Call Center Agents Research Articles

Talent retention in Asian emerging markets: evidence from China and Malaysia

Purpose The purpose of this paper is to study talent retention, which has long been an important area of inquiry across many industries. Consistently, both academicians and practitioners have recommended several “posthire” solutions to retain employees, such as allowing employees to work from home, providing them with flexible work schedules, promoting a work–life balance and rewarding good performance. In this study, the authors focus on how the “prehire” career-related characteristics of call center agents and their personality traits relate to their turnover intentions. This is important because selecting the right person at the employee selection stage can prevent firms from trying to retain someone who is likely to quit his/her job. Design/methodology/approach The authors surveyed 442 employees working in the call centers of a major multinational logistics company across China and Malaysia and used covariance-based structural equation modeling (CB-SEM) to test the model. Findings The results showed that call center agents who reapplied for a job in the current company had lower turnover intentions than first-time applicants. Similarly, call center agents who provided supplementary information during their application had lower turnover intentions than the ones who did not provide any such information. As for the personality traits, the results indicated that while the call center agents’ agreeableness and openness to experience were positively associated with their turnover intentions, their consciousness and emotional stability were negatively associated with them. Originality/value This study shows the uniqueness of Asian emerging markets and the call center industry by presenting several interesting patterns that are different from those that have been found in other industries.

Artificial intelligence, emotional labor, and the quest for sociological and political imagination among low-skilled workers

Abstract This study examines how generative AI impacts low-skilled workers in their daily professional lives, how it changes the nature of their work, and what, if any, strategies they develop to cope with this new reality. Emphasis is placed on call center agents—an occupational group facing a particularly high automation risk. Drawing on Constructivist Grounded Theory and semistructured interviews in an Austrian call center, we uncover how flawed generative AI tools have increased emotional labor among these workers. This increase is hypothesized to result in agents’ inability to embed their own problems in the larger social context of generative AI’s impact on the labor market, let alone to politicize these problems. They were thus said to lack sociological and political imagination. Our study is the first to link emotional labor with these forms of imagination among low-skilled workers, offering new analytical tools for future research on generative AI’s nuanced effects on the labor market. To empower low-skilled workers, foster their imaginations and address their concerns, we propose several policy recommendations, including targeted education campaigns, enhanced social dialogue, co-determination rights, and tailored upskilling programs. This study thus offers a valuable contribution to scientific research while providing practical implications for policymakers.

Identification of Customer Through Voice Biometric System in Call Centres

In recent times, there has been a growing emphasis on adjusting communication strategies to foster strong customer relationships. This shift is driven by intensified competition, market maturation, and swift advancements in business technology. Consequently, companies have established call centers to efficiently handle customer support and fulfil customer inquiries. A pivotal aspect of enhancing service quality within these call centers involves accurately identifying customers during their interactions. The primary objective of this study is to introduce a methodology for identifying customers within call centers by analyzing their voice characteristics. Voice authentication (VA) has gained prominence in critical security operations, including banking transactions and conversations within call centers. The susceptibility of automatic speaker verification systems (ASVs) to deceptive spoofing attacks has prompted the development of countermeasures (CMs). These countermeasures are designed to differentiate between authentic and fabricated speech. ASVs and CMs collectively constitute contemporary VA systems, positioned as robust access control mechanisms. To achieve this goal, various customer identification systems within call centers have been examined, along with an analysis of audio signal attributes. Ultimately, the manuscript presents a novel approach to customer identification through voice biometrics. Notably, this method excels in recognizing customers even when provided with limited voice data. Empirical findings demonstrate that the suggested speaker identity confirmation method outperforms alternative techniques utilizing different algorithms, exhibiting a higher recognition rate. The present research work is based on two important perspectives of the call centres: a. call center agents experience and b. customer experience. The data collected separately from customers and agents for understanding the effective usage of voice biometric system in call centres. The data represented and satisfies the effectiveness of voice biometric system from both the perspectives. From the data it is also cleared that, the implementation of voice biometric system in call centres still have long way to go but will be a major technological change for the industries worldwide.

Emotional Dissonance and Coping Strategies According to the Emotional Processing Type of Call Center Counselors

Background: This study explored the emotional processing types of call center counselors and examined the differences in emotional dissonance and related adaptation indicates of coping strategies, emotional exhaustion and work performance orientation according to the types.Methods: A total of 271 call center agents (204 females, 67 males; mean age 36.5) participated in the study. Latent class analysis of emotional awareness, emotional expression, ambivalence over emotional expression were conducted. Analysis of variance(ANOVA) was used to examine differences in adaptation indicators according to emotion processing type.Results: Emotional processing types were categorized into Clear(CG), Passive(PG) Repressive(RG) groups. The CG showed low emotional dissonance, good adaptation indicates and functional coping strategies whereas results for the RG type revealed the opposite.Conclusions: By distinguishing between emotional processing types, this study found that emotional processing type is more closely correlated with burnout and work performance orientation than emotional dissonance itself.

Sugar-Sweetened Beverage (SSB) and Alcoholic and Caffeinated Beverage (ACB) Intake and Their Effect on the Sleep Quality of Selected Night Shift Call Center Agents Working in Mandaluyong City

Sugar-Sweetened Beverage (SSB) and Alcoholic and Caffeinated Beverage (ACB) Intake and Their Effect on the Sleep Quality of Selected Night Shift Call Center Agents Working in Mandaluyong City

English Pre-Service Teachers' Decisions on Working as Bilingual Agents at Call Centers and Their Perspectives for Future Employment

Currently, there is a growing trend for pre-service language teachers to work as bilingual agents due to the increase in call centers as a means of customer service. This research investigates the reasons why pre-service language teachers, choose to work as bilingual agents in call centers instead of pursuing a career in education as teachers of foreign languages which is part of the essence of their professional training. The results indicate that the main reasons for their interest were related to payment, flexible schedules, opportunities to improve their communicative competencies in the target language and enhance their cultural awareness. When asked about their future employment prospects, they expressed a desire to become language teachers. However, a significant group is uncertain about their decision to become teachers, and some are more interested in continuing to work as call center agents. Following a mixed research design, the researcher developed the present study integrating qualitative and quantitative data for more reliable results. Data was collected through semi-structured interviews, surveys and focus groups. Participants were 55 pre-service language teachers currently working as agents at a call center. The data was analysed using thematic analysis to identify categories that emerged. In addition, the research is comprehensively discussed, and the conclusions of the study are presented. The results obtained provide an opportunity for discussion and reflection on the conditions of teachers in educational contexts compared to other job offers.

A TRACER STUDY OF BACHELOR IN PUBLIC ADMINISTRATION GRADUATES FROM ACADEMIC YEAR 2018 TO 2023

This quantitative descriptive study aimed to determine the profile of the 118 Bachelor of Public Administration (BPA) graduates from the Academic Year 2018 to 2023 at Kapalong College of Agriculture, Sciences and Technology (KCAST). This tracer study involves the gathering of quantitative information through the use of online survey forms to get the necessary data, the study employed the descriptive quantitative technique of research. According to findings, 65% of graduates are currently employed, with the majority of them holding full-time jobs, the remaining 35% are not working yet because of their job preferences. Further, the results showed that 44% are working full-time, 25% are working on contractual basis, 10% in regular positions, 2% are working part-time, and another 1% are self-employed. Then, 43% are employed in the government, 18% as office-based clerk, 9% as sales agent/representatives, 18% as account specialist, 8% as marketing specialist, and the remaining 4% as call center agent. The level of attitude to work obtained a very high descriptive rating which means that the public administration graduates always manifested the said behavior. The quality education provisions of the institution as well as skills and abilities development obtained a high descriptive rating which means that the public administration graduates manifested the influence of the factor as extensive. It is recommended that to achieve the programs core academic goals and objectives, the institution should strengthen its connections, collaborations, and partnerships with other governmental and non-governmental organizations. KEYWORDS: descriptive-quantitative method, graduate tracer study, public administration study

A TRACER STUDY ON BACHELOR OF SCIENCE IN BUSINESS ADMINISTRATION - FINANCIAL MANAGEMENT GRADUATES FROM ACADEMIC YEAR 2019 TO 2023

This study aimed to assess the employment rates and employability status of graduates from the Bachelor of Science in Business Administration-Financial Management program at Kapalong College of Agriculture, Sciences, and Technology from 2019 to 2023. It also examined graduates attitudes towards work, the quality of education provided by the institution, and their skills development. Using a descriptive research method, a total of 587 respondents participated in an online survey conducted through Google Forms. Findings revealed that 88.17% of financial management graduates were employed, with 52.07% working in job-related professions such as credit & collection assistant, entrepreneur, cashier, auditor, bookkeeper, inventory personnel, accounting staff, and account officer. Additionally, 30.77% were employed in non-related fields including office-based clerk, government employee, sales agent/specialist/representative, call center agent, marketing specialist, technical staff, and photographer. Among the employed graduates, 37% held regular positions, 33% were on job order, 16% worked on a contractual basis, 8% were casual employees, and 6% were self-employed. Furthermore, only 0.85% pursued a Master in Business Administration, while 4.26% became teacher education unit earners. The study found that graduates consistently exhibited very high levels of attitude towards work, quality education provisions, and skills development. However, computer and ICT skills received the lowest mean score, suggesting a need for the program to offer practical training sessions, workshops, or laboratory sessions to enhance students proficiency in these areas. Providing opportunities for students to practice using computer software and applications in simulated business environments or real-world projects is recommended.

Model Lingkungan Kerja Fisik dan Motivasi Kerja Guna Meningkatkan Kinerja Karyawan

The physical work environment and work motivation are factors that impact an employee's performance. A quantitative research design and probability sampling are employed in the study. Techniques for gathering data include conducting interviews and distributing surveys. The data analysis approach interprets the table of output findings from the SPPS version 26 program using descriptive and associative methods and data analysis, specifically multiple regression analysis. The study's findings indicate that while work motivation has a partial impact on performance, the physical work environment has a partly zero influence. Additionally, the physical workspace and work motivation simultaneosly the performance of call center agent PT. XYZ Bandung City.

Strategic deception in call centers: impacts on well-being, cognition, and work motivation

The literature indicated that deceivers in face-to-face communication experience psychological strains derived from guilt or distress associated with violating conversational rules. We proposed that this also applies to telephone-mediated deception. Drawing insights from the theoretical and empirical literature, we surmised that strategic trickery utilized by outsourced call center agents would elicit adverse psychological reactions that have unfavorable impacts on their well-being, cognition, and work motivation. We used structural equation modeling to test our hypotheses using data from a sample of 554 outsourced Filipino call service agents who worked graveyard shifts to cater to mainly American customers. The results suggested that strategic deception increases the experience of cognitive dissonance while negatively impacting psychological well-being and intrinsic work motivation. The results also showed that dissonance negatively influences well-being and intrinsic motivation and partially mediates the deception-motivation relationship. Unlike previous findings, however, our multivariate analyses revealed that well-being and motivation were not correlated. Our original findings have theoretical and practical implications.

Work Training, Workplace Relationships, Workload and Job Performance

This study explores the optimization of job performance by examining the interplay of work training, workplace relationships, and workload within the dynamic setting of a call center. The overarching goal is to gain a holistic understanding of how these three elements collectively contribute to fostering a positive impact on workforce productivity. Utilizing a descriptive survey method, the research employed a questionnaire to systematically collect data on the perceived positive effects associated with work training, workplace relationships, and workload on job performance. Following data collection, thorough analysis and interpretation were conducted to derive meaningful insights. To assess the significance of differences between the factors influencing job performance, a one-way ANOVA was applied. The study aimed to shed light on several key aspects, including the dynamics of the work environment concerning the identified factors affecting job performance, the levels of agreement among respondents regarding these factors, significant differences in responses, and implications for improvements. In conclusion, the study highlights that work training, workplace relationships, and workload positively influence job performance, as evidenced by responses from call center agents. However, it is noteworthy that all three factors were rated one level below the highest possible classification, underscoring the need for targeted interventions. Significant differences in ratings were identified among work training, workplace relationships, and workload. All three factors were considered for intervention, with a particular emphasis on workload, which received the lowest rating. This prioritization sets the groundwork for strategic improvements to elevate overall job performance in the call center environment.

Practice Summary: Henkel Uses Analytics to Improve Call Center Performance

The development of a decision support tool to assist with call center agent scheduling at Henkel is described. Call center demand varies by hour, and agents have dissimilar service time distributions. Target agent utilizations are calculated using a metamodel of a simulation that finds the elbow of the utilization to waiting time curve.

Comprehensive Analysis of Kisan Call Centre in Tiruchirappalli District of Tamil Nadu, India

The farmer may come across a number of information sources but they pursue only few of them depending upon the availability and the ease of use. Countering the importance and facts in view the present study was undertaken in Trichy district. 90 farmers from Manachanallur block were selected using simple random sampling method. Majority of the respondents were middle aged and illiterate, most of them were marginal farmers with farming as sole occupation, had an annual income up to one lakh rupees. Majority of the respondents had moderate to strongly favorable attitude towards the use of Kisan Call Center and had medium knowledge about Kisan Call Center. Major constraints as perceived by respondents were, KCC is not providing the information regarding the seed, pesticide etc. of private agencies followed by SMS send by KCC not display in some of the mobile handsets there is no feedback facility in KCC. The suggestion that KCC agent should use conferencing system to solve the critical queries followed by the use of technical words should be replaced by local language by Call Center Agent.

Prevalence of social risks among cancer patients in an integrated health system.

195 Background: Social risks can lead to adverse cancer outcomes, including poor quality of life and increased mortality. These risks also contribute to health disparities and inequities, deepening needs for social care and support of cancer patients. Kaiser Permanente (KP) evaluated its social determinants of health (SDOH) questionnaires to assess the prevalence of social risks among cancer patients and members to design solutions that would address their social support needs. Methods: KP uses standard and non-standard SDOH questionnaires across markets to screen pediatric and adult members for social risk factors such as financial strain, housing instability, and social isolation. Screening is built into KP’s electronic health record (EHR), where the survey is administered by clinical staff, call center agents, or patients when logged into KP.org. SDOH screening data was collected between January 2021 to September 2022 for this analysis. Electronic Medical Record (EHR) and claims data were used to identify KP members with care associated with a cancer diagnosis between September 2017 to September 2022. Benign neoplasm and basal/squamous cell diagnoses were excluded. Results: There were 608K patients identified with visits associated with a cancer diagnosis in the 5-year period. Of these 608K cancer patients, 18% (n=109,773) were screened for social risk using standard and non-standard SDOH surveys. For comparable results across KP markets, standard questionnaires yielded 39% (n=7,507) presenting at least one positive social risk factor out of 19,274 cancer patients screened. Financial strain and social isolation were the most prevalent factors. Members across all major health plan products screened positive for at least one risk. When stratified by product, 65% (n=825) of Medicaid members screened were the highest observed group with at least 1 social risk, and commercial members screened were the second highest (40%, n=2,700). Cancer patients’ positive social risks were consistent with the overall screened population at 38% (n=102,392). Conclusions: KP cancer members yielded a similar measure of social risks as the general screened population, and the prevalence of these risks across major health plan products signals a call to action. The top social needs surfaced from this analysis informed how KP can support members by designing solutions that will provide access and referrals to appropriate resources. Deploying standardized social needs screenings and integrating them with clinical workflows are critical success factors. KP is building screening tools in multiple languages and will offer additional screening modalities to broaden equitable access. Though wide evidence demonstrates social factors have a major impact on health and well-being, more research is required to understand their effects on disparities, other dimensions of inequity, and health outcomes among cancer patients and members.

Suffering at Work or Neo-Taylorism that Leads to Resignation: Case of Two Professions in Tunisia

The objective of this article is to understand the path of suffering at work, in the Tunisian context, through a survey carried out on two professions in the private sector (agents in call centers, cashiers in supermarkets) to put highlight the patterns of this suffering through the singularities of the experience of individuals, while seeking the constants that cross these professions. This is an exploratory qualitative research which is situated in the interpretivist paradigm and where we interviewed 10 respondents by profession (20 semi-structured interviews). The results of the content analysis show an almost similar evolution of suffering for the two professions with a similar reaction to suffering: The resignation of call center agents and cashiers due to neo-Taylorism.

KisanQRS: A deep learning-based automated query-response system for agricultural decision-making

Delivering prompt information and guidance to farmers is critical in agricultural decision-making. Farmers’ helpline centres are heavily reliant on the expertise and availability of call centre agents, leading to inconsistent quality and delayed responses. To this end, this article presents Kisan Query Response System (KisanQRS), a Deep Learning-based robust query-response framework for the agriculture sector. KisanQRS integrates semantic and lexical similarities of farmers’ queries and employs a rapid threshold-based clustering method. Before clustering, KisanQRS employs data cleaning by performing steps such as the removal of special characters and extra white spaces. It also removes crop names from the queries, which helps in putting similar queries to the same clusters irrespective of the crop. Subsequently, semantic and lexical similarities of queries are computed, and a final similarity matrix is generated based on the weighted sum of these two similarities. Next, a clustering algorithm is applied to organize the queries into clusters according to their similarity. A query mapping module is trained on these cluster labels as the target. For this query mapping module, LSTM is found to be the optimal method. Next, the answer retrieval method clusters candidate answers for a crop, ranks these answer clusters based on the number of answers in a cluster, and selects the leader of each cluster, finally providing the top-K answers. The dataset used in our analysis consists of a subset of 34 million call logs from the Kisan Call Centre (KCC), operated under the Government of India. We evaluated the performance of the query mapping module on the data of five major states of India with 3,00,000 samples and the quantifiable outcomes demonstrate that KisanQRS significantly outperforms traditional techniques by achieving 96.58% top F1-score for a state. The answer retrieval module is evaluated on 10,000 samples and achieves a competitive NDCG score of 96.20%. KisanQRS could be useful in enabling farmers to make informed decisions about their farming practices by providing quick and pertinent responses to their queries.

Where are the customers’ bots? The AI paradigm shift in retail banking

Financial institutions are already using artificial intelligence (AI) to cut costs and deliver new services. Robo-advisers, chatbots and ‘copbots’ auto-detecting fraudulent transactions are increasingly common. These uses are undoubtedly valuable, but the business model is still the consumers being sold a financial product by a bank, whether by a call centre agent or a robot that impersonates a mortgage vendor. The big change in financial services will come when customers use AI to assess offers from financial institutions for themselves. They will have access to AI as powerful as the banks have, because Google, Facebook, Apple and Amazon (and companies like them) will be giving it to them. And this will mean individuals will not be the customers: their bots will be. Since most retail financial services offer products that just service a need at a point in time (eg paying for parking) rather than create an extraordinary user experience or are too complicated for normal people to make informed decisions about (eg pensions), we might expect most consumers to abdicate in favour of intelligent agents operating under the new duty of care umbrella. This has been a subject of futurist speculation for some time, but the rapid growth of ChatGPT and its ilk means that banks now have an urgent need to develop strategies to take advantage of this significant change in the nature of the financial services in the mass market. This paper looks at the imminent confluence of open finance and AI to consider the consequences of giving bots access to consumers’ cash (through open banking, for example). This will mean a world of smart wallets, capable of making decisions on behalf of consumers. They will be capable of deciding what services to use, who to get them from and how to maximise their financial well-being, leaving their users to spend more time on human activities.

Aspect-based automated evaluation of dialogues

Evaluating human dialogue is a complex task, as our conversation are never structured. There are, however, cases where there is some structure in our conversation, e.g., in a typical call centre, dialogue between a call centre agent and customer revolves around certain topics of conversation. These dialogues can be evaluated based on some pre-specified criteria as well as sub-criteria. This evaluation is typically done manually, which can be time-consuming, motivating the need for an automated system that employs Artificial Intelligence (AI) algorithms to evaluate dialogues efficiently. In this paper, we have proposed a novel dialogue-evaluation framework that leverages recent advancements in deep learning research. The contributions of this work are two fold. Firstly, we introduce a straightforward end-to-end framework – CallAI, for evaluating dialogues in any domain, based on some predefined hierarchical criteria. Secondly, we present a novel algorithm – TAABLM, utilizing a novel combination of aspect-based learning along with traditional TF-IDF features for text. We show in this paper, that TAABLM outperforms conventional baselines such as BERT, LSTM, etc, delivering improved performance in automated dialogue evaluation, whereas CallAI offers a simple yet elegant framework for an AI-based solution to hierarchical dialogue evaluation. We demonstrate the efficacy of our proposed framework and proposed algorithm on three datasets, where we quantify performance in terms of an aggregated dialogue-score as well as in terms of either accuracy or AuROC metrics.

If and to What Extent Does Organizational Learning Culture Predict Turnover Intentions of Telecommuting Call Center Agents?

This study focuses on measuring the relationship between organizational learning culture (OLC) and turnover intentions of telecommuting call center agents. Although many studies involve the call center industry from different perspectives, the literature is scant in studies that have assessed the relationship between OLC and turnover intent in telecommuting call center agents. Call centers exist in almost every organization worldwide. Organizations have centralized their customer service process through computer￾based technologies allowing call center agents to work from home. In addition, in the post-COVID-19 era, telecommuting has become a permanent option for many call center employees. Indeed, in the call center industry, telecommuting has become an essential part of the business strategy that seeks to attract new and maintain current employees. In the call center industry, learning is a factor that influences job satisfaction and turnover intentions. Specifically, OLC increases job satisfaction and performance in telecommuting call center agents, influencing employees’ turnover intentions. The study’s findings indicate that OLC is a needed factor that helps lower turnover intentions of telecommuting call center agents in the United States.

Investigation of the effect of the career management system and succession plan on employees' work stress and feelings of entrapment.

Work stress and feeling of entrapment are harmful physical and emotional results for employees when the workload demands exceed their capacities. This study aims to investigate the effects of the career management system and succession plan on employees' work stress and feelings of entrapment in hopes of improving employees' well-being to promote business continuity. In this cross-sectional study, the convenient sampling method was adopted. The research was conducted with the participation of call center agents (n = 621) of three call centers in Turkey. The Partial Least Squares Structural Equation Modeling (PLS-SEM) path analysis was performed on the collected data for hypothesis testing. Both career management systems (CMS) and succession plans (SP) reduce employees' work stress and feelings of entrapment. Work stress was found to mediate the effects of CMS and SP on the Feeling of Entrapment. The CMS reduces the work stress of employees with university degrees than those with a high school diploma. Meanwhile, SP reduces more of the feeling of entrapment for employees newly starting their jobs (with 0-2 years of seniority) than the workers with three or more years of seniority. Empirically, the feeling of entrapment seems higher among the employees with three or more years of seniority, suggesting that human resource management should focus on employees' work stress and feeling of job insecurity issues and offer possible and timely solutions. Furthermore, organizations showing care to newly arriving staff and giving them job assurance is believed crucial to improving employees' recruitment and retention.