Customer Feels Research Articles

AN EXPLORATORY INVESTIGATION OF CUSTOMER SATISFACTION IN MOBILE COMMUNICATIONS: EVIDENCE FROM ROMANIA

Due to the technological evolution, telecom companies play a critical role of the entire economy with the importance of the provided services, that are inseparable of the daily activities in a business scope but in the same time for the daily life of the population. Being a dynamic and a competitive market, the customer satisfaction for the service provide is crucial for every telecom provider because the investment and continuously understanding the customer feelings and experiences because only in this way every telecom operator can deliver to their customers the expected services. This study will complete the literature that are focused on the customer satisfaction on mobile communications through the applied research model, the presentation of the theoretical concepts as customer satisfaction, mobile technologies including 5G, quality of service in telecommunication, network quality, information security, customer support and information quality. The research method was chosen a quantitative one as a questionnaire, there were formulated six hypotheses based on the dimensions chosen and were validated using one of the statistical tools as SPSS.

فاعلية توظيف العلاقات العامة لربورتات الدردشة في التعريف بالخدمات في المؤسسات الحكومية

The study aimed to describe the effectiveness of employing public relations for chat bots in defining services in government institutions, by knowing the manifestations of public relations practitioners' interest in knowing information about chat bots and employing them in defining services in government institutions, services and areas of use, as well as the benefits achieved and the obstacles they face in this field, reaching their suggestions and their evaluation of the impact of these applications on their professional competence, and the future of public relations in light of chat bots. The study used the descriptive approach, and among the tools, the interview was used, and a questionnaire on the reality of public relations practitioners' use of chat bots in defining services in government institutions. The study sample consisted of (240) employees in the Corporate Communications and Public Relations Department in government institutions. As for the results of the study, it showed great interest from public relations practitioners in government institutions in chat bots and their use in managing corporate communication, as their aspects of use varied between crisis management and meeting the needs of the public. These technologies have contributed to improving the professional efficiency of most of the respondents by enhancing daily performance, speed of accomplishment, planning and decision-making. However, users faced challenges such as the difficulty of robots understanding customer feelings and fear of losing jobs. They suggested linking promotion to their ability to use them and provide training and technical support. Despite the benefits of robots, there are still concerns about the future of the public relations profession in light of this technology.

Unravelling tourism destination's competitiveness using big data analytics: a comparative analysis

PurposeThe competitiveness of destinations is crucial for tourism. In this context, the study aims to uncover customer satisfaction, experiences, feelings, and thoughts by conducting a comparative analysis of social media comments from various competitive tourism destinations.Design/methodology/approachBig data research was conducted to answer the research questions. The data was collected on a social media platform focusing on three destinations in the Mediterranean region. Three methods were employed to analyse the data: sentiment analysis, topic modelling, and named-entity recognition.FindingsThis study addressed traveller satisfaction levels. It identified the topics concerning each destination, examined the emotions expressed by travellers about these topics, explored the potential impact on future behaviour, and investigated the features of the destinations and satisfaction levels about these features. It also identified the prominent food and beverage names in destinations and explored tourists’ preferences regarding these foods and beverages.Research limitations/implicationsThe limitations of this study relate to the sample. The data used in this study was solely obtained from a single social media platform and focused on English-only comments. Further research that includes different social media platforms for hotel categories and considers reviews in local languages could capture a broader range of customer opinions and experiences.Practical implicationsPolicymakers can gain insight into a destination’s position in the competitive landscape. This study has numerous implications for policymakers in the relevant destinations and managers in the design and implementation of services.Social implicationsThe findings of this study can have broader societal implications if considered and implemented by decision-makers and tourism businesses in the context of competitiveness.Originality/valueThe study’s originality lies in integrating multiple disciplines and comparing tourism destinations using big data. This study improves the understanding of competitiveness in three specific Mediterranean destinations. Previous research has focused on different contexts in these Mediterranean destinations. Therefore, the study fills this gap by focusing simultaneously on all three destinations in the context of competitiveness.

The Barbie Movie Collaboration

The aim of this research is to find out strategies for success in entering the market through collaboration with local brands of Barbie products even though the film has not yet been released. Using qualitative research with a cyber phenomenology approach. This research model uses a simple design with Triangulation Theory. Data collection techniques used were observation, interviews and documentation. The data analysis technique used is Manual Data Analysis Procedure (MDAP). The results of this research found that 3 local brands ESQA, SOVLO, Day and Night use marketing strategies: Marketing Mix; Segmentation (Geography, Demographics, Psychography, Behavior); Cooperation Patterns Marketplace; Timing Strategy (Viral, Building Hype) with Co-Branding: Uniqueness; Awareness; Positive Customer Feelings (Consumer Rating); Favorable (Instagram Poll, Question Box); Positive Customer Judgment (Review Before Launching).

Exploring factors and customer perceptions of airport services: A quantitative textual analysis

<span lang="EN-GB">This study conducted an analysis of 1500 user generated content from Google Travel to examine the factors influencing airport services and customer perceptions. Quantitative textual analysis is employed to extract meaningful insights. Our findings highlighted the most frequently used words in airport user generated content, reflecting critical aspects of airport experiences such as the airport itself, the quality of service, and international travel. A cluster analysis revealed five distinct clusters, representing flight operations, location, views, customer feelings, and intangible services. A co-occurrence network analysis showed strong correlations among keywords associated with positive experiences, underscoring the importance of service quality and infrastructure in customer satisfaction. Furthermore, through topic modeling, we categorized words into five distinct groups: airport flights, ground services, international services, customer experience, and location. The practical implications of this study are substantial. The insights can help airport management identify strengths and areas needing improvement, ultimately enhancing customer satisfaction and the overall airport experience.</span>

Antecedents Word of Mouth Intention in the Restaurant Industry

A restaurant is a place that provides good service to all its customers, both in the form of food and drinks. This research aims to investigate the antecedents word of mouth intention This research uses a quantitative approach with a survey method. with a sample size of 102 respondents. The data collection tool in this study used an online questionnaire which was distributed to respondents using a non-probability sampling approach using a purposive sampling technique with the criteria of using respondents who visited the restaurant at least once a year. Data analysis using PLS-SEM. The contribution of this research is to expand the factors that influence positive customer feelings towards restaurants such as environmental quality, food quality, service quality, and comfort. Service Encounter and Awareness as mediation to explain its influence on word-of-mouth intention. The results show that food quality, personal interaction quality, physical environment quality, perceived value, Service Encounter, and Awareness have a significant effect on word-of-mouth intention. This research implies that there is an influence between food quality, personal interaction quality, physical environment quality, and perceived value with word-of-mouth intention, so it can be concluded that food quality and interaction quality can shape customer relationships in providing positive recommendations about restaurants so that customers will visit. return to the restaurant.

A CONSUMER SENTIMENT ANALYSIS METHOD BASED ON EEG SIGNALS AND A RESNEXT MODEL

E-commerce is becoming increasingly dependent on technologies such as consumer sentiment research at an ever-increasing rate. Its purpose is to recognize and comprehend the feelings and dispositions of customers by analyzing customer language and behavior as expressed in social media, online reviews, and other forms of digital communication. The proliferation of digital technology has resulted in an increase in the number and variety of channels through which customers can communicate their feelings. Gaining a comprehensive understanding of consumer sentiment may be of great use to businesses, as it enables them to better satisfy customer demands, enhance their products and services, improve their brand reputation, and ultimately increase their level of competitiveness. As a result, consumer sentiment research has evolved into a tool that is essential for the decision-making process in e-commerce as well as the management of customer relationships. Within the scope of this discussion, this study uses deep learning models to improve consumer sentiment research precision. The following is the list of the primary contributions that this paper makes. (1) Advancing the use of EEG signals as a basis for a method for analyzing customer feelings. This technique measures brain activity directly, thus avoiding the restrictions and ambiguities that come with relying on verbal expression. (2) The purpose of this study is to improve the overall performance of the model for analyzing sentiment by incorporating an attention mechanism into the ResNeXt model. This attention mechanism is intended to augment the model’s capacity to extract subtle characteristics. (3) The results of the experiments show that the strategy described in this study is effective in improving EEG-based sentiment analysis performance. When compared to standard text-based sentiment analysis approaches, this sentiment analysis model demonstrates greater objectivity, real-time capabilities, and multidimensionality when applied to consumer sentiment analysis in e-commerce.

Komunikasi Interpersonal Customer Service Lotte Grosir dalam Melayani Pelanggan di Kota Samarinda

Interpersonal communication plays an important role in a company, one of which is retail, the quality of good interpersonal communication needs to be mastered by customer service because it deals directly with customers, the quality of interpersonal communication is needed to create good service for customers. The purpose of this study was to determine the interpersonal communication process of Lotte Grosir's customer service in serving customers in Samarinda City. The research method used is a qualitative method. Data collection techniques include interviews, observation and documentation. The informants in this study consisted of 3 customer service people, 1 guard manager and 2 customers. The results of this study indicate that there are 6 elements found in the field, namely self-introduction and other individuals from customer service openness to customers and customer service digging into customer backgrounds to reduce uncertainty to customers. Knowing the situation can be seen from the way customer service listens to complaints experienced by customers before providing solutions. Creating and maintaining meaningful relationships is evident in customer service. Providing service to customers in a friendly and courteous manner, not hurting customer feelings, giving trust to customers. Persuasion is seen when customer service provides options for exchanging goods before a refund is made if there is a discrepancy with the customer. Relaxed interactions can be seen from the way customer service makes jokes to customers, but one customer service that lacks initiative tends to wait for customers who ask questions. Helping seen from customer service helps reduce cognitive and behavioral uncertainty in customers in making decisions if customers feel unsure about their choices.

A Branch-and-Cut algorithm for the dial-a-ride problem with incompatible customer types

Ridepooling is expected to become more and more important in people’s mobility. At the same time, autonomous vehicles are expected to be widely used in such applications in the future. While the driver as a person of trust currently provides security, passengers are alone with strangers in an autonomous ridepooling vehicle. In the paper, we address this aspect by including incompatibilities between customers, meaning that incompatible customers cannot share the vehicle at the same time. Although incompatibilities can be defined in any way by the provider, they can be set, for example, if a customer feels unsafe in sharing the vehicle with customers of a certain type. As other compatible customers can replace the driver as a person of trust, we present a second setting where all customers are allowed to share the vehicle at the same time, but customers are never alone in the vehicle with incompatible customers. We present Branch-and-Cut algorithms for both problem settings including methods to improve the search with respect to the incompatibilities. We show in a computational study that the introduced methods improve the search significantly and evaluate the Branch-and-Cut algorithms on realistic instances with up to 120 customers and 10 vehicles. Moreover, our results suggest that it can be a beneficial option for the provider to allow their customers to participate in the decision process by indicating incompatibilities for types of customers, meaning that they do not want to share a vehicle with a customer of an incompatible type.

PENERAPAN METODE CUSTOMER SATISFACTION INDEX (CSI) dan SERVICE QUALITY DALAM MENENTUKAN TINGKAT KUALITAS PELAYANAN TERHADAP KEPUASAN CUSTOMER WEDDING ORGANIZER

customer satisfaction process relates to the quality of service products in the CV. X company. More and more customers are on a CV. X then the company is required to provide a quality service to increase customer satisfaction, of course, a method is needed to analyze the level of customer satisfaction. This study aims to determine the value of the customer satisfaction index and service quality on a CV. X to improve the level of service quality according to the will of consumers. The results of this study include providing a customer satisfaction index and service quality value of 74%. In the five dimensions of tangible, reliability, responsiveness, assurance, and empathy, all these dimensions have negative gap values (-). The average tangible gap is 0.608; the staff was very quick in setting up the facility (-0.23); quick and easy ordering process (-0.20); and the staff is very responsive in taking care of all the needs of the guests (-0.17) with an average gap of -0.597 then the responsiveness of the attribute statement is that the WO team can reprimand the mistakes of the guests (-0.20), the WO team can accept criticism from the customer (-0.23), the WO team serves wholeheartedly so that the customer feels commensurate with the price paid (-0.06).

Alternative Insitutions on Dispute Settlement For Financial Services Sector (LAPS SJK) in Banking Disputes

A dispute is a problem submitted by the Customer or Customer Representative to the bank mediation organizer, after going through the complaint resolution process by the Bank. When the customer feels that the problem is not resolved through Complaint to the Bank, a dispute is born here. Disputes between the Bank and the Customer are inevitable because of the legal relationship between the two. Dispute resolution solutions are carried out through litigation or court and non-litigation channels. One of the best steps in resolving disputes between banks and customers is through Mediation which is facilitated by the Alternative Insitutions on Dispute Settlement For Financial Services Sector/Lembaga Alternatif Penyelesaian Sengketa Sektor Jasa Keuangan (LAPS SJK). The purpose of writing this article is to examine the optimization of the role of mediation for banking disputes. The settlement process at LAPS for the Financial Services Sector is confidential. The term confidential here means that the announcement is not announced. It prioritizes a win-win solution. Therefore it is more comfortable for the parties. Ultimately there will also be able to maintain consumer confidence in the financial services sector.

Analisa Sentimen Pelanggan pada Review Belanja Online Berbasis Text Mining Menggunakan Metode K-Means

Technological developments have changed conventional sales to online sales. In online sales, a review from a customer is a very important thing that needs attention, because customer reviews will show the quality and credibility of a sale. Customer reviews can increase or attract new customers or vice versa. Therefore reviews from customers need to be carried out sentiment analysis to know and understand, preferences and feelings of customers towards a product or service in online business. One of the analyzes that can be done is by clustering reviews from customers so that it can be seen from what side the customer dissatisfaction arose. In this study an analysis will be carried out by utilizing text mining from customer reviews by conducting clustering reviews using the K-means method. By grouping customer reviews, a model can be formed to classify the types of reviews according to their class. From the research conducted, it can be concluded that the k-means clustering method can be used to analyze customer sentiment grouping with the number of clusters produced there are 3 groups, namely in cluster 1 complaining about slow delivery, in cluster 2 it leads to a mismatch of goods ordered with goods received by customers, while the results of cluster 3 customer sentiment lead to service and packing. The results of this modeling can be used as a basis for making improvements in sales services at online stores.

KAREN’S DINER JAKARTA MARKETING: UNIQUE SERVICE EXPERIENCE BECAME AUTOPILOT MARKETING

In Hospitality industry, courtesy became the most important part doing a service to the guest. Karen’s Diner brings a new concept of hospitality which is different than the usual service. Using type unfriendly waiter/waitress when doing a service, became a kind of attraction for the guest that make them want to try the sensation the rough service. From hospitality point of view, this kind of service wasn’t proper for the guest. Especially in Indonesia well known for warm hospitality. But many people upload their experience in social media make them proud have tried Karen’s Diner. This research uses the qualitative descriptive and used data collection techniques such as literature studies, documentation through social media Tik Tok and internet source. Many customer feels proud and happy for trying Karen’s Diner because of Karen’s Diner existences on social media. They makes many posting on social media and goes viral. After many customer curious and try their service, some of the customers feels unpleasant because the service and post their experience in social media. So many pro’s and con’s on social media makes Karen’s Diner more famous. The source of the research object was limited from the papers, only can find on online source. The authors suggests to makes more research about Karen’s Diner to make it more valid. There’s no previous research about Karen’s Diner especially in marketing.

OPTIMIZATION OF THE REPLACEMENT PROCESS FOR THE BRAKE SHOES ISUZU GIGA TRUCK AT PT AI-ISO DM JAKARTA BRANCH

PT AI-ISO workshop on DM Jakarta provides various repair and periodic maintenance services. In periodic maintenance, brake repair jobs have problems replacing the brake pads (brake shoe set) of Isuzu Giga Trucks, which takes about 9 hours. To reduce the processing time, an improvement process is carried out to shorter processing time, so the customer feels more satisfied with repairing his vehicle. From observations, the length of work time was due to the process of changing the brake pads outside the workshop due to the absence of tools to install the brake pads. The repair shop offers to replace a set of brake pads, but the price is higher than just replacing the brake pads, so the customer makes this choice. The improvement made was the manufacture of a rivet installation tool on the brake pads based on the workings of a rivet machine. First, it is necessary to make a brake pad holder so that it does not shift when pressed and ensures that the pressure acting on the rivet is as requested. This tool is also equipped with a Standard Operation Procedure to make it easier for technicians to replace brake pads. The result is a decrease in processing time for the brake pad replacement process from an average of 9 hours to 5 hours. With these tools, repairing the brake system can be accelerated and within the safe limits required in the vehicle's manual, and the customer will be more satisfied.

Ordinary customer experience: Conceptualization, characterization, and implications

AbstractAlthough businesses strive to create extraordinary customer experiences, it is the ordinary experiences that form the backbone of customers' lives and hold the greatest potential for creating meaning and relevance. This conceptual study aims to shed light on the sources, characteristics, and mechanisms of the ordinary customer experience by conducting a scoping review of literature from various fields, including sociology, philosophy, consumer behavior, psychology, marketing, and management. The findings demonstrate that researchers characterize the ordinary customer experience as familiar, simple, and mundane—and thus often taken for granted—and as formed through customers' daily routines. This study defines the ordinary experience as the accumulation of a customer's perceptions, feelings, and sensemaking of customer‐specific, contextual, and offering‐related stimuli that are meaningfully and purposefully present in the customer's daily life. The ordinary experience representing a lived and reflective phenomenon is characterized as peripheral, predictable, neutral, acceptable, longitudinal, and convenient. Despite its seemingly mundane nature, the ordinary customer experience provides valuable insights into customers' sensemaking of experiences. By reconciling and bridging understandings from various fields, this study presents a comprehensive view of the ordinary customer experience and contributes to a more granular and holistic understanding of the ordinary in the marketing domain. It offers an alternative perspective on customer experience that extends beyond the conventional ordinary–extraordinary continuum.

Emotional connection and customer orientation as moderators in improving the customer satisfaction–behavioral intention link: A moderated moderation service model

Customer engagement is one of the significant operational and quality practices service providers use to build service experiential relationships with customers. The purpose of this paper is to examine the moderating role emotional connection and customer orientation play in customer relationship building. A quantitative survey method is carried out among 515 self-reported active members at a single fast-growing non-denominational faith-based organization in Southwestern United States. Using a hierarchical multiple regression to evaluate our research model, we find relationship satisfaction is positively associated with customers’ behavioral intention in doing business with a service firm, while emotional connection shows no moderating effect on such a relationship. However, we found a significant three-way interaction effect of relationship satisfaction, emotional connection, and customer orientation on behavioral intentions. Customer orientation strengthens and fortifies the relationship between satisfaction and behavioral intentions for customers with high emotional connection than for customers with low emotional connection. The focus on customer orientation and emotional connection provides a framework that can assist service firms develop quality operational strategies that target the emotions and feelings of customers to value the relationship while supporting service employees with quality operational practices and customer orientated activities to better manage customers.

SOCIAL COMPANION CHATBOT FOR HUMAN COMMUNICATION USING ML AND NLP

The advent of chatbot technology has led to a significant shift in the humans communicate with machines. Chatbots powered by Machine Learning (ML) and Natural Language Processing (NLP) can interact with humans naturally and conversationally. This chatbot's primary objective is to provide companionship to individuals who may feel lonely or isolated. The chatbot prompts customers to express their feelings and provides a personalized response based on whether the customer's feelings are positive or negative. The chatbot's development involved designing a userfriendly interface and integrating natural language processing techniques to enable more human-like conversations. If the customer's response matches one of the feelings in the respective list, the chatbot responds with empathy and requests the customer to describe their feelings in more detail. Overall, the chatbot enhances customer support by providing personalized communication with customers.

Evaluation and Analysis of the Impact of Customer Satisfaction of After-sales Service of Medical Equipment on Financial Performance-Taking a Medical Equipment Company as an Example

Abstract Taiwan's high-end medical equipment industry has been updated rapidly, especially the emphasis that medical institutions place on medical quality is reflected in the consumer demand market. In order to improve performance, in addition to promoting new equipment products, equipment manufacturers must pay more attention to customer feelings and sales satisfaction. This study aims at medical professional customers' satisfaction with the after-sales service customer service of medical equipment companies, using questionnaire surveys, and Use statistical analysis to detect the correlation and influence among variables, and make internal adjustments and service upgrades for the more influential variable groups to focus on projects, improve the overall after-sales service satisfaction, and then drive the growth of the company's performance and performance. According to the research results, the service items valued by the customer group can be significantly affected by the five dimensions in the conceptual model of service quality (PZB, 1988): 1. Reliability 2. Responsiveness 3. Assurance 4. Empathy 5. Tangible, so medical equipment manufacturers should continue to maintain good technical service quality, in order to improve customer satisfaction and loyalty. These results can be used as a reference for enhancing the internal core value of the enterprise and planning marketing strategies. Keywords: Medical equipment, Service quality conceptualization model, After-sales service customer satisfaction.

Sentiment analysis algorithm using contrastive learning and adversarial training for POI recommendation.

Finding a suitable POI based on the user's needs and intentions is a complex decision-making process. Obtaining valuable information from the vast amount of social media data and using it for travel recommendations is a challenging issue. Traditional POI recommendation algorithms do not fully take into account the true feelings of customers about tourist attractions implied in social media data because they usually require a large amount of tagged travel commentary data. This study presents an aspect-based sentiment analysis model and POI recommendation method to accurately capture sentiment information contained in social media data with a small amount of tagged data. The pre-training model BERT is used to obtain the embedded representation of words that fuse the semantic information of the text. Using contrastive learning, point clusters belonging to the same class in the embedded space of words are pulled together, and sample clusters from different classes are separated. The potential relationship between comment ratings and their impact on user perception is analyzed, and the best performance formula for the loss function is determined. The test accuracy and F1-Score of the model in the experiment improved by 13.03% and 12.23%, respectively, compared to the BERT base model. POI recommendation validation is performed using a variety of recommendation algorithms. The experimental results show that the addition of aspect-based sentiment attributes can effectively improve the accuracy of recommendations.

Online-Review-Driven Products Ranking: A Hybrid Approach

Online customer reviews (OCRs) are the real feelings of customers in the process of using products, which have great reference value for potential customers’ purchase decisions. However, it is difficult for consumers to extract helpful information from very large numbers of OCRs. To support consumers’ purchase decisions, this paper proposes a hybrid method to rank alternative products through OCRs. In this method, we use the fine-grained Bidirectional Encoder Representation from Transformers (BERT) model for aspect-level sentiment analysis (SA) and convert SA results of sub-criteria into a corresponding interval intuitionistic fuzzy number, accurately extracting customer satisfaction in OCRs and reducing the errors caused by different amounts of OCRs. Furthermore, in order to obtain the ranking results of products, the subjective and objective weights are combined to determine weight of feature. Subsequently, an improved interval intuitionistic fuzzy VIKOR method is proposed to rank mobile games. Finally, we conduct a case study and make some comparisons, which show that our method can reduce the complexity of accurately obtaining consumers’ personal preferences and help consumers make more accurate decisions.