Patientnämndens förvaltning i Stockholm tar årligen emot tusentals samtal som önskar framföra klagomål på vården i Region Stockholm. Syftet med arbetet är att undersöka hur en NLP-robot för klassificering av inkomna klagomål skulle kunna bidra till en ökad effektivitet av verksamheten. Klassificeringen av klagomålen har utförts med hjälp av en metod baserad på Support Vector Machines. För att optimera modellens korrekthet undersöktes hur längden av ordvektorerna påverkar korrektheten. Modellen gav en slutgiltig korrekthet 53,10 %. Detta resultat analyserades sedan med målsättningen att identifiera potentiella förbättringsmöjligheter hos modellen. För framtida arbeten kan det därför vara intressant att undersöka hur antalet samtal, antalet personer som spelar in samtal och klassfördelningen i datamängden påverkar korrektheten. För att undersöka hur effektiviteten hos Patientnämndens förvaltning i Stockholm skulle påverkas av implementeringen av en NLP-robot användes en SWOT-analys. Denna analys visade på tydliga fördelar med automatisering av klagomålshanteringen, men att en sådan implementation måste ske med försiktighet där det säkerställs att tillgången på kompetens är tillräcklig för att förebygga potentiella hot. / Every year Patientnämnden recieves thousands of phone calls from patients wishing to make complaints about the health care in Stockholm. The aim of this work is to investigate how an NLP-robot for classification of recieved phone calls would contribute to an increased efficiency of the operation. The classification of the complaints has been made using a method based on Support Vector Machines. In order to optimize the accuracy of the model the impact of the length of the word vector has been investigated. The final result was an accuracy of 53.10%. The result was analyzed with the goal to identify potential opportunities of improvement of the model. For future work it could be interesting to investigate in how the number of calls, the number of people recording the calls and the distribution between the classes affect the accuracy A SWOT-analysis was performed in order to investigate in how the efficiency of Patientnämnden would be affected by the implementation of an NLP-robot. The analysis showed apparent benefits of automation of complaint management, but also that such an implementation must be done with great caution in order to be able to ensure that the available competence is high enough to prevent potential threats.

This study is rooted in the Service Dominant Logic (SDL) theory and explores the phenomenon of value co-destruction, the context being chatbot-mediated customer service, with a focusing on chatbots affiliation with value-co-destruction and on the impacts outsideof the dyadic relationship between the service provider and receiver, described as the broader consumer ecosystem. It is evident that the relationship between businesses and consumers is being revolutionized through the implementation of chatbots, claiming benefits such as improved operational efficiency, and non-time specific service. However, Plé (2017) argues that SDL research is overly focused on value co-creation and not enough on value codestruction, as well as being too narrowly focused on specific factors, therefore more studies are needed in exploring the effects on the broader ecosystem involved. Therefore, this study aims to explore the value co-destruction and its effects on the broader consumer ecosystem. The research was conducted using a qualitative method, through an interpretivist research philosophy to collect data in the form of the subjective and personal experiences of customers. It also utilized an abductive approach to allow for the generation of new insights through combining established knowledge, empirical evidence, and theory to formulate a proposition and interpretation beyond what is initially apparent. Through semi-structured interviews, 9 participants with prior experiences of customer service orientated interactions with chatbots across various industries were conducted. To analyze the data, a thematic analysis was employed where the findings indicate that in chatbot interactions which result in value co-destruction the effects affect a broader number of stakeholders in the consumer ecosystem such as family and friends.

Research questions: How can businesses improve the trustworthiness and competence of chatbots for consumers? Purpose: The purpose is to investigate how chatbots' perceived competence and trustworthiness impact consumers' willingness to interact with them. The study             aims to identify patterns or businesses to advance  Method: The study relies on qualitative data and semi-structured interviews with consumers about their experience with chatbots. For deeper and more detailed data, it is conducted by interviewing experts with years of experience with chatbots. The data has been then analyzed through thematic analysis.  Conclusion: The study identifies 10 key themes connected to the theories and the two main elements of this research. Companies are advised to give top priority to the identified themes when integrating chatbots into their customer service operations.

This report describes the design and development processes used in creating a customer service training program for Deseret Mutual Benefit Administrators (DMBA) by three Instructional Psychology and Technology graduate students from Brigham Young University (the BYU design team). This paper reviews both the product and the process of developing the product. It also contains a formative evaluation of the product and provides a summative evaluation plan to be utilized by DMBA trainers once the product is fully implemented. The strengths and weaknesses of the training program are critiqued and recommendations for improvement are made. Finally, BYU design team members describe their unique contributions throughout this project and individually critique the process and experience.

Supply chain agility has been receiving a lot of attention in recent literature as a way for organizations to become more responsive to change and improve customer service levels. However, agility is typically dealt with qualitatively, and organizations are usually unsure of the steps to take to improve their agility and the customer service level to target. This research studies supply chain agility based on a case study of Intel Corporation, a large semiconductor manufacturer. Here, agility is defined as the ability to satisfy customer demands by reacting effectively to changes in market stimuli. Reacting effectively does not mean reacting to every change in supply or demand. Doing so means increasing supply chain variability unnecessarily, which is amplified by the bullwhip effect. The essence of supply chain agility is determining the degree to which variability should be managed through artificial means such as safety stock, and appropriate triggers for changing production levels and inventory targets. The purpose of this research is to examine factors that influence supply chain agility and identify a cost-effective plan for achieving it. The first phase addresses the problem of identifying target inventory and customer service levels based on regression analysis of historical data and financial analysis of inventory holding costs and stock-out costs. The impact of three factors (forecast error, order lead-time, and demand variability) on the relationship between inventory and customer service level is also examined. The second phase of the research evaluates strategies for production and inventory control with the goal of finding the appropriate trade-off between minimizing cost (of holding inventory and stock-outs) and minimizing variability. Control policies based on the Exponentially Weighted Moving Average (EWMA) control chart with control limits on demand forecasts are proposed to detect when tighter control of processes is necessary. A Monte Carlo supply chain simulation is used to evaluate the performance of these policies under various levels of forecast error and demand variability. Results indicate that several control chart-based policies outperform Intel's current planning policy in terms of cost without significantly increasing variability. The selection of the appropriate policy must be based on the decision-makers' desire to minimize cost compared to the desire to minimize variability, as each policy results in a trade-off between these two objectives.

This study sought to determine customer satisfaction levels of faculty and staff with their technology support office in a large university in Florida. The focus of research was to determine if there were any differences in customer satisfaction based on four demographics: gender, faculty versus staff, educational level and age. An anonymous customer satisfaction survey included 26 Likert-type scale questions measuring 16 service quality dimensions was administered to the population. The 16 service quality dimensions included 10 dimensions from Zeithaml et al. (1990), five dimensions from Besterfield et al. (1995, 2003), and one dimension, overall satisfaction. Findings showed there was a statistically significant difference in two demographics, gender and faculty versus staff. Regarding gender, there were no differences in 14 of 16 dimensions examined. The two dimensions with differences were tangibles and understanding the customer, with males having lower customer satisfaction than females. Regarding faculty versus staff differences, there were no differences in all the dimensions other than the courtesy dimension for which faculty had a lower level of customer satisfaction level than staff. Regarding educational level and age, there were no differences in any of the 16 dimensions.

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Defining and measuring the quality of customer service has been a major challenge for business-to-business marketers. This research addresses the question whether an established instrument for consumer markets (SERVQUAL) can be used for understanding the role of customer service in the European nylon intermediates industry. To accomplish this objective, an in-depth literature review is accomplished followed by several expert panels adopting the instrument slightly. Based on a survey sample of 110 industry members collected with the ¿drop and collect technique¿ the appropriateness of the tool to verify the anticipated structure is examined using reliability tests as well as exploratory and confirmatory factor analysis. The findings suggest that even though various criteria for reliability and validity are met, the five-dimensional structure of the instrument cannot be recovered. The research questions the usefulness of the instrument for the European nylon intermediates industry despite it being originally anticipated to be applicable. However, the research emphasises that the instrument is a useful indicator for understanding the role of customer service based on individual items rather than on the instrument¿s dimensionality. It is demonstrated how the implementation in the nylon intermediates industry enables an organization to develop a greater awareness of customer service quality and how an enterprise gains an initial instrument to comprehend and improve this element of the offering. The thesis concludes by linking the results of the research with the discussion on service-dominant logic.

Today's digital progress highlights disruptive digital technology as a numerous impact on marketing and societies. Artificial intelligence in conjunction with chatbots creates a seamless and powerful tool for customer service. Companies are estimated to save 30% in customer service related costs while chatbots can assist with up to 80% of routine questions. Such numbers are considered appealing for companies to implement chatbots with the aim of streamlining and maximizing profits. An important aspect that can be neglected by companies is quality, which is an essential factor for customers' user experience. In this context, the user experience creates satisfaction and repeated use. An understanding of chatbot quality increases the chances of successfully implementing and developing the right tool with the aim of satisfying customers both efficiently and qualitatively in customer service. From such a perspective, the survey has concentrated around the user experience for a chatbot interaction. How is the quality of the user experience and what factors have a direct impact on chatbots in customer service? What characteristics should a chatbot possess to enhance the user experience? The survey has been carried out with the choice of a multimethod research with a qualitative approach. Some quantitative measures have also been used to concretize certain values, but the main focus area has been on the survey of the user experience from a qualitative perspective. Two theoretical frameworks have been used to analyze the user experience of chatbots. These focus on qualitative factors that have an effect on the user experience. The result shows that the quality of the user experience is considered high on the selected chatbot for simpler questions and less complex matters. The factors response-relevance, response-comprehensibility, dialogue-result and dialogue-efficiency showed a relatively high user experience. The characteristics that should be implemented in a chatbot are understandability, reliability, responsiveness and assurance. This creates a confirmation, satisfaction and repeat use for the user experience. Influential factors that have been analyzed in the survey are the user's question formulation. A qualitative advantage is created for users who formulate formal questions, while more personal questions increase the margin of error of the chatbot's interpretive ability to answer the question. The perspective can be seen as a lack of quality from the chatbot or as a missing feature. A final factor impacted in the user experience is technology anxiety, which has been shown to be lowered for users after interacting with a chatbot. Users do not have a high sense of difficulty to use a chatbot but may hold a sense of uncertainty and discouragement. With greater experience and a perceived positive user experience of a chatbot, these factors are drastically reduced. The 5 conclusion leads to the user experience being of high quality in terms of interaction with a chatbot, while several influencing factors are highlighted. Future research is recommended to replicate the study on a larger scale and with more personal and complicated cases for analysis of the user experience of chatbot quality.

Customer retention is crucial for a firms long term success and its application and dynamics are particularly interesting in the context of high growth firms. High growth firms are commonly characterised by having limited resources and operating in constant change in structure and routines which can affect the way the firms are able to work with customer retention. This research aims to investigate how high growth firms perceive customer retention. This research also aims to identify major difficulties high growth firms have working with customer retention as well as what strategies are used to counteract those difficulties. In order to investigate this topic, a qualitative study based on data from semi-structured interviews with seven high growth firms was conducted. My finding suggest that high growth firms has a great prioritising on customer retention. The findings also identified that limited resources and changing structure and routines is a challenge for high growth firms working with customer retention. This research identified key strategies high growth firms use to work with customer retention, being a quality customer service, customer focused culture, and relationship bonds.