cross-border insurance calls. The results of this study reveal that register variables, specific generic stages, and various lexicogrammatical choices play significant roles in call center negotiation. The theoretical framework used in this research is Systemic Functional Linguistics (SFL), which provides valuable insights into the study of text at the register level, including field, mode, and tenor, as well as semantically, in terms of metafunctions. A data set of over 2000 English conversations from an insurance call center in the Philippines was examined, and 20 longer complaint calls involving complex negotiations were carefully selected for transcription. These calls amounted to approximately four hours of talk, resulting in a total of 39,440 words, and the findings highlight the register variables and common generic stages observed in the analyzed calls. It is observed that customers frequently use the recount strategy in call center encounters. Recounts are typically used by the customer in the Objection stage and are associated with delayed refusal in generic stages, contributing to the formation of experiential meanings. It is hoped that the present study provides insights into call center discourse in the insurance industry by identifying the register and generic features of cross-border complaint calls.

การพัฒนารูปแบบศักยภาพของพนักงานในหน่วยปฏิบัติงานบริการลูกค้าสัมพันธ์ในยุคดิจิทัล

The objectives of this research were 1) to study the components of customer service employees’ potential in the digital age, 2) to develop a potential model of customer service employees in the digital age, and 3) to create a potential development manual of customer service employees in the Digital Age. This study integrated the methods of qualitative and quantitative researches. The participants were customer service representatives of customer service operation units of organizations, customers using the services and experiential experts in service business.The research tools were interview questions and questionnaires. The qualitative data were analyzed by using content analysis and the quantitative data were analyzed by using statistics of frequency, mean, percentage, standard deviation, and factor analysis. The results showed that the potential of customer service employees in the Digital Age composed of 70 variables. The developed potential model of the customer service employees in the Digital Age comprised 5 key components with 17 sub-components. The key components were as followed: 1. Organization, 2. Performance operation, 3. Services, 4. Information technology and Innovation, and 5. Employees’ attributes. The manual for potential development of customer service Employees in the Digital Age consisted of 2 parts: Part 1: Introduction and Part2: Guideline for employees’ potential development in customer service operation units in the Digital Age. Both the model and the manual were approved by the experts for the appropriateness in application to develop the employees’ potential in customer service operation units in the Digital Age.

Customer Service Ethics in the Metaverse: A Value-Sensitive Design Science Approach

The aim of this paper is to develop recommendations for the value-sensitive design of social virtual reality (VR) applications with respect to the interaction between customers and customer service representatives, considering the value-sensitive design approach. Based on a systematic literature search, 125 relevant hits could be found, which especially assigns the values of openness, security, and liability to problems and categorizes them into six problem areas. These values of openness, security, and liability and problem fields form the requirements for a value-sensitive design of social VR applications. Based on these requirements, preliminary design principles were derived in two evaluation cycles, each assessed using an online survey (Survey 1 with 221 participants and Survey 2 with 310 participants) and presented in the form of instantiation. One main finding of the paper can help counteract discrimination in social VR applications within the interaction between customers and customer service representatives.

From worker empowerment to managerial control: The devolution of AI tools' intended positive implementation to their negative consequences

AI tools are increasingly being deployed in organizations with the promise to support workers, enable faster and more accurate processes, and thus to contribute to enhanced organizational outcomes. However, in practice, the introduction of AI tools often fails to meet these expectations and results in negative consequences, such as worker resistance and dissatisfaction. Yet we have little understanding of the process of how and why initially positive design intentions of AI tools result in negative consequences. Building on a qualitative in-depth case study of a Chinese firm introducing an AI tool in sales, we found that whereas the AI tool's initial design seemingly intended to lead to salespeople's empowerment and first achieved respective outcomes, over time the tool was appropriated for managerial control. We show that this devolution emerged organically from a growing managerial awareness of the affordances that the AI tool offered managers to perform their work better. Our study contributes to the literature on AI by highlighting the potential dangers of AI tools and emphasizing the importance of including workers in the AI tool's design and implementation phases.

“But it’s truly aggravating and depressing”: Voicing counter-expectancy in US–Philippines service interactions

Intercultural competence is essential in a globalized business environment, where successful cross-border transactions rely on effective cross-cultural communication. Interactions between US customers and Filipino customer service representatives (CSR) in call centers are one example where intercultural competence is required. This study examines the use of counter-expectancy expressions in call center complaint calls by American consumers and Filipino CSRs in the insurance sector. This study used a Systemic Functional Linguistic (SFL) framework to examine the various linguistic realizations used in the dialogues, with a focus on appraisal theory. To further explore the connection between the use of business language, cultural norms, and the growth of intercultural competence, this study also considered Hofstede's cultural distinctions, as well as Hall's high-context and low-context cultures. Using a mixed approach, the present study examined 20 authentic audio recordings of complex insurance complaint calls (approximately four hours in length and containing 39,440 words). These spoken data were transcribed and analyzed for linguistic characteristics that indicated concessive expressions, for example, connectives such as “but” and “however”, and adjuncts such as “just” and “only”. The findings of this study have implications for language and cultural awareness training programs, and ultimately for enhancing intercultural communication skills in professional settings.

Hurdles to Knowledge Management Application in Enhancing Service Delivery at The National Land Commission Nairobi County, Kenya

Efforts to address the ongoing problem facing Kenyan communities may be summed up by the National Land Policy and the National Land Commission. The issue has exacerbated by the rapid transition from the traditional method of land ownership in Kenya, where land is held in common, to a scenario in which land is held by individuals and the affluent could gain an advantage over the poor without knowledge management and any pushback from the community. The study's focus was on the knowledge management practices used by the Kenya National Land Commission, with the ultimate goal of enhancing the quality of those practices and the services they provide to the general public. Therefore, the study sought to investigate hurdles to knowledge management application in improving service performance at the National Land Commission, Nairobi County. A descriptive survey methodology was used for this study. The sample size was 150 people including NLC managers, customer service representatives, secretaries and customers and it was selected using stratified random selection to ensure that it is representative of the institution as a whole. The study was able to gather both primary and secondary information through conducting surveys and scheduling interviews. Cronbach's alpha was utilized to determine the reliability of the research instruments in the Test-retest technique. Means, percentages, standard deviations, tables, and figures were used to display the findings of inferential and descriptive statistics performed on the gathered data in SPSS (version 23). The biggest barriers that hurt knowledge management implementations are awareness, time, and culture. Many KM programs struggle to gain traction because they aren’t marketed in a way that cuts through the noise and resonates with employees. The study recommends that the organizational management must understand where and in what forms knowledge exists. The organization need to create a culture that values and rewards knowledge sharing, providing employees with the tools and resources they need to share knowledge through knowledge management tools, training programs and communication channels. For the organization to achieve the goal of knowledge management practice, they should enable and promote a culture of learning and development, creating an environment where employees are encouraged to share information to better the collective workforce. The organization should brainstorm catchy terms and phrases to talk about KM, along with a logo or motto that aligns with the organization’s culture and values.

An Investigation of the Impact of Online Customer Service Burnout on Customer Experience in Malaysia

The article presented here involves examining the impact of online customer service burnout on customer experience, and also then to show how customer service burnout can be alleviated using the credible neural network and thus improving customer experience overall. A quantitative method was used which involved using a questionnaire to collect data from a sample of 384 respondents. The data that was collected were analyzed using SPSS. The hypothesis testing showed that H1, H2, H3, and H4 are accepted. The results showed that online customer service burnout did have a negative effect on customer experience and more importantly, the results highlighted the use of credible neural networks can reduce mental burnout among customer service representatives, thus contributing to a more positive customer experience. These results suggest that mental burnout of online customer service representatives which results in the deterioration of the customer service experience can be alleviated by credible neural networks. This is because these systems can reduce customer waiting times, handle large data volumes, reduce additional employee training, and reduce overall working time. These important attributes of the credible neural networks can generate lower mental burnout among customer service representatives and this will enable them to serve the customers much more efficiently thus improving customer experience. It was thus recommended for organisations implement credible neural networks to help supplement and support the work of customer service representatives working online remotely so that their performance can be enhanced and the customer experience can be improved. Credible neural network systems will be very beneficial to the employees by allowing them to carry out their work with less mental fatigue and this enables them to excel to higher levels, thus providing a superior customer experience.

The Effect of Immigrant Customer Service Representatives’ (ICSRs) Accents on Customers’ Experience and Satisfaction

This study shows that most customers are frustrated because of the unintelligible communication they usually have with Immigrants Customer Service Relations (ICSRs). Customers’ experience worsens when they find it difficult to understand the customer representatives they are communicating with because their accents make them unintelligible, causing communication breakdown. This study adopted the qualitative research approach. Frame Analysis (FA) and Discursive Social Psychological (DSP) methods were used to analyze Reddit online forum users’ responses to a peer’s question posed on the forum. It found that accents play a significant role in why some customers, using American customers as cases, are rude to ICSRs. Aside from this, it also found that other factors, such as the organizations’ systems—long wait times to access CSRs, network connection failures, inexperienced CSRs, and acts of racism affect customer experience.

Effect of AI Chatbot’s Interactivity on Consumers’ Negative Word-of-Mouth Intention: Mediating Role of Perceived Empathy and Anger

Although much research has examined chatbot interactivity as one of the most human-like qualities, replicating a conversation norm in human-to-human dialogue, far less has examined the "native state" of two-way communication between humans and chatbots. This study fills the gap by substantiating a synchronous two-way conversation between users and chatbots and testing how chatbot interactivity shapes the users’ perceived empathy. Guided by the computers-are-social-actors (CASA) paradigm, like skilled customer service representatives interacting with customers during product failures, this study designs a between-subject experiment (N = 300) to embody the warm and competent types of human conversation and suggests two versions of chatbot interactivities: social interactivity (high/low) and message interactivity (high/low). We further investigate whether a chatbot’s warm or competent persona manifested in its interaction with consumers elicits empathic responses from consumers, such as calming down their anger in line with social response theory. As a result, both social and message interactivity in chatbots effectively elicit users’ perception of empathy, alleviating customer anger and reducing adverse word-of-mouth (WOM) intentions. The findings provide empirical evidence that supports the explanatory framework of social response theory. This research demonstrates how technological features, particularly interactivity, contribute to creating experiential value for customers. Specifically, it elucidates how customers perceive empathy displayed by chatbots, which subsequently influences their level of anger and inclination to engage in negative word-of-mouth communication. Notably, these results offer novel insights into the roles of chatbot interactivity and empathy as psychological mechanisms that enable consumers to express their dissatisfaction by interacting with chatbot service agents, particularly in situations involving product failures. The implications of this study extend to the practical realm, providing valuable guidance on the design and implementation of empathetic chatbots in frontline consumer service contexts.

How does emotional intelligence influence self-efficacy among customer service representatives in Pakistan? Mediatory effects of emotional labour

PurposeThis study intends to explore the influence of emotional intelligence on employee self-efficacy in Pakistan's telecom industry. Besides, it explores the mediating effect of emotional labor (surface acting and deep acting) between them. This study also tests the relationship between emotional labor (surface acting and deep acting) and self-efficacy in the customer care of Pakistan's telecom division.Design/methodology/approachThe study leads forward with a positivist approach to obtain data in two different waves as a time lag study from the big five telecom companies operating in Pakistan. The data was collected from 270 employees working in Customer Services in the Telecom sector.FindingsThe results reveal that there exists a positive relationship between emotional intelligence and self-efficacy in customer care employees in Pakistan's telecommunication division sector. Moreover, emotional labor (deep acting) partially mediates the relationship between emotional intelligence and self-efficacy, and surface acting could not mediate the relationship among the employees of customer care in Pakistan's telecom division.Originality/valueManagement of emotions at the workplace has been an immensely vital area in managing the performance of employees, especially in customer-centric jobs, where dealing with customers is the prime focus and achieving customer satisfaction is the utmost outcome. There is limited evidence of the relationship between emotional intelligence and self-efficacy specifically in the customer care of the Telecom sector.

Sentimental Analysis on Webio Comments using Machine Learning

Sentiment analysis is a powerful technique that allows us to automatically classify the sentiment of a text into positive, negative or neutral categories. In this study, we explore the application of sentiment analysis on Webio comments using machine learning algorithms. Webio is a popular online platform that enables users to interact with chatbots and customer service representatives. By analysing the sentiment of Webio comments, businesses can gain value insights into customer satisfaction and identify areas of improvement in their products or services. We used a dataset of Webio comments and employed various machine learning algorithms, including Support Vector Machines(SVM), Naive Bayes(NB), and Random Forest(RF), to classify the sentiment of the comments. We evaluated the performance of the algorithms using metrics such as accuracy, precision, recall, and F1-score. Our results show that the SVM algorithm outperformed the algorithms, achieving an accuracy of 85% in classifying the sentiment of Webio comments. We also conducted feature selection experiments to identify the most important features in the classification task, and found that the presence of certain keywords and emoticons had a significant impact on sentiment classification. Overall, our study demonstrates the effectiveness of machine learning algorithms in analysing sentiment on Webio comments and provides insights into the features that are most indicative of sentiment in this context

Role of Rental Car Market in India: An Empirical Analysis

India's rental-car industry has grown to be an essential part of the nation's transportation infrastructure. The demand for rental automobiles has significantly increased in recent years as a result of growing urbanization, shifting consumer preferences, and rising disposable incomes. The function of the Indian rental-car market and its effects on various stakeholders are examined in this abstract. First off, the market for rental cars offers a practical and adaptable form of transportation, meeting the demands of both domestic and foreign tourists. It provides a large selection of vehicles, from affordable cars to high-end automobiles, guaranteeing solutions for any need and price range. Second, renting a car has emerged as a practical substitute for owning one, especially in crowded cities where parking is scarce and traffic is heavy. The growth of ride-hailing services and the shared economy have further exacerbated this trend, making rental automobiles a desirable choice for transient mobility needs. Thirdly, the rental automobile sector has given many people work opportunities, including drivers, customer service representatives, and maintenance employees. It has also aided in the expansion of related sectors including auto service and repair, petrol stations and insurance companies. But there are still issues to be solved, like the need for better infrastructure, legal frameworks, and assuring client happiness and safety. Overall, the Indian rental automobile industry is essential for offering practical and adaptable modes of transportation, boosting the nation's economy, and improving both business and leisure travellers' overall travel experiences.

GoPrintBot: An Interactive E-Commerce for Online Printing Services

GoPrintBot is an innovative endeavor focused on creating an interactive e-commerce chatbot tailored specifically for online printing services. The primary objective is to enhance the customer experience by offering a seamless and efficient ordering process, eliminating the need for customers to navigate complex websites or wait for customer service representatives. This study addresses common issues encountered in traditional e-commerce platforms, including unintuitive navigation, ineffective search and filter systems, and slow response times for customer inquiries. The proposed solution involves developing a chatbot system that will revolutionize the online printing industry, significantly improving the customer experience and operational efficiency. The methodology employed encompasses comprehensive requirements gathering, followed by the design and development of the chatbot system using established System Development Life Cycle (SDLC) methodologies. GoPrintBot serves as a prototype, showcasing the potential of chatbots to streamline the online printing process and provide personalized and efficient services. The findings of this study have significant implications for businesses that prioritize customer satisfaction and aim to optimize their online printing services.

Nǐ kànzhe bàn ba: negotiating complaint solutions in e-shopping service encounters

Abstract In Mandarin Chinese, the expression nǐ kànzhe bàn ba can be employed in either ‘you-decide use’ (you assess and decide by yourself), whereby the speaker disclaims his/her deontic authority to the recipient in decision-making, or ‘I-claim use’ (you have to assess and decide cautiously), whereby he/she claims a higher degree of deontic authority than the recipient when determining a proposed action. Focusing on the ‘I-claim use’ of nǐ kànzhe bàn ba, this study examines how this expression is manipulated by customers to negotiate solutions for their complaints with customer service representatives in Chinese e-shopping platforms. Utilising naturally occurring data from Taobao service encounters spanning about one year, this study employs a discursive approach and finds that this expression fulfills one of a number of pragmatic functions: (1) when there is no mutual agreement on the complaint proposals, the customers deploy it to upgrade their deontic authority to orient to their own unilateral solution and refrain from further negotiations; (2) when expressing a negative evaluation, the customers use it to pre-empt potential complainables that reflect their strong deontic authority; or (3) following non-substantive rectification on the part of the agent, the customers use it to express diluted deontic authority in order to display disaffiliation and solicit more substantive proposals. By analyzing the use of this expression in e-shopping service encounters, our study contributes to understanding how deontic authority is exercised in negotiating solutions to complaints.

The Transformation in Philippine BPO Companies: The Impact of Digital Workplace Transformation to the Front Office CSR in terms of their Work Culture

The workforce in various industries, particularly the BPO industry, experiences significant impacts from digital workplace transformation. It is affected by employee skill levels, knowledge, efficiency, and rationalization. This research aims to investigate the impact of digital workplace transformation on work culture, represented by the following variables: employee retention, motivation, and productivity. Participants in this study work as front-office customer service representatives (CSR) for business processing outsourcing (BPO) companies in the Philippines, specifically the top BPO companies on the list issued by the IT & Business Process Association of the Philippines (IBPAP). Using a mixed method approach, the researchers incorporated qualitative and quantitative data for this study, allowing them to compile all the necessary information. Using Somer's delta, the researchers identified the association between the dependent and independent variables. After analyzing the data, researchers found that the development of the digital workplace positively impacts work culture. At the same time, the shift to a digital workplace benefits worker productivity, motivation, and retention. On the contrary, with the interview results of the study conducted with the respective team leaders of these employees, the researchers discovered that despite the magnificent benefits of digital workplace transformation, it can still cause stress and work overload. In conclusion, our research findings contradicted our initial hypothesis that the digital workplace would not significantly impact work culture in BPO companies. Instead, we discovered that digital workplace transformation impacts employee retention, motivation, and productivity. The transformation to a digital workplace progressively enhances the quality of work performed by customer service representatives in BPO companies, leading to a better work experience. Researchers recommend that BPO companies focus on skills development, effective communication, work environment enhancements, and supervisor support to ensure a successful transformation.

RESEARCH ON VOICE QUALITY IN CALL CENTER DISCOURSE: VALIDATING RELIABILITY THROUGH INTERRATER AGREEMENT AND PRAAT

Voice quality is an important component of effective communication in call center conversations. A qualitative research methodology was used in the present study to examine how Filipino customer service representatives (CSRs) and American customers use voice quality features in call center discourse. A precise evaluation of voice quality features can aid in the development of effective communication strategies. Through interrater agreement, the present study aimed to validate the reliability of voice quality feature assessment. In this study, how Filipino CSRs and American customers' call center telephone conversations differed in terms of voice quality characteristics such as volume (Loud/Soft), pitch (High/Low), tension (Tense/Lax), and rhythm (Fast/Slow) was investigated. The conversation transcripts were examined using the aforementioned voice quality features. The transcriptions were then evaluated by three independent raters to determine interrater agreement. The findings revealed a high level of interrater agreement between the three raters of all voice quality features, with up to 0.8 in identifying voice quality changes in generic stages. In particular, a higher agreement was found in the assessment of specific voice quality features such as loudness, high pitch, and tension. Praat software was also used to aid in the analysis of some voice recordings to validate the interrater agreement reliability. The approach taken in the present study for assessing voice quality using interrater agreement and Praat software can improve service quality in the call center industry and provides a reliable and valid framework for future qualitative research in applied linguistics.

Managing indifferent customers: A phenomenological study of the experiences of customer service representatives

Managing indifferent customers: A phenomenological study of the experiences of customer service representatives

Performance Analysis of a Chunk-Based Speech Emotion Recognition Model Using RNN

Recently, artificial-intelligence-based automatic customer response system has been widely used instead of customer service representatives. Therefore, it is important for automatic customer service to promptly recognize emotions in a customer’s voice to provide the appropriate service accordingly. Therefore, we analyzed the performance of the emotion recognition (ER) accuracy as a function of the simulation time using the proposed chunk-based speech ER (CSER) model. The proposed CSER model divides voice signals into 3-s long chunks to efficiently recognize characteristically inherent emotions in the customer’s voice. We evaluated the performance of the ER of voice signal chunks by applying four RNN techniques—long short-term memory (LSTM), bidirectional-LSTM, gated recurrent units (GRU), and bidirectional-GRU—to the proposed CSER model individually to assess its ER accuracy and time efficiency. The results reveal that GRU shows the best time efficiency in recognizing emotions from speech signals in terms of accuracy as a function of simulation time.

Cross-Gender Interpersonal Meaning in Banking Product and Service Offerings

This study examines the realization of interpersonal meaning through the speech function of offering products and services carried out by male and female Customer Service Representatives in banking service activities. Although in the results of the study, it was found that the similarity of the dominant mood type was used, it was concluded that male and female CSR realized interpersonal meanings differently. This can be seen from the emergence of imperative forms by male CSR and the dominant use of my subject compared to other subjects as well as types of High Modalities, compared to female CSR which uses more product name subjects and medium modalities in offering banking products and services to their customers. The results of the study concluded that when offering products and services to customers, A man's CSR tends to show its identity as mentioned in gender theory, namely speaking with authority, direct, and placing oneself as a superior party, while female CSR in addition to offering products and services she also tends to show a desire to establish close relationships with her customers.