Search

This paper presents a case study of a book reduction project undertaken by an academic library. The project aimed to reduce the size of the library's monograph collection by 61% and maintain a relevant and accessible print collection that best serves the needs of its users. To achieve this goal, the library outsourced technical services work and relied on temporary student workers to assist in the project. The paper discusses the challenges faced in onboarding and training temporary workers, as they had varying levels of experience and lacked knowledge of library terminology. To address these issues, the library provided onboarding and training, regular 1 + 1 meetings, and the effective use of project management software. The use of data analysis provided by LibraryIQ allowed for an objective assessment of which items to retain or remove. While removing materials could have negative implications, the project's emphasis on clear communication and ongoing evaluation of the collection's relevance and accessibility ensured that the library continues to meet the evolving needs of its users. The paper highlights the importance of effective project management, clear communication, and ongoing evaluation in managing library collections. The project's strategies and insights can provide valuable guidance for other libraries looking to undertake similar collection management projects. [ABSTRACT FROM AUTHOR]

To help customers get quality feedback from the huge number of online reviews, online retailers attempt to generate evaluations from consumers of how helpful product reviews are. Drawing on signalling theory, this study proposes a comprehensive model to examine the influence of factors related to the reviewer (signaller), the review (signal) and the users (readers of the signal) on online review helpfulness via e‐commerce sites and apps. This study also includes the moderating role of product categories (goods/services) in the model. Data were collected from 466 Vietnamese respondents. Using a Smart Partial Lease Square 3.0, the outcomes indicate that online review information quality, online reviewer information credibility and two dimensions of receivers (e.g. users' attitudes towards information and information task‐fit) all have a significant influence on online review helpfulness; however, users' need for information has no impact on the helpfulness of online reviews. Interestingly, the product type (goods vs services) has a moderating effect between online review information quality/attitude towards information and online review helpfulness. This study contributes significantly to signalling theory and online review helpfulness by comprehensively incorporating three attributes that are paramount to online reviews: the review, the reviewer and the users. Additionally, the information is enriched by the investigation of the moderating effect of product categories (goods vs services) on the context of online review helpfulness. [ABSTRACT FROM AUTHOR]

The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This model is built on the transformer architecture, which enables it to process massive volumes of data and produce text that is both cohesive and illuminating. Service is a crucial component everywhere as it provides the basis for establishing client rapport and offering aid and support. In healthcare, the application of ChatGPT for patient service support has been one of the most significant advances in recent years. ChatGPT can help overcome language obstacles and improve patient satisfaction by facilitating communication with healthcare personnel and understanding of care. It can assist in enhancing the entire patient experience by offering personalised information and support to patients and making it more straightforward for them to communicate with healthcare professionals. Its goal can be to expedite and streamline service by promptly and accurately responding to customers. Businesses of all sizes increasingly use ChatGPT since it allows them to provide 24/7 customer support without requiring human contact. This paper briefly discusses ChatGPT and the need for better services. Various perspectives on improving customer and patient services through ChatGPT are discussed. The article also discussed the major key enablers of ChatGPT for refining customer and patient assistance. Further, the paper identifies and discusses the critical application areas of ChatGPT for customer and patient service. With its ability to handle several requests simultaneously, respond quickly and accurately to client questions, and gain knowledge from every interaction, ChatGPT is revolutionising customer and patient service. Its accessibility and compatibility with various communication channels make it a desirable solution for businesses looking to improve support. As technology advances, ChatGPT is positioned to become an essential tool for businesses wishing to provide speedy and customised service. Although ChatGPT may give convincing solutions, the chance of providing accurate and updated information poses a problem for its usage in service jobs that need accurate and up-to-date information. In future, various services will become better and more efficient due to ChatGPT and AI. [ABSTRACT FROM AUTHOR]

In health insurance markets with regulated competition, regulators face the challenge of preventing risk selection. This paper provides a framework for analyzing the scope (i.e., potential actions by insurers and consumers) and incentives for risk selection in such markets. Our approach consists of three steps. First, we describe four types of risk selection: (a) selection by consumers in and out of the market, (b) selection by consumers between high- and low-value plans, (c) selection by insurers via plan design, and (d) selection by insurers via other channels such as marketing, customer service, and supplementary insurance. In a second step, we develop a conceptual framework of how regulation and features of health insurance markets affect the scope and incentives for risk selection along these four dimensions. In a third step, we use this framework to compare nine health insurance markets with regulated competition in Australia, Europe, Israel, and the United States. [ABSTRACT FROM AUTHOR]

Telecommunications operators are tasked with enhancing service quality, reducing operational costs, and preserving customer privacy. This study presents an innovative application of large language models (LLMs) integrated with the LangChain technology framework, aimed at revolutionizing customer service in the telecom sector. The LangChain framework features a Knowledge Organizing Module and a Knowledge Search Module, both designed to refine customer support operations. The research develops an LLM‐based approach to improve the segmentation and organization of knowledge bases, tailored for the telecommunications industry. This approach ensures seamless integration with existing LLMs while preserving distinct knowledge domains, crucial for search accuracy. Additionally, the framework includes an advanced information security protocol with a robust filtering system that effectively excludes sensitive data from the model's outputs, enhancing data security. Empirical findings indicate that the ChatGLM2‐6B+LangChain model outperforms the baseline ChatGLM2, demonstrating heightened effectiveness in telecom‐specific tasks and outstripping even more sophisticated models like GPT‐4. The implementation of this LLM‐based framework within telecom customer service systems has significantly sharpened the precision of knowledge recommendations, as reflected by a dramatic increase in acceptance rates from 15% to 70%. [ABSTRACT FROM AUTHOR]

Purpose: With the great changes brought by information technology, there is also a challenge for the elderly's acceptance. This study aimed to determine the antecedents of elderly people's usage intention of financial artificial intelligent customer service (FAICS) and to examine the relationships between various factors and thus to help them better adapt to the digital age. Design/methodology/approach: A mixed method, including the qualitative and quantitative study, was utilized to explore answers of the research questions. As the qualitative study, the authors used semi-structured interviews and data coding to uncover the influencing factors. As the quantitative study, the authors collected data through questionnaires and tested hypotheses using structural equation modeling. Findings: The results of data analysis from interviews and questionnaires suggested that perceived anthropomorphism and virtual identity of elderly users have a positive impact on their perceived ease of use, and the perceived intelligence of elderly users positively influences their perceived ease of use, satisfaction and perceived usefulness. Additionally, the elderly's cognition age can moderate the effects of perceived usefulness and satisfaction on their usage intention of FAICS. Originality/value: This study contributes to the literature by taking the elderly group as the research participants and combining those influencing factors with technology acceptance model and information systems success model. The findings provide a basis for accelerating the promotion of FAICS and help address the problem that the elderly have difficulty adapting to a new technology. [ABSTRACT FROM AUTHOR]

Understanding the ubiquitous digitalization of everyday life and associated inequalities presupposes rich conceptualizations of the associated social dynamics. Accordingly, we investigate digital service domestication as a social dimension of people's lives, building on concepts that center users' everyday lives and agency. We adopt the perspective of people who find the use of digital services difficult and examine the hurdles they face when attempting access. Our data consists of semi-structured interviews with migrant women (N = 22) living in Finland, where most essential services are digitalized. The study highlights the societal boundedness of the participants' agency, which we maintain is a key dynamic of inequality. We classify digital services in four categories, interactive communication services; information, media, and entertainment services; private customer services, and public health and social welfare services. The first two are voluntary digital services that did not create insurmountable barriers for the participants, but enabled them to conduct action they valued. By contrast, essential private and public services require mastering more complicated service technologies, a foreign language, and complex contents. Our results highlight how diversity-blind essential digital services produce and reinforce inequalities. Our analysis emphasizes the need for researchers to consider the coercive dimensions of digitalization. [ABSTRACT FROM AUTHOR]

The extensive study was conducted to enhance the prediction of customer turnover in an online retail and distribution organization. The study combines data from surveys, consumer comments, and financial records to uncover themes from textual assessments using state-of-the-art methodologies. Methods such as Dirichlet Multilayer Perceptron Mixing, Latent Dirichlet Allocation and Random Sampling fall within this category. In addition to its usage for assessing geographic data for location-based consumer segmentation, DBSCAN is a crucial tool for this investigation. Model development for churn prediction and root cause analysis makes use of logistic regression and extreme gradient boosting. The statistical and practical benefits of the proposed paradigm are shown via comparison to existing options. A model's predictive efficacy may be evaluated using the area under the curve or the lift metric. The research also introduces the concept of "Consumer-driven energy-efficient WSNs architecture for Personalization and contextualization in E-commerce Systems," which suggests using wireless sensor networks (WSNs) to collect data efficiently, provide customized service and provide context for online purchases. Overall, the research demonstrates the effectiveness of machine learning in harnessing consumer input for strategic decision-making, illuminating the potential of creative sensor network integration in enhancing e-commerce personalization and contextualization. [ABSTRACT FROM AUTHOR]

In today's rapidly advancing digital era, service provider applications such as Grab have become an integral part of people's lives, especially in urban areas. Despite providing convenience in mobility and time efficiency, users of such applications often encounter challenges such as product non-compliance with what was promised, resulting in losses that require accountability from the business entities. In this context, Consumer Protection Law becomes crucial as the foundation for both parties in transactions. However, in reality, many consumers still struggle to obtain compensation for their losses, indicating the weak consumer protection, especially in electronic transactions, in Indonesia. This study aims to highlight the need for more effective protection for consumers so that their rights can be fulfilled. By analyzing regulations and business practices, this research aims to evaluate the level of existing protection and concludes that efforts to protect consumers need to be enhanced. The implication of this research is the need for collaborative efforts among the government, companies, and service platforms to improve consumer protection and enhance the quality of services and products offered to consumers. [ABSTRACT FROM AUTHOR]

Understanding users' exact feelings and enhancing enterprise customer relationship management depend heavily on emotion and sentiment analysis in intelligent customer service conversations. However, the research that is currently available analyzes either emotion or sentiment. This paper proposes a multi-task ensemble model that can perform multiple tasks of emotion and sentiment analysis simultaneously. This ensemble model via a multi-layer perceptron (MLP) network develops three deep learning models based on convolutional neural network (CNN), long short-term memory (LSTM), and gated recurrent unit (GRU) for predicting intelligent customer service dialogue emotion and sentiment analysis, including "emotion classification and intensity", "valence and arousal for emotion", "valence and arousal for sentiment", and "3-class categorical classification for sentiment". The underlying problems cover two granularity analysis (i.e., coarse-grained and fine-grained) in the intelligent customer service domain. Experimental results suggest that the proposed multi-task ensemble model outperforms the single-task framework, and the method performs well in emotion and sentiment analysis tasks in intelligent service conversation. [ABSTRACT FROM AUTHOR]

The use of AI chatbot applications with social media messengers aims to shape the 'online to offline' approach to chat-based purchases. Using a sequential mixed-methods approach, we examined customer experiences with and the uses and gratifications of AI chatbots, and the influence of customers' perceptions of service quality in AI-based customer services on favourable customer experiences, brand loyalty and purchase loyalty. Twenty-five online shoppers participated in our qualitative study, which was analysed using a thematic analysis. Subsequently, our quantitative study involving 423 online shoppers employed structural equation modelling. We identified that seeking an instant response, real-time information, fast navigation and transactions and useful advice and suggestions were the uses and gratifications of AI chatbots. Furthermore, customers' perceptions of empathy and automated responsiveness in AI chatbots were determinants of positive customer experiences with AI-based customer services. Favourable customer experiences with AI chatbots affected brand loyalty, which in turn influenced purchase loyalty. [ABSTRACT FROM AUTHOR]

Labour research in geography has long been fascinated with the role of affects and emotions in capitalism. This article foregrounds ambivalent moments when labour creatively uses affection and intimacy to make claims over autonomy and agency. Set against a backdrop of increasing automation of infrastructural work, we draw on interviews with personnel at Jakarta Soekarno‐Hatta Airport (CGK). In culturally situating these automations, we evince how the "heart" (or the Indonesian notion of curahan hati), with semblances to customer‐facing labour management practices, and other affective dispositions under neoliberal life, is repeatedly deployed to "fill in the gaps" for where automation may fail. We illuminate how these workers navigate wearying, uncertain, and demanding facilitation, security, and customer service situations by emphasising "heart‐to‐heart" relations, even as they stave off technology's encroachments (and withdrawals). This plastic automaticity offers a template by which the pressures of capital's technologisation could be relieved, beyond emotional labour. [ABSTRACT FROM AUTHOR]

This study explored the sources of value co-creation, co-destruction and co-recovery amid the COVID-19 outbreak using 415 online reviews of guests' experiences with Airbnb. Data analysis using the grounded theory approach identified two main sources: Airbnb's customer service and hosts' conduct. Four sub-themes (quality of interactions with customer service representatives, difficulties in achieving resolution, dissatisfaction or satisfaction with the resolution offered and costs incurred by the consumer) comprised the main theme of Airbnb's customer service. Two sub-themes (the role of the host's communication in service recovery and perceived unethical actions by the host) comprised the main theme of hosts' conduct. The findings indicate that collaborative engagement in the restoration of service failure by actors results in value co-recovery. [ABSTRACT FROM AUTHOR]

This paper presents a multimodal dialogue system with user personality adaptation and multiple nonverbal behavior generation for a conversational android robot that plays a customer service role in recommending travel plans. It is useful to estimate the user's personality to realize a dialogue system that adapts the dialogue strategy to individual users. To improve the user's impression of the conversation robot as a customer service agent, we must control the nonverbal behavior of the robot, such as its facial expressions and motions. Moreover, we need to design the dialogue strategy to provide information and make users enjoy the conversation by adding an ice-breaking step. Against this background, we develop a dialogue system prototype that adjusts the dialogue strategy based on the user's personality, as estimated by a pre-trained multimodal sensing model. Furthermore, we implement appropriate nonverbal behavior patterns for each situation, including the voice, motion, and facial expressions of the android robot, to provide it appropriate and polite service agent behaviors. A personality assessment game is introduced into the dialogue to prevent the user from becoming bored. The game plays an ice-breaking role in the dialogue. To let the user engage with the robot, we implement a complement to the user as a dialogue act. We evaluate the proposed multimodal dialogue system for customer service by means of participation in a dialogue robot competition. The fair evaluation results from 26 dialogue users who conversed with multiple systems show that the proposed dialogue system achieved the best score among 13 teams participating in the preliminary round of the competition, indicating that the user personality adaptation and various elements implemented in our dialogue system improve the dialogue experience of general users. The results of a third-party evaluation and multiple regression analysis show that natural response is the most important factor contributing to user impression. [ABSTRACT FROM AUTHOR]

This study examined the impact of university services on customers' (students') Emotional Brand Attachment (EBA) and Customer Citizenship Behaviors (CCB). The main reason for examining this association was to explore the role customer service generated EBA played in motivating students to exhibit voluntary and extra-role behaviors. Using 568 completed research questionnaires, the proposed hypotheses were tested using multiple regression analysis. In addition, mediation effect of EBA on customer service quality and CCB relationship were tested. The research findings indicated that reputation and academic aspects (primarily represented by teaching quality and student–faculty bonding) were most influential in creating EBA and subsequent willingness towards extra role and voluntary behaviors. The outcome of the mediation analyses showed that non-academic aspects (such as effective complaint resolution, IT support and administrative assistance) had a full mediating effect, whereas access and reputation had partial mediating effect, on students' citizenship behaviors. [ABSTRACT FROM AUTHOR]

In a competitive environment, satisfying the growing demand of customers for the quality of service of transport services, taking into account the economic interests of transport companies and service users is the most important task. Existing methods based only on the opinions of users do not fully take into account the interests of companies providing these services. To this end, the article analyzes the qualitative indicators of customer service provided by transport companies when providing them with various services. It has been established that the cost of organizing the service, the (lost) income, and the time lost by customers depend on the quality of service. This analysis is based on the queuing theory model. A method is proposed for determining the optimal value from an economic point of view of indicators of the quality of customer service. The method is based on minimizing a generalized indicator – reduced costs. This indicator takes into account, on the one hand, the interests of the company and, on the other hand, the interests of service users. The results obtained allow companies to choose the quality of customer service indicator and its optimal value for the provision of various services. [ABSTRACT FROM AUTHOR]

With the advent of AI, consumer-brand interactions are undergoing a dramatic transformation (Prikshat, Malik, and Budhwar, 2021). Consumer experience with AI is a lesser explored area of study. This research aims to examine how AI may be used in the retail industry to enhance the purchasing experience for AI users. With the trust-commitment theory and the service quality model as our inspiration, we developed our theoretical framework. Customers who have used a YouTube service powered by artificial intelligence were sent an online survey. Partial least squares-structural equation modeling was used to analyze the data (n=301 replies). Trust and relationship commitment was shown to play a pivotal role in moderating the connections between customers' evaluations of service convenience, individualization, and quality. We also discovered that trust is not the only factor that substantially influences relationship commitment and that relationship commitment acts as a mediator between service quality and AI-enabled customer experiences. This research fills a gap in the literature by identifying the direct influence of perceived convenience, personalization, and service quality on AI-enabled customer experience and the intermediary effects of trust and relationship commitment. Further, the research has real-world consequences for businesses that want to apply AI in the services they provide to YouTube subscribers. [ABSTRACT FROM AUTHOR]

Dysfunctional customer behavior is a cause of concern due to its short and long-term impact on both employees as well as organizations. This paper aims to present the moderating effect of dysfunctional customer behavior on the relationship between job crafting and job outcomes (job satisfaction, job stress, and emotional labor) in light of the conservation of resource theory. This cross-sectional study was comprised of 440 frontline customer service employees (345 males and 94 females) serving in shopping malls located in Islamabad and Rawalpindi, Pakistan. Results indicated a negative relationship of job crafting with job stress and a positive relationship with job satisfaction. Moreover, a positive relationship of dysfunctional customer behavior was found with job stress and emotional labor, and a negative relationship with job satisfaction was also found. Furthermore, it was found that dysfunctional customer behavior moderated the relationship of job crafting with job stress and emotional labor, but it didn’t moderate the relationship of job crafting with job satisfaction. This study concludes that dysfunctional customer behavior is a cause of concern as it impacts the job outcomes of employees. Organizations should empower employees by training them to enhance their resources. Future studies may check for mediational pathways to enrich this finding. [ABSTRACT FROM AUTHOR]

This paper addresses the dynamics of a two-product closed-loop supply chain with realistic assumptions on production capacity constraints. The closed-loop supply chain is also subject to unpredictable disruptions, which lead to the non-stationarity of customer demand. The factory employs a production control policy to decide the product type to be processed. We propose a novel production control policy, named the Adaptive Hedging Corridor Policy, which makes decisions on production capacity based on the demand evolution. The proposed strategy is compared with well-known production control policies widely used in literature, such as DDMRP. Simulation results demonstrate the benefits of implementing an adaptive production control as it enables the closed-loop supply chain to enhance customer service level and bullwhip effect. Additionally, a sensitivity analysis is provided to assess the influence of experimental factors on the performance. The analysis highlights the significance of return flows and manufacturing operations for the closed-loop supply chain. [ABSTRACT FROM AUTHOR]

Despite the increasing pressure to reduce working capital across many industries, many multinationals still optimize their inventory in the end-to-end supply chain in siloes. This leaves room for improving costs, customer service and working capital. This article explains the concept of multi-echelon inventory optimization and how to successfully implement it in your organization, along with best practices and lessons learned from a real life MEIO implementation in the CPG industry. [ABSTRACT FROM AUTHOR]

Many firms are beginning to replace customer service employees with bots, from humanoid service robots to digital chatbots. Using real human–bot interactions in lab and field settings, we study consumers' evaluations of bot-provided service. We find that service evaluations are more negative when the service provider is a bot versus a human—even when the provided service is identical. This effect is explained by consumers' belief that service automation is motivated by firm benefits (i.e. cutting costs) at the expense of customer benefits (such as service quality). The effect is eliminated when firms share the economic surplus derived from automation with consumers through price discounts. The effect is reversed when service bots provide unambiguously superior service to human employees—a scenario that may soon become reality. Consumers' default reactions to service bots are therefore largely negative but can be equal to or better than reactions to human service providers if firms can demonstrate how automation benefits consumers. [ABSTRACT FROM AUTHOR]

This article deals with the queuing-inventory system, composed of c junior servers, a senior server, two finite waiting halls, and an infinite orbit. On occasion, junior servers encounter challenges during customer service. In these instances, they approach the senior server for guidance in resolving the issue. Suppose the senior server is engaged with another junior server. The approaching junior servers await their turn in a finite waiting area with a capacity of c for consultation. Concerning this, we study the performance of junior servers approaching the senior server in the retrial queuing-inventory model with the two finite waiting halls dedicated to the primary customers and the junior servers for consultation. We formulate a level-dependent QBD process and solve its steady-state probability vector using Neuts and Rao's truncation method. The stability condition of the system is derived and the R matrix is computed. The optimum total cost has been obtained, and the sensitivity analyses, which include the expected total cost, the waiting time of customers in the waiting hall and orbit, the number of busy servers, and a fraction of the successful retrial rate of the model, are computed numerically. [ABSTRACT FROM AUTHOR]

Banks asfinancial institutions that rely on customer trust are obliged to continually improve service quality in order to maintain their role. In carrying out its business activities, banks have three main functions, including accepting money deposits, lending money, and providing money transfer services. One way to find out the condition of a company can be done by analyzing the annual financial reports made by the company. Financial reports are prepared with the aim of providing an overview of periodic progress reports carried out by the management of the company concerned. This research aims to find out the influence of equity, assets and liabilities on share prices with profitability as an intervening variable at PT Bank Syariah Indonesia in 2020-2022 . Sampling is a part of an overall population that is carefully selected to be representative of that population. The sampling technique used in this research is a time series . The purposive sampling method is the selection ofsamples that meet certain criteria determined by the researcher. The analysis used uses path analysis using SPSS V22 software. From the results of the data tests in this research, it is clear that equity has an effect on profitability. Assets have no effect on profitability. Liabilities affect profitability. Equity influences share prices. Assets have no effect on share prices. Liabilities affect share prices. Profitability influences share prices. The conclusion of the final hypothesis states that profitability has not been able to partially mediate the influence between equity, assets and liabilities on share prices. [ABSTRACT FROM AUTHOR]

This research aims to analyze the competitive advantage strategy management implemented by the Basmalah store. Competitive advantage is the key to maintaining and increasing market share in the competitive retail industry. The research method used was a qualitative approach by conducting in-depth interviews with the owner and manager of the Basmalah shop as well as direct observation at the shop location. The research results show that the Basmalah store has implemented several competitive advantage strategies, including product differentiation, improving customer service, and operational efficiency. By maintaining a stock of unique, high-quality products, Basmalah stores are successful in attracting customers looking for specialty items. Apart from that, improving customer service through friendly and informative service is also an important factor in maintaining customer loyalty. Operational efficiency is also considered crucial in maintaining competitive advantage. Through effective inventory management strategies and the use of technology to monitor store performance, Basmalah can reduce operational costs and increase efficiency. However, this research also identified several challenges faced by Basmalah stores, including price competition from competitors, and fluctuations in market demand. Therefore, it is recommended that Basmalah stores continue to monitor industry trends, innovate competitive advantage strategies, and maintain focus on customer satisfaction. [ABSTRACT FROM AUTHOR]

In this paper, we propose a design to detect and prevent IP spoofing-based distributed denial of service (DDoS) attacks on software-defined networks (SDNs). DDoS attacks are still one of the significant problems for internet service providers (ISPs) and individual users. These attacks can disrupt customer services by targeting the availability of the system, and in some cases, they can completely shut down the target infrastructure. Protecting the system against DDoS attacks is therefore crucial for ensuring the reliability and availability of internet services. To address this problem, we propose a lightweight source address validation (LSAV) framework that leverages the flexibility of SDN architecture in ISP networks and employs a lightweight filtering mechanism that considers the cost of operation to maintain high performance. Our setup for the proposed mechanism reflects client–server communication through an ISP SDN, and we use the entry points to eliminate malicious user requests targeting the systems. We then propose a novel algorithm on top of this setup to introduce a new and more efficient approach to existing mitigation methodologies. In addition to filtering the traffic against IP spoofing-based DDoS attacks, LSAV also prioritizes low resource consumption and high performance in terms of delay and bandwidth. With this approach, we believe that ISPs can effectively defend against IP spoofing-based DDoS attacks while still preserving low resource consumption for the infrastructure and high-quality internet services for their customers. [ABSTRACT FROM AUTHOR]

The goal of this study is to analyze the experiences of customers who used the food ordering app (FOA) in Ho Chi Minh City (HCMC) using a systematic review technique. By focusing on customers in HCMC, the study offered valuable localized insights, which could prove instrumental in improving app features, optimizing user interface, and tailoring marketing strategies for better user engagement. Subsequently, this study delivered an exhaustive explanation of the practical application of decision science, focusing on its relevance to the usage pattern of FOAs by customers on their handheld devices. Based on a systematic review, this study demonstrates that brand trust, service quality, hedonic motivation, price value, performance expectancy, and online reviews all have a positive influence on customer satisfaction and their intention to reuse the FOA. The scholars and management in the food industry of HCMC have the opportunity to use the results of this research as a blueprint for enhancing and reorganizing their customer service practices. They may strive to enhance the overall quality of service by improving the food ordering applications and integrating them with the identified criteria. The management of restaurants or food companies that use an app to deliver services to customers should update their apps to offer excellent services. As a result, it is anticipated that this will have a positive effect on customer satisfaction and enhance the likelihood of customers returning to utilize the service again. [ABSTRACT FROM AUTHOR]

The carpooling service, which is the sharing of journeys heading in similar directions, is expected to be more efficient. In this article, we study the impact of providing a carpooling service on customer waiting time and driver utilization in an on-demand service platform. We build an M / G / N queueing model to approximate the dynamics of the on-demand service platform that provides two services: a standard service and a carpooling service. We find that two factors influence the efficiency of the carpooling service: the source of customers who use the carpooling service, and the length of a normalized detour. If the carpooling service attracts customers who have not used this on-demand service before, i.e., the market size increases, then both the customer waiting time and driver utilization increase when more customers use the carpooling service. If the carpooling service primarily attracts customers who already use the standard on-demand service before, i.e., customers switch from the standard service to the carpooling service, then the impact of the carpooling service depends on the normalized detour. It is possible that customer waiting time and driver utilization first increase and then decrease as customers switch from the standard service to the carpooling service. [ABSTRACT FROM AUTHOR]

Compared to other sectors, the restaurant industry has a high reliance on human resources through active interactions with customers. Therefore, it is important to identify job satisfaction among employees and satisfy their needs at work in order to provide high customer service. Until now, surveys have been the traditional method for measuring employees' job satisfaction. Recently, numerous studies have analyzed employee job satisfaction based on extensive data collected directly from job portal websites. Therefore, it is necessary to verify whether the results of job satisfaction among employees derived from such methods have similar implications. This study compared the results of job satisfaction analysis using (1) 11,446 big data provided by former & current employees of the restaurant industry from a job portal website based on the two-factor theory and (2) A survey was conducted among 400 former & current employees. We found that only in big data, advancement opportunities & possibilities, and the compensation system significantly and positively (+) affected job satisfaction. In addition, current employees are more satisfied with advancement opportunities & possibilities than former employees only in big data. Thus, the big data and survey data analysis results differ. This can be attributed to the functionality and benefits of job portals. Therefore, it is necessary to consider the portal site's functions, beneficial features, and online environment characteristics before using big data in the field of human resources. Plain Language Summary: Big Data Analysis and Small Data Analysis Purpose: This study based on the two-Factor Theory, this study aims to explore determinants affecting job satisfaction of former and current employees within the restaurant industry by using two analytical. Methods: (1) Big data analysis through the collection of a large amount of corporate data from Job Planet, a Korean job portal site (2) Survey data analysis through the collection of questionnaires with relatively small data. The above results derived from two different methodologies are compared and analyzed to see if their implications are compatible to one another. Conclusions: This study utilized both survey and review data analyses to explore factors affecting job satisfaction among former and current employees in the restaurant industry based on the two-Factor Theory. The results of such analytical methods were compared to detect any differences between them. Implications: The results of analyzing survey and review data were similar in many aspects with minor differences. This suggests that either survey method or big data analysis can be meaningfully used in different contexts. For example, in situations where it is challenging to collect data from a specific group of audience who have low access to Internet, researchers may choose to use survey methods to collect information directly from the participants. Limitations: This study only used ratings on reviews that belong to quantitative information. However, job portal sites provide not only ratings on job satisfaction but also text reviews which are qualitative. We suggest future studies to understand job satisfaction of employees using qualitative reviews and various other information as well. [ABSTRACT FROM AUTHOR]

Information transparency plays a vital role for developing capital markets. Using data of A-share listed companies from 2007 to 2020, this study examined the impact of customer concentration on corporate information transparency from a supply chain perspective. It suggests that a significant negative correlation exists between customer concentration and information transparency. Customer concentration affects the quality of corporate information disclosures. Through the mechanism test, the impact of customer concentration on corporate information transparency is based on the risk effect rather than the substitution effect of private information on public information. Research on regulatory effects points out that a poor internal information environment aggravates the negative relationship between customer concentration and information transparency. However, media supervision and a higher marketization process alleviate the adverse effects of customer concentration on information transparency. This study indicates that firms with a higher customer concentration have a higher risk of information disclosure, which provides a reference point for investors for making investment-related decisions and for the capital market supervision department for formulating information disclosure policies. [ABSTRACT FROM AUTHOR]

Objective –This study investigates the role of customer service support (CSS) in co-creating brand value and enhancing corporate performance in the fintech industry. The research focuses on analyzing the impact of CSS on the customer journey from registration to first deposit. Methodology – The study utilizes historical data analysis and A/B testing. Client data from a leading fintech company is analyzed to compare conversion rates between those who used CSS versus those who did not. An A/B test is then conducted using a specialized support team targeting clients who haven’t made a deposit and had less than 2 chats with CSS. Findings –Clients who used CSS before depositing had 5 times higher conversion rates. The A/B test found a 3.1 percentage point (9.3% relative) increase in conversion from using targeted support. Novelty –This study provides new empirical evidence on the impact of CSS as a brand value co-creator in fintech, with a novel methodology to enhance corporate performance. [ABSTRACT FROM AUTHOR]

Text-based customer service is emerging as an important channel through which companies can assist customers. However, the use of few identity cues may cause customers to feel limited social presence and even suspect the human identity of agents, especially in the current age of advanced algorithms. Does such a lack of social presence affect service interactions? We studied this timely question by evaluating the impact of customers' perceived social presence on service outcomes and customers' attitudes toward agents. Our identification strategy hinged on Southwest Airlines' sudden requirement to include a first name in response to service requests on Twitter, which enhanced customers' perceived level of social presence. This change led customers to become more willing to engage and more likely to reach a resolution upon engagement. We further conducted a randomized experiment to understand the underlying mechanisms. We found that the effects were mainly driven by customers who were ex ante uncertain or suspicious about the human identity of agents, and the presence of identity cues improved service outcomes by enhancing customers' perceived levels of trust and empathy. Additionally, we found no evidence of elevated verbal aggression from customers toward agents with identity cues, although a mechanism test revealed the moderating role of customers' emotional states. Our study highlights the importance of social presence in text-based customer service and suggests a readily available and almost costless strategy for firms: signal humanization through identity cues. [ABSTRACT FROM AUTHOR]

From the theoretical perspectives of value co-creation and value appropriation in platform governance, this study explores how a platform can design motivation mechanisms to induce the proactive efforts of providers to reduce customer complaints. We conducted a field experiment on a major Chinese peer-topeer real estate platform offering long-term rental properties. Specifically, when a renter (customer) complaint about a host (provider) occurs, we sent reminder messages to other unaffected hosts in the same neighborhoods (as the affected host) and urged them to proactively prevent similar complaints. The reminder messages varied in terms of their emphasis of the roles of different stakeholders in platformbased value co-creation (provider-emphasized vs. customer-emphasized) and how they explicated different value appropriation mechanisms (competition-based vs. cooperation-based). Results show that compared to the control message, customer-emphasized messages effectively motivated providers' proactive efforts to reduce customer complaints. Contrastingly, provider-emphasized messages led to the undesirable outcome of increasing customer complaints, possibly due to providers' shirking behavior. We also found that a competition-based value appropriation mechanism strengthened the motivating effect, whereas a cooperation-based mechanism undermined the motivating effect. The study provides important theoretical and practical implications for platforms on the design of effective governance mechanisms. [ABSTRACT FROM AUTHOR]

Traditionally, call centers have experienced high voluntary turnover rates among their agents (i.e., Customer Service and Sales Representatives). This continues to be an unresolved issue. This paper presents a research study that was conducted to gain a better understanding of the reasons behind employees' decisions to leave a Customer Service and Sales organization belonging to a large multinational company in Financial Services in the USA. The company's call centers have consistently experienced a high turnover rate among its agents. This qualitative study was conducted with former employees across three markets to understand the "turning points" which led them to decrease their commitment to the organization and subsequently leave their job. This research aims to enhance our comprehension of the sequential decision-making process that culminates in an employee's decision to resign. The key findings and recommendations from this study could be used to create targeted organizational development initiatives designed to improve employee retention. [ABSTRACT FROM AUTHOR]

Increase of technical lifetime of infrastructures based on semi‐probabilistic considerations One of the most important measures in the discussion on improved sustainability in construction is to extend the service life of our structures [1]. Therefore, intensive research is conducted with regard to changing environmental conditions as well as external load effects for structures and new materials and their impact on the production and operation of infrastructures. Already now, according to [2], changes in the kinematics of the degradation mechanisms can be observed. In particular, changing environmental conditions (exposures) can accelerate but also slow down the degradation of materials and structures. These understandings of the degradation processes, but also the improved knowledge of the geometry and effective mechanical building material properties, should be effectively transferred into engineering practice for the assessment of structural reliability and remaining service life [3]. This paper presents how the elements of reliability analysis can be combined with the elements of in‐depth testing and monitoring procedures to periodically evaluate the degradation processes due to changing environmental conditions and new building materials. Subsequently, the remaining service life can be continuously updated with the help of semi‐probabilistic partial safety considerations. [ABSTRACT FROM AUTHOR]

We explored the question of how employees react to the perceived fairness of their manager's treatment of customers. Current models of third-party justice reactions produce two tenable but mutually exclusive responses to observed manager-customer treatment: Relational affirmation, in which service employees engage customers in ways perceived to be congruent with manager-customer treatment, and relational restoration, in which they attempt to rebalance or restore their perceived relationship with customers to counteract observed treatment. Hypothesizing both effects, we explore the role of service employees' relational identification with customers as a moderator of these two employee reactions. Across a field study of nursing assistants (n = 107) and their supervisors (n = 7), and a laboratory study with a simulated customer service help desk (n = 100), employee-customer identification was found to interact with supervisor-customer interpersonal justice such that the relationship between perceived justice and pro-customer behavior was positive when employee-customer identification was low (consistent with relational affirmation) and negative when employee-customer identification was high (consistent with relational restoration) (Study 1: β = −.22; Study 2: η2 =.07). [ABSTRACT FROM AUTHOR]

This study analyzed internal corporate social responsibility's (ICSR) effect on post-pandemic real estate companies' performance, which has been affected by recent dramatic changes in customers' mentality and habits. Data were gathered from 109 firms via questionnaires and processed using structural equation modeling. The results indicate ICSR has a direct positive influence on clients' choices, which then affect customer satisfaction and, ultimately, real estate companies' performance. ICSR is thus a valuable source of competitive advantage, with implications for the sector's management. [ABSTRACT FROM AUTHOR]

Effective scheduling algorithms are needed in the cloud paradigm to leverage services to customers seamlessly while minimizing the makespan, energy consumption and SLA violations. The ineffective scheduling of resources while not considering the suitability of tasks will affect the quality of service of the cloud provider, and much more energy will be consumed in the running of tasks by the inefficient provisioning of resources, thereby taking an enormous amount of time to process tasks, which affects the makespan. Minimizing SLA violations is an important aspect that needs to be addressed as it impacts the makespans, energy consumption, and also the quality of service in a cloud environment. Many existing studies have solved task-scheduling problems, and those algorithms gave near-optimal solutions from their perspective. In this manuscript, we developed a novel task-scheduling algorithm that considers the task priorities coming onto the cloud platform, calculates their task VM priorities, and feeds them to the scheduler. Then, the scheduler will choose appropriate tasks for the VMs based on the calculated priorities. To model this scheduling algorithm, we used the cat swarm optimization algorithm, which was inspired by the behavior of cats. It was implemented on the Cloudsim tool and OpenStack cloud platform. Extensive experimentation was carried out using real-time workloads. When compared to the baseline PSO, ACO and RATS-HM approaches and from the results, it is evident that our proposed approach outperforms all of the baseline algorithms in view of the above-mentioned parameters. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic brought about many unexpected changes for academic libraries. Technical services departments were especially disrupted due to the nature of their responsibilities and library operations. In response to these pandemic-induced changes, technical services managers were tasked with maintaining a high level of operations while also navigating sudden workforce changes including evolving job demands and employees working off-site. This study documents and analyzes the responses of technical services managers during the pandemic. Documenting these practice changes will help inform current managers looking to compare themselves to peers and future managers who may experience a similar event that causes a sudden shift in operations. Overall, managers reported a high incidence of change to their typical management practices. Managers made the biggest changes in communications and practices related to work-life balance. A significant theme emerged from the analysis that shows technical services managers adding several new practices to support and care for the mental health of employees. [ABSTRACT FROM AUTHOR]

Employees' proactive customer service performance can increase customers' perceived service quality and satisfaction, which is important for the long-term development of service enterprises. Ethical leadership can affect employees' attitude and behavior by showcasing ethical norms and improving employees' recognition of the organization. Using social identity theory and social cognitive theory, this study proposed that the relationship between ethical leadership and proactive customer service performance would be mediated by organizational identity and moderated by service climate. Utilizing structural equation modeling, we found a positive association between ethical leadership and proactive customer service performance, in which organizational identity acted as a mediator and service climate acted as a moderator. This study has expanded understanding of the antecedents of proactive customer service performance and filled a research gap on the relationship between service climate and proactive customer service performance. It offers a reference point and guidance for the management practice of service enterprises. [ABSTRACT FROM AUTHOR]