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Customer care is important for its role in relationship building. This role has traditionally been performed by human customer agents; however, the emergence of interactive generative AI (GenAI) shows potential for using AI for customer care in emotionally charged interactions. Bridging practice and the academic literatures in marketing and computer science, this article develops an AI-enabled customer care journey, from accurate emotion recognition to empathetic response, emotional management support, and, finally, the establishment of an emotional connection. Marketing requirements for each of the stages are derived from in-depth interviews with top managers and a survey of chief marketing officers. By juxtaposing these requirements against the current feeling capabilities of GenAI, the authors highlight the technological challenges engineers must tackle. The article concludes with a set of marketing tenets for implementing and researching the caring machine. These include verifying emotion recognition accuracy using marketing emotion theories through multiple emotion signals and methods, utilizing prompt engineering to enhance GenAI's emotion understanding, employing "response engineering" to personalize emotion management recommendations, and strategically deploying GenAI for emotional connection to simultaneously enhance customer emotional well-being and customer lifetime value. [ABSTRACT FROM AUTHOR]

Production planning and scheduling for companies with divergent processes, where a single component can be transformed into several finished products, are challenging as planners might face material misallocation issues. In this paper, we address the problem of managing a divergent process with DDMRP stock buffers, where different finished products are bottled with the same component having a fixed batch size. An allocation decision needs to be made to determine the quantities of finished products to be bottled. This study is motivated by a real-life problem faced by a dermo-cosmetic company. We compare and analyze by simulation nine different policies triggering allocation decisions. The first policy is the classic DDMRP rule, while the others are new policies, including a virtual buffer of a generic finished product and ConWIP loops, delaying the allocation decision. Our results show that the policy combining the classic DDMRP rule and a ConWIP loop surrounding a part of the process reduces the work-in-process by 34% compared to the classic DDMRP while ensuring high customer service rates and control of flow times. [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]

Post-sale customer care (PSCC) outsourcing is an effective supply chain strategy to reduce costs, but traditional outsourcing methods cannot ensure consumers' belief in PSCC quality, harming the firms' competitive strategy. To ensure consumer satisfaction through transparency, this article examines evolving supply chain strategies of leveraging blockchain to outsource PSCC operations of competing manufacturers to third-party agents. Based on consumers' beliefs and blockchain adoption cost, manufacturers have two choices; to outsource the PSCC operations with or without blockchain, resulting in multiple outsourcing strategies. Results show that the consumers' belief in one manufacturer's outsourcing strategy has detrimental effects on the stance of another manufacturer. Moreover, the blockchain cost and consumers' beliefs dictate the manufacturers' strategies for PSCC outsourcing, resulting in a 'quadruple zone of strategic fit', where both manufacturers adopt blockchain or neither adopt blockchain, or one adopts while the other does not. Interestingly, despite the low or zero blockchain cost, both manufacturers will outsource without blockchain if their traditional business models satisfy consumers. The extended analysis reveals contradictory results that manufacturers should outsource more often with blockchain to facilitate consumers when a long-term warranty is offered, or the product has a higher failure rate, even though, overall these factors increase costs. [ABSTRACT FROM AUTHOR]

The current research advances understanding of how consumers respond to embarrassing service encounters. Across a combination of field and online studies, the authors provide evidence that (1) consumers prefer self-service to human services when purchasing embarrassing products or services; (2) when self-service is not available, consumers respond more positively to a mechanistic service provider than to a personable service provider; and (3) if consumers must engage in embarrassing social interactions, they dehumanize service providers, perceiving them as more mechanistic and less capable of emotional reactions than when engaging in nonembarrassing service interactions. The authors also examine consumers' familiarity with the service provider as a boundary condition for the effect. Collectively, the results provide converging evidence for the proposed framework and have substantive implications for service management. [ABSTRACT FROM AUTHOR]

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]

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. [ABSTRACT FROM AUTHOR]

The infusion of emerging technologies (e.g., IoT-enabled algorithmic customer service systems [IACSs]) often brings disruptive changes to customer service. In particular, the agentic nature of these technologies challenges prominent service theories. Among these challenges, recent scholarly calls have pushed for more research on the infusion of emerging technologies into the service-profit chain (SPC) framework, advocating for the importance of extended knowledge to develop a techno-infused version of the SPC. Thus, from an interdisciplinary perspective, we draw upon role theory and propose a technoservice-profit chain (TSPC). Specifically, we contextualize the SPC in the technoservice context with different approaches, including decomposing context-specific constructs and theorizing IACS implementation as a contextual factor that moderates TSPC relationships. Using a sequential mixed methods design combining quantitative and qualitative approaches, we tested our research model by conducting multiwave surveys and follow-up interviews in a large business-to-business service firm with data from employees, supervisors, and customers before and after IACS implementation. This interdisciplinary study contributes to the information systems, service marketing, and management literatures by enriching the compositions of core SPC constructs, theorizing interactions between human agents and technology agents, and scrutinizing the impacts of technology agents on the linkages between internal employee management and external customer service. Our results further reveal the emerging issues of competing bosses (i.e., supervisors and IACSs), competing employees (i.e., employees and IACSs), and the unintended dehumanization effects of IACSs on supervisors and employees. [ABSTRACT FROM AUTHOR]

This article examines the characteristics of human errors in processing transportation requests. The role of artificial intelligence (AI) in maritime transportation is explored. The main methods and technologies used for automating and optimizing the handling of transportation requests are analyzed, along with their impact on reducing the number of errors. Examples of successful AI implementation in large companies are provided, confirming the positive influence of these technologies on overall operational efficiency and customer service levels. [ABSTRACT FROM AUTHOR]

Problem definition: This paper considers a tandem queueing system in which stage 1 has one station serving multiple classes of arriving customers with different service requirements and related delay costs, and stage 2 has multiple parallel stations, with each station providing one type of service. Each station has many statistically identical servers. The objective is to design a joint capacity allocation between stages/stations and scheduling rule of different classes of customers to minimize the system's long-run average cost. Methodology/results: Using fluid approximation, we convert the stochastic problem into a fluid optimization problem and develop a solution procedure. Based on the solution to the fluid optimization problem, we propose a simple and easy-to-implement capacity allocation and scheduling policy and establish its asymptotic optimality for the stochastic system. The policy has an explicit index-based scheduling rule that is independent of the arrival rates, and resource allocation is determined by the priority orders established between the classes and stations. We conduct numerical experiments to validate the accuracy of the fluid approximation and demonstrate the effectiveness of our proposed policy. Managerial implications: Tandem queueing systems are ubiquitous. Our results provide useful guidelines for the allocation of limited resources and the scheduling of customer service in those systems. Our proposed policy can improve the system's operational efficiency and customers' service quality. Funding: Z. Zhong's research is partially supported by the Fundamental Research Funds for the Central Universities [Grant 2023ZYGXZR074] and the Hunan Provincial Natural Science Foundation of China [Grant 2022JJ40109]. P. Cao's research is partially supported by the National Natural Science Foundation of China [Grant 72122019]. J. Huang's research is partially supported by the Hong Kong Research Grants Council General Research Fund [CUHK-14501621] and the National Natural Science Foundation of China [Grant 72222023]. S. X. Zhou's research is partially supported by the Hong Kong Research Grants Council General Research Fund [CUHK-14500921], the National Natural Science Foundation of China [Grant 72394395], and the Asian Institute of Supply Chains and Logistics. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0266. [ABSTRACT FROM AUTHOR]

Problem definition: We study customer service chat (CSC) systems, in which agents can serve multiple customers simultaneously, with generally distributed service and patience times. The multitasking capability of agents introduces idiosyncratic challenges when making routing and staffing decisions. Methodology/results: To determine the dynamic matching of arriving customers with available agents, we first formulate a routing linear program (LP) based on system primitives. Inspired by the optimal solution of the routing LP, we design a parsimonious dynamic routing policy that is independent of arrival rate and service capacity information. We also use the optimal solution to develop closed-form approximations for crucial performance metrics and show that a similar LP can be utilized to make staffing decisions. Through extensive simulation experiments, we showcase the efficacy of our approximations and staffing decisions. Furthermore, under our proposed policy, the CSC system exhibits a unique stationary fluid model in which the steady-state performance measures align with our approximations. Managerial implications: The extant literature primarily focuses on Markovian systems with exponential distributions. In this paper, customers' service and patience times are allowed to be generally distributed to agree with practical settings. Our findings indicate that the distributions have a significant impact on routing policies, staffing decisions, and system performance. Funding: Z. Long was supported by the National Natural Science Foundation of China [Grants 72101112, 72132005, and 72271119] and Jiangsu Province, China [Grant BK20210171]. J. Zhang was supported by the Hong Kong Research Grants Council, General Research Fund [Grants 16208120 and 16214121]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0114. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to shape, design and present a model that can be used to develop the level of customer service through social networks in the banking system. For this purpose, a large part of the mentioned structures was extracted using the ultracomposite method. Therefore, in the first step, an extensive search was conducted among various sources (including books, book summaries, periodicals, case studies, doctoral dissertations, etc. based on keywords) and more than four hundred sources were collected. Then, by separating the categories, themes and coding, using qualitative data analysis software, the results will be extracted and finally, multiple structures will be extracted to compile the model. In the following, by using ”content validity indices and content validity ratio”, the validity of the desired measures was measured by the opinions of the experts and then with the limited use of questionnaire items, the reliability of the items that make up the functional structures, as well as the reliability of the questionnaire tool (alpha Cronbach’s) calculation and the result was 0.89. [ABSTRACT FROM AUTHOR]

This article presents the results of research exploring the dynamics of recognition in the interactive work of female cashiers in supermarket chains in Santiago, Chile. Based on three dimensions of recognition configured from gendered elements of interactive service work, cashiers' recognition experiences are analyzed, considering their socio‐biographical trajectories, their link with the companies, and the dynamics of the trade they establish in customer service labor. Findings show ambivalent recognition processes combining those instituted “from above” by the administration and those articulated “from below” by families, professional peers, and customers in daily interactions. Based on the results, the article discusses the challenges for a research agenda on recognition at work capable of considering the gendered dynamics of work in the service sector. [ABSTRACT FROM AUTHOR]

This paper embarks on a comprehensive and in-depth comparative analysis of two prominent artificial intelligence applications: ChatGPT and IBM Watson. Developed by OpenAI, ChatGPT excels in natural language processing, leveraging cutting-edge technology to enable robust conversational interfaces. In contrast, IBM Watson offers a multifaceted suite of AI services that encompass machine learning, advanced data analytics, and sophisticated language processing capabilities. This analysis delves into their intricate technical specifications, exploring the nuances of their respective architectures and computational frameworks. It meticulously evaluates their diverse capabilities, ranging from text generation and comprehension to complex data analysis and predictive modeling. Moreover, the paper critically examines the industry-specific use cases where ChatGPT and IBM Watson demonstrate their strengths and applications. By highlighting real-world examples across various sectors such as healthcare, finance, customer service, and education, it elucidates how each platform can be leveraged to enhance operational efficiency, decision-making processes, and user interaction experiences. Additionally, the analysis forecasts emerging trends in AI development, shedding light on how these technologies are expected to evolve and integrate into broader technological landscapes. [ABSTRACT FROM AUTHOR]

Indonesia as one of the countries with a large population and significant economic growth, has a dynamic and rapidly growing retail variant. This study aims to analyze the effect of product, price, location, promotion, store atmosphere, and customer service on consumer purchasing decisions on electric motors at the Soekarno Hatta Bandung branch. The research method used is a survey with a quantitative approach. Data is collected through questionnaires distributed to consumers who have purchased electric motors at that location. Data analysis was carried out using multiple linear regression to test the effect of independent variables on purchasing decisions. The results showed that product, price, location, promotion, store atmosphere, and customer service have a significant influence on consumer purchasing decisions. The findings indicate that companies need to pay attention to these factors to improve purchasing decisions and customer satisfaction. This research provides practical implications for companies in designing more effective marketing strategies to increase consumer attractiveness and satisfaction with their electric motor products. [ABSTRACT FROM AUTHOR]

In this study, we investigate the container delivery problem and explore ways to optimize the complex and nuanced system of inland container shipping. Our aim is to fulfill customer demand while maximizing customer service and minimizing logistics costs. To address the challenges posed by an unpredictable and rapidly-evolving environment, we examine the potential of leveraging reinforcement learning (RL) to automate the decision-making process and craft agile, efficient delivery schedules. Through a rigorous and comprehensive numerical study, we evaluate the efficacy of this approach by comparing the performance of several high-performance heuristic policies with that of agents trained using reinforcement learning, under various problem settings. Our results demonstrate that a reinforcement learning approach is robust and particularly useful for decision makers who must match logistics demand with capacity dynamically and have multiple objectives. [ABSTRACT FROM AUTHOR]

Customer relationship management is complicated by a lack of understanding of customer attributes and needs. Transformational and inventive techniques are needed to improve customer service. WhatsApp-based AI Chatbots can improve academic service efficiency and quality. The platform's usability and interaction with customer management systems are the main reasons. By adopting the AI Chatbot, clients and internal users will receive consistent and correct responses. Qualitative interviews and survey analysis are used to collect data for the study. Qualitative interviews are utilized for qualitative analysis, while survey analysis validates research survey data. The report reveals 83.8% customer satisfaction and 75.3% customer loyalty. The study found that the chatbot's ability to minimize service time greatly affected customer satisfaction. Due to their consistency and speed, chatbots in customer care have improved consumer satisfaction. Customers like chatbots' speed and efficiency, which allow them to get help immediately. The chatbot's ability to handle common questions and tasks frees up staff to handle more complex and urgent issues, improving service. [ABSTRACT FROM AUTHOR]

In China, the native people living in the society have great enthusiasm for their country and they always prefer using and consuming their homeland-manufactured products. Moreover, Chinese have their own culture in which they possess different arts and creative commodities consumption and purchasing to follow their traditional norms. This study investigates the patriotic nature of Chinese customers, who have a strong preference for their home-made products and cultural heritage. The research uses an empirical model to examine the relationship between animosity, ethnocentrism, country of origin, and country knowledge, as well as perceived warmth as a mediator. The study used a positivist philosophy with a deductive approach, using the S-O-R theory as the empirical support. Quantitative primary data was collected from 280 customers of blue and white ceramic products, with a total sample size of 280. The SEM technique revealed that country of origin and ethnocentrism significantly influences customer purchase intentions for ceramic products. Furthermore, the mediation analysis revealed that customer ethnocentrism indirectly impacts purchase intentions through perceived warmth. The study concludes that Chinese customers have a high devotion to their mother country's products, and the behavior of native sellers and general society people is crucial in stimulating their purchase intentions. [ABSTRACT FROM AUTHOR]

The implementation of information and technology (IT) supports company sustainability. Large companies use IT as an integral part of their business model. Digital strategies must align with business strategies to achieve sustainability. Wirelessindo, established in 2007, provides IT solutions such as equipment, site surveys, network design and security, and tower installations. Its mission is to increase company productivity to win the competition in the era of Industry 4.0. It is used to enhance customer service and internal business process efficiency. Initial investigations found issues with IT function mismatches, financial losses due to data loss, IT equipment installation and configuration errors, and business process incidents caused by emerging risks. Identified root problems include employee knowledge gaps, risk management disparities, errors in defining business needs, and change management gaps. Based on these findings, IT governance evaluation was chosen as the research focus. This study aims to provide an overview of CV Wirelessindo IT capability levels and recommend improvements to meet expected levels. A mixed-method approach and COBIT 2019 were used in this study. The General Manager, IT Division Manager, Software Development Team, Network Monitoring Team, Project Manager, and HR Manager were selected as respondents based on the RACI chart guidelines. Of the nine selected objectives, BAI08 showed level 0. APO12, BAI02, BAI06, BAI07, and DSS01 showed level 1. APO07, BAI10, and DSS03 showed capability level 2. Therefore, 61 recommendations were provided to raise the IT governance capability level to level 3 for all objectives. [ABSTRACT FROM AUTHOR]

Docked Bike Sharing Systems often experience load imbalances among bike stations, leading to uneven distribution of bicycles and to challenges in meeting users' demand. To address the load imbalances, many docked Bike Sharing Systems employ rebalancing vehicles that actively redistribute bicycles across stations, ensuring a more equitable distribution and enhancing the availability of bikes for users. The determination of the number of rebalancing vehicles in docked Bike Sharing Systems is typically based on various criteria, such as the size of the system, the density of stations, the expected demand patterns, and the desired level of service quality. This is a determining factor, in order to increase the efficiency of customer service at a reasonable cost. To enable a cost-effective rebalancing, we have used a cluster-based approach, due to the large scale of the Bike Sharing Systems, and our model is based on Markov Chains, given their proven effectiveness in this domain. Degrees of subsystem load at station level were used for modeling purposes. Additionally, a quantization strategy around cluster load was developed, to avoid state space explosion. This allowed the computation of the probability of transitioning from one degree of system load to another. A new method was developed to determine the fleet size, based on the identified subsystem steady state, describing the rebalancing necessity. The model evaluation was performed on traffic data collected from the Citi Bike New York Bike Sharing System. Based on the evaluation results, the model transition rates were in accordance with the expected values, indicating that the rebalancing operations are efficient from the point of view of the fulfillment of on-time arrival constraints. [ABSTRACT FROM AUTHOR]

Copyright of Die Unternehmensbesteuerung (Ubg) is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We study maintenance service operations in large facilities portfolios with a focus on modeling logistics of associated spare parts and their storage locations serviced by personnel from several trades who move around the buildings in their vehicles. The key challenge is to reduce the cost of spare parts inventory, storage, and vehicles while providing responsive customer service. To address these challenges, we propose (i) inventory models to determine stock levels and (ii) storage space in personnel vehicles to allocate the mix and location of spare parts by trade. The two models can be readily integrated, and conceptually, technician vehicles serve as “forward-reserve storage” that improves service responsiveness. The proposed model is applied to a large facility of a non-profit organization with 330 buildings, 17,000 spare parts, and 254 vehicles. Compared to prevailing practice, the proposed model can potentially reduce $1.27 million worth of inventory costs, a reduction of ~77%. [ABSTRACT FROM AUTHOR]

The article focuses on the necessity for courts to adopt modern, technology-driven customer service features. Topics include the use of remote court appearances via telephone or video, the integration of smartphone evidence presentation in courtrooms, and the implementation of responsive, mobile-friendly court websites.

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]

Retrieval-augmented generation (RAG) adds a simple but powerful feature to chatbots, the ability to upload files just-in-time. Chatbots are trained on large quantities of public data. The ability to upload files just-in-time makes it possible to reduce hallucinations by filling in gaps in the knowledge base that go beyond the public training data such as private data and recent events. For example, in a customer service scenario, with RAG, we can upload your private bill and then the bot can discuss questions about your bill as opposed to generic FAQ questions about bills in general. This tutorial will show how to upload files and generate responses to prompts; see https://github.com/kwchurch/RAG for multiple solutions based on tools from OpenAI, LangChain, HuggingFace transformers and VecML. [ABSTRACT FROM AUTHOR]

The research of the quality control of logistics services relevancy is determined by the increasingly dynamic and competitive nature of the market requires companies to ensure the high quality of their logistics services, especially in the sphere of business-to-consumer (B2C). The research aims to analyse and identify optimal approaches and strategies for quality control of logistics services in B2C interactions. Among the methods used were the analytical method, statistical method, functional method, system analysis method, deduction method, synthesis method and comparison method. In the process of the study, the current practice of quality control in B2C logistics was analysed. An economic relevance assessment identified how service quality can affect business and also assessed the potential benefits of improving it. Approaches to quality control were analysed, including such methods as statistical data analysis, internal and external audits, application of quality standards, and use of technology for monitoring and tracking processes. Opportunities to optimise logistics processes and their impact on overall quality were also considered. A comparative analysis of practices in the industry identified best practices and innovations. The study summarised current trends and provided practical recommendations for companies seeking to optimise quality control of logistics services on a costeffective basis. The practical relevance of the findings is to provide companies with valuable tools and insights to improve their logistics operations and enhance customer service. [ABSTRACT FROM AUTHOR]

The article discusses the American Library Association (ALA) Annual Conference in Chicago, U.S. on June 25, 2023. Topics included documentation in technical services, focusing on best practices and challenges in documentation management and developing future electronic resource librarians. Attendees from diverse library backgrounds has attended the conference including Greg Ferguson and Cara Calabrese.

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Copyright of Tourism & Rural Development Studies / Turisztikai és Vidékfejlesztési Tanulmányok is the property of CampInvest Kft. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Public procurement contracts (PPCs) of goods, services, and works are about one-tenth of the global gross domestic product. Much research has been conducted on government spending and its aggregate effects, but the evidence is scarce at the micro-level. We exploit sealed-bid PPC auctions of construction works, discontinuity in bidders' win margin, and firms' daily employment variation to provide a causal estimate of winning a PPC on firms' employment. Winning a PPC has a small positive impact on a firm's short-run employment. We investigate mechanisms and heterogeneity that can explain the small initial magnitudes. We find no compelling evidence in favor of political connections, an information leakage channel, or PPC size as explanations for the small magnitude. Our investigation of a longer period shows that the impact phases out in less than a year. The lack of a long-term impact is due to runners-up winning more PPCs and runners-up substituting for more market revenue in the year after closely losing a PPC. Finally, the impacts are concentrated in construction firms that conduct most contracted work in-house. The final estimation shows the effect is 3.7 new employees per PPC with a public cost per job created at €58,600 (€49,800–€65,100). [ABSTRACT FROM AUTHOR]

While interests in Industry 4.0 technologies such as cloud computing and the Internet of Things (IoT) are growing, an ongoing challenge is to properly evaluate the performance of the providers of such technologies. Methods have been developed and applied to assess the efficiency of cloud service providers (CSPs) for Industry 4.0. However, most existing methods suffer from such shortcomings as subjective weights and computing complexity, rendering it difficult to succinctly differentiate the performance of CSPs in a competitive market. Besides, the literature has not taken into account many different types of data such as ratios, integers, and undesirable factors that can affect the performance of CSPs. Most importantly, most existing studies do not consider the sustainability of CSPs in evaluating their performance. To address the above issues, we present a comprehensive analytical method based on data envelopment analysis (DEA) to gauge the sustainability of CSPs for Industry 4.0. Validating the usefulness of our method using a real-life dataset, we provide not only a viable means with sound academic underpinning but also significant managerial insights for practitioners to assess the sustainability of CSPs for Industry 4.0. [ABSTRACT FROM AUTHOR]

With the wide use of information technologies including Big Data and artificial intelligence (AI), consumers' personal actions (their search history, transaction records, click-through behaviors, etc.) can be tracked, recorded and analyzed by the service provider (e.g., Google) to provide personalized services. Under the current regime, consumers usually hand over their personal data for free in exchange for high-quality services. As it becomes more and more commonly accepted that "data is property," should consumers be entitled to claim their property rights over their personal data? New technologies emerge to empower consumers to control their own data, and the service provider may need to compensate for the usage of such data. How consumers and the service provider should react to such technologies, however, is not clear. We build a theoretical model in which consumers have different sensitivities towards their data ownership. We show that the impact of the data ownership shift depends not only on the service provider's revenue structure and the discount in the service quality offered to non-data-providing consumers, but also on whether and how consumers are compensated. More importantly, if the service provider can endogenously adjust the qualities of services provided to consumers, the shift of data ownership may not necessarily benefit consumers, or harm the service provider. We also offer guidelines for data regulation policy designs. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is pervading the government and transforming how public services are provided to consumers across policy areas spanning allocation of government benefits, law enforcement, risk monitoring, and the provision of services. Despite technological improvements, AI systems are fallible and may err. How do consumers respond when learning of AI failures? In 13 preregistered studies (N = 3,724) across a range of policy areas, the authors show that algorithmic failures are generalized more broadly than human failures. This effect is termed "algorithmic transference" as it is an inferential process that generalizes (i.e., transfers) information about one member of a group to another member of that same group. Rather than reflecting generalized algorithm aversion, algorithmic transference is rooted in social categorization: it stems from how people perceive a group of AI systems versus a group of humans. Because AI systems are perceived as more homogeneous than people, failure information about one AI algorithm is transferred to another algorithm to a greater extent than failure information about a person is transferred to another person. Capturing AI's impact on consumers and societies, these results show how the premature or mismanaged deployment of faulty AI technologies may undermine the very institutions that AI systems are meant to modernize. [ABSTRACT FROM AUTHOR]

The present research demonstrates how consumer responses to negative and positive offers are influenced by whether the administering marketing agent is an artificial intelligence (AI) or a human. In the case of a product or service offer that is worse than expected, consumers respond better when dealing with an AI agent in the form of increased purchase likelihood and satisfaction. In contrast, for an offer that is better than expected, consumers respond more positively to a human agent. The authors demonstrate that AI agents, compared with human agents, are perceived to have weaker intentions when administering offers, which accounts for this effect. That is, consumers infer that AI agents lack selfish intentions in the case of an offer that favors the agent and lack benevolent intentions in the case of an offer that favors the customer, thereby dampening the extremity of consumer responses. Moreover, the authors demonstrate a moderating effect, such that marketers may anthropomorphize AI agents to strengthen perceived intentions, providing an avenue to receive due credit from consumers when the agent provides a better offer and mitigate blame when it provides a worse offer. Potential ethical concerns with the use of AI to bypass consumer resistance to negative offers are discussed. [ABSTRACT FROM AUTHOR]

In modern banks, establishing efficient and quality customer services plays a crucial role to achieve the business success. There are a large number of customers to be served daily; however, required service resources (in particular, customer service representatives) can be rather limited. Therefore, customer service representative scheduling is a challenging problem for bank managers. In the present paper, we focus on a customer service representative scheduling problem considering the stochastic customer arrival time and service duration to minimise the total cost including two parts: (i) the loss concerning the customer waiting and (ii) cost of providing service representatives. We formulate this scheduling problem as an integer programming problem and employ an adapted water wave optimization (WWO) algorithm to solve this problem efficiently. We adapt the propagation and refraction operators of WWO according to the solution space of this problem. The results of the conducted computational experiments demonstrate that the adapted WWO algorithm outperforms the considered state-of-the-art evolutionary algorithms in solving a set of test instances. [ABSTRACT FROM AUTHOR]

Enhancing the naturalness and rhythmicity of generated audio in end-to-end speech synthesis is crucial. The current state-of-the-art (SOTA) model, VITS, utilizes a conditional variational autoencoder architecture. However, it faces challenges, such as limited robustness, due to training solely on text and spectrum data from the training set. Particularly, the posterior encoder struggles with mid- and high-frequency feature extraction, impacting waveform reconstruction. Existing efforts mainly focus on prior encoder enhancements or alignment algorithms, neglecting improvements to spectrum feature extraction. In response, we propose BERTIVITS, a novel model integrating BERT into VITS. Our model features a redesigned posterior encoder with residual connections and utilizes pre-trained models to enhance spectrum feature extraction. Compared to VITS, BERTIVITS shows significant subjective MOS score improvements (0.16 in English, 0.36 in Chinese) and objective Mel-Cepstral coefficient reductions (0.52 in English, 0.49 in Chinese). BERTIVITS is tailored for single-speaker scenarios, improving speech synthesis technology for applications like post-class tutoring or telephone customer service. [ABSTRACT FROM AUTHOR]

The purpose of this study is to determine the strategy applied by Bank Jatim KCP tripe in winning the banking industry market amid many other banking industries around it. There are several strategies used in dealing with the competition including: improving services, providing complete and comfortable facilities and infrastructure, when marketing their products using a strategy of going directly into the field. The method used in this study uses a qualitative descriptive analysis approach with data sources obtained from observation, interviews, and documentation. In-depth interviews were conducted with informants from the employees of Bank Jatim KCP tripe. In addition, secondary data sources in this study were obtained from journal literature studies, research articles, and literature related to this study. The results showed that the strategy applied by Bank Jatim KCP is different between innovation and service including the provision of products from savings to financing according to customer needs, reliable service by providing the best solution to customer financial problems, and avoiding problems with customers because they provide services according to SOP. Third, marketing markets its products using a direct field strategy that is carried out to establish close relationships with customers. The strategy of Bank Jatim KCP tripe in facing the competition of the banking industry is more to improve the quality and service at Bank Jatim KCP tripe because customer satisfaction is also one of the strategic aspects to win the competition and maintain the company's image in the market and the wider community. So that the quality of customer service becomes a very important issue. Because service is not limited to serving, but can understand, understand and feel. [ABSTRACT FROM AUTHOR]

Due to the rise of user-generated content, social media is increasingly adopted as a channel to deliver customer service. Given the public character of online platforms, the automatic detection of emotions forms an important application in monitoring customer satisfaction and preventing negative word-of-mouth. This paper introduces EmoTwiCS, a corpus of 9489 Dutch customer service dialogues on Twitter that are annotated for emotion trajectories. In our business-oriented corpus, we view emotions as dynamic attributes of the customer that can change at each utterance of the conversation. The term 'emotion trajectory' refers therefore not only to the fine-grained emotions experienced by customers (annotated with 28 labels and valence-arousal-dominance scores), but also to the event happening prior to the conversation and the responses made by the human operator (both annotated with 8 categories). Inter-annotator agreement (IAA) scores on the resulting dataset are substantial and comparable with related research, underscoring its high quality. Given the interplay between the different layers of annotated information, we perform several in-depth analyses to investigate (i) static emotions in isolated tweets, (ii) dynamic emotions and their shifts in trajectory, and (iii) the role of causes and response strategies in emotion trajectories. We conclude by listing the advantages and limitations of our dataset, after which we give some suggestions on the different types of predictive modelling tasks and open research questions to which EmoTwiCS can be applied. The dataset is made publicly available at https://lt3.ugent.be/resources/emotwics. [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]

This research was conducted because there was a decrease in the number of customers of the Tirta Giri Nata Drinking Water Regional Public Company in Cirebon City during the 2021-2023 period. This research uses a qualitative method by collecting data through interviews, observation and documentation. This research uses public service theory which focuses on the five main service quality dimensions related to customer service by public water companies: Tangibles, responsiveness, reliability, assurance and empathy. This study uses an interactive model data analysis procedure, which begins with data collection and continues with data reduction, data visualization, and conclusion drawing as the final step. The results showed that the service quality of PERUMDA Tirta Giri Nata Cirebon City still did not meet the five main success indicators, namely reliability, responsiveness, assurance, empathy, and tangible. The conclusion of this study is that the quality of customer service at PERUMDA Tirta Giri Nata Cirebon City, especially in terms of administrative and technical complaint services, has not yet reached an optimal level. There are still shortcomings in fulfilling the expected dimensions and indicators of service quality. [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]