View Of Customer Research Articles

Societal Impact of Machine Learning on Human Emotions

Modern networking conversations generate annotated metadata, necessitating a method for synthesizing insights from statistics. Emotion detection is crucial for practical conversations, distinguishing joy, grief, and wrath. Corpora are becoming the standard for human–machine interaction, aiming to make interactions feel natural and real. A paradigm that identifies debates and customer views can provide a human touch to these interactions. Researchers developed a machine learning framework for assessing emotions in English phrases, utilizing Long Short Term Memory perspective and real-time emotion recognition in idiomatic speech. Emotion recognition rule is created using ontologies like Word Net and Concept Net, Naive Bayes, and Random Forest. Real-time analysis of written words and facial expressions significantly outperforms current algorithms and commandment classifiers in identifying emotional states.

Big Data Analytics And Predictive Analysis In Enhancing Customer Relationship Management (CRM): A Systematic Review Of Techniques And Tools

This systematic review examines the transformative role of big data analytics and predictive techniques in Customer Relationship Management (CRM), focusing on how these advancements enhance customer engagement, satisfaction, and retention strategies. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this review analyzed a final selection of 100 articles, exploring CRM applications such as predictive modeling, real-time data processing, data integration, and Natural Language Processing (NLP). Findings indicate that predictive analytics enables CRM systems to anticipate customer behaviors and personalize interactions, while real-time data processing supports immediate responses to customer needs, essential in high-demand sectors. Data integration helps overcome silos, creating a cohesive customer view that enhances personalized engagement across all touchpoints. NLP applications, including sentiment analysis and chatbots, further improve CRM by fostering empathy and responsiveness in customer interactions. Despite these advancements, challenges related to data privacy and regulatory compliance remain central, necessitating strict data protection and ethical handling practices. This review underscores that while CRM technology is evolving to meet modern demands, effective implementation depends on a balance between technical innovation and adherence to ethical standards in data management, ultimately fostering meaningful and sustainable customer relationships.

A privacy-preserving federated learning approach for airline upgrade optimization

PurposeA key issue of making upgrade decisions is to match the most relevant upgrade offers to the right customers at the right time. To optimize upgrade strategies and profitability, companies seek to break “data silos” between themselves and other business partners for a more holistic view of customers' consumption experiences. However, multi-source data fusion may lead to potential privacy leakage. To overcome these two challenges in data silos and privacy protection, this study introduced a privacy-preserving federated learning (FL) approach and explained the process of using FL in modeling airline passengers’ willingness to pay for upgrade offers. Design/methodology/approachFederated learning is a new confidential computing technique that allows companies to train a model cooperatively by exchanging model parameters instead of the actual raw data, which might include customers' privacy sensitive information. Using a case study of a Chinese airline company, this study demonstrated how FL-based upgrade models using multi-source data can be developed to improve the accuracy of predicting customers' willingness to pay for upgrades while preserving customers’ personal data privacy. FindingsComparing with traditional unilateral model using single-source data, the federated logistic regression and SecureBoost models demonstrate better model performance. This indicates that the proposed FL approach can enhance the accuracy of modeling airline passengers' willingness to pay for upgrade offers while preserving passengers’ data privacy. The findings also show that the FL-based models generally took longer running time than the traditional unilateral model due to the design of FL approach in ensuring data privacy. OriginalityThis study contributes to the literature of upgrade optimization by introducing the new FL approach for developing machining learning models to predict customers’ reaction to upgrade offers. Although we focus on the airline industry in our case study, the proposed FL approach can be applied to other industries with a similar issue of upgrade optimization such as hotels or cruise lines, and car rental.

Analisis Persepsi Konsumen Terhadap Kualitas Produk Lavanda Brownies Karawang

The purpose of this study is to investigate customer experiences with Lavanda Karawang goods and examine how customers view the quality of Lavanda Brownies products. The purpose of the qualitative descriptive approach is to gain a deeper understanding of customers' experiences and views regarding the quality of Lavanda Brownies products following a purchase. Data is gathered by observation, documentation, and interviews. Primary data for this study came from informants, and secondary data came from a variety of publications. Validation tests were conducted utilizing a source triangulation method to guarantee the accuracy of the data. The findings indicated that, as one of the elements contributing to a company's competitive advantage, the impression of product quality is significant. Also, customers frequently repurchase Lavanda items.

Pengaruh Kualitas Produk, Persepsi Harga dan Kualitas Pelayanan Terhadap Kepuasan Pelanggan Es Coklat Ngetop di Surakarta

This research aims to determine the influence of Product Quality, Price Perception, and Service Quality on Customer Satisfaction of Popular Chocolate Ice in Surakarta. The population in this research are Ngetop Ice Chocolate consumers who are in Surabaya and have purchased the product more than once. This research also aims to analyze the influence of product quality, price perception, and service quality on customer satisfaction for Es Coklat Ngetop in Surakarta. Product quality is measured based on the taste, appearance and consistency of the chocolate ice served. Price perception is understood as a customer's view of the value of a product compared to the price they pay. Service quality is assessed from the responsiveness, competence and reliability of the service provided by the seller. The type of data used in this research is quantitative data. The sampling technique in this research used accidental with a sample of 100 respondents. The data collection technique uses a questionnaire method and data analysis in this research uses the t test and f test methods. In this research, the results show that product quality, price perception and service quality partially have a positive and significant effect on customer satisfaction. Simultaneously, these three independent variables have a positive and significant effect on customer satisfaction Based on the results of the SPSS version 29 F test, all independent variables simultaneously influence customer satisfaction. based on the results of the t test, it shows that the product quality variable has a positive and significant effect on customer satisfaction, the price perception variable has a positive and significant effect on customer satisfaction, and the service quality variable has a positive and significant effect on customer satisfaction

Predictive Analytics Techniques in Consumer Behaviour: A Literature Review

Under fierce market competition, there is a need for enterprises to analyze and predict the behavior of consumers in order to improve the market competitiveness. We find that in the previous literature, there is little specific systematic summary and research on the methods to predict customer behavior. Thus, in this paper, we discuss relevant concepts of customer behavior and predict consumer behavior by studying the operation mechanism of Big Data Analysis (BDA), Decision Tree (DT) and Consumer Relationship Management (CRM). We also study the application of each technology to enterprises in different fields and its impact on consumer behavior. BDA can efficiently organize a large amount of data into several variables that is related to the prediction and provide a reference prediction for the business. DT can effectively improve the accuracy of market segmentation, classify customers into sub-customer groups with distinct consumption characteristics, and help enterprises make targeted decisions. CRM can collect customer information through data sampling to build a comprehensive view of customers, and create customer analysis and prediction models according to the different needs of the enterprise. Studying the past consumer behavior can help enterprises to better develop products and make personalized decision plans for specific customer groups.

Describing and Sharing Molecular Visualizations Using the MolViewSpec Toolkit.

With the ever-expanding toolkit of molecular viewers, the ability to visualize macromolecular structures has never been more accessible. Yet, the idiosyncratic technical intricacies across tools and the integration complexities associated with handling structure annotation data present significant barriers to seamless interoperability and steep learning curves for many users. The necessity for reproducible data visualizations is at the forefront of the current challenges. Recently, we introduced MolViewSpec (homepage: https://molstar.org/mol-view-spec/, GitHub project: https://github.com/molstar/mol-view-spec), a specification approach that defines molecular visualizations, decoupling them from the varying implementation details of different molecular viewers. Through the protocols presented herein, we demonstrate how to use MolViewSpec and its 3D view-building Python library for creating sophisticated, customized 3D views covering all standard molecular visualizations. MolViewSpec supports representations like cartoon and ball-and-stick with coloring, labeling, and applying complex transformations such as superposition to any macromolecular structure file in mmCIF, BinaryCIF, and PDB formats. These examples showcase progress towards reusability and interoperability of molecular 3D visualization in an era when handling molecular structures at scale is a timely and pressing matter in structural bioinformatics as well as research and education across the life sciences. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating a MolViewSpec view using the MolViewSpec Python package Basic Protocol 2: Creating a MolViewSpec view with reference to MolViewSpec annotation files Basic Protocol 3: Creating a MolViewSpec view with labels and other advanced features Support Protocol 1: Computing rotation and translation vectors Support Protocol 2: Creating a MolViewSpec annotation file.

Accessibility of Halal Certification Bodies in Australia: A Website Content Analysis

ABSTRACT The increasing Muslim population and growing demands for Halal products have necessitated a corresponding growth in Halal certification. While Muslim-majority countries typically practice centralized Halal certification governance, non-Muslim countries, including Australia, have their own unique Halal certification body systems. The Australian Government recognizes 24 Halal certification bodies. Previous studies have primarily focused on the general requirements for certification. In contrast, our study takes a unique and novel approach, attempting to understand each body’s system and accessibility from the point of view of customers and food producers. This novel approach should pique the interest of our audience, as it offers a fresh perspective on a well-studied topic. We implemented website content analyses through website searches and comparative analysis to identify information that can assist Halal product consumers and certification applicants. While most bodies have established guidelines for Halal certification, several areas remain unclear, with no procedures to aid consumers and producers in checking and applying for certifications. Our study identifies these areas for improvement, with the goal of enhancing information accessibility and marketability of these bodies to assist consumers and applicants in obtaining proper guidance on Halal certification. This research is not just theoretical, but it has practical implications that can significantly improve the Halal certification process in Australia, making it more accessible and marketable. This reassurance of practical application should instill confidence in the audience about the relevance and usefulness of the study.

An Affordable Wager: The Wider Implications of Regulatory Innovations to Address Vulnerability in Online Gambling

The British government is introducing new regulatory measures to address gambling harm, including affordability checks on online players that rely on cross-operators data sharing. This article seeks to understand these measures, and their limits. Section 1 recaps what we already know about differentiated restrictions on access to gambling, including as manifest in recent state-industry efforts to deploy online gambling technologies to identify and preempt gambling harm. Section 2 summarises agreed and proposed changes to British online gambling regulation since 2019, focusing in depth on affordability checks for players and the related imperative to develop a ‘single customer view’ of play. Section 3 outlines two grounds for concern about the measures, rooted in the industry’s enthusiasm for affordability checks, and ii. the implications for groups of customers who may already be disadvantaged and hyper-surveilled. I raise these concerns in an attempt to identify a way out of an impasse, such that urgent concerns about gambling harm do not translate so readily into regulatory efforts to differentially restrict access to ever-expanding groups of adults considered vulnerable.

Social Media Tourism Marketing Optimization: Improving Promotion Effectiveness and Broadening the Consumer Base

This research investigates the price-based strategy of social media in tourism marketing, specifically in China. The study involves both primary and secondary methodology research, represented in qualitative format. The primary research evidence is collected from Chinese travelers and relevant people in the travel industry by using online questionnaires and interviews since it is a more efficient way to receive more responses within less amount of time. On the other hand, secondary evidence is collected from various online sources, including relevant and credible articles, news reports, and academic essays. According to the secondary evidence, the key areas considered in the pricing-based Marketing Landscape for the Travel industry on social media are the challenges, stakeholders perceptions, pricing-based strategies, and the impact of social media marketing. By evaluating the evidence and data, the research concludes that from both social and economic perspectives, social media marketing has a more significant positive impact than a negative one on the views of companies and customers, which benefit both firms and consumers in terms of the ability to provide better product quality. This research further shows that the tourism industry needs to adopt a pricing strategy tailored to firms specific cases in order to achieve more effective marketing and operation efficiency with long-term development.

Exploring the interplay between website quality and consumer purchase behavior in e-commerce after the COVID-19 pandemic: A study of Shopee Vietnam

Vietnam is recognized for its significant growth in e-commerce. Shopee has become the leading e-commerce platform in Vietnam in terms of revenue and market share. However, Shopee Vietnam faces several challenges, including how customers perceive its services. There is also a lack of academic studies on how the COVID-19 pandemic affected consumer buying habits, especially in relation to Shopee Vietnam. This research looks into how the quality of Shopee's website - including its system, information, and service quality - affects customer buying behavior. The study uses a theoretical framework and tests ten hypotheses using a quantitative approach. Data was collected from 309 Shopee users through a questionnaire and analyzed with SPSS and AMOS 22.0 software. The results show that only information quality and system quality significantly influence customer buying behavior, with service quality having no notable effect. Information quality is the most influential factor. The study concludes that customers view Shopee.vn not just as a place to buy, sell, and ship goods but also as a source of information for searching, exploring, and comparing data.

Analysis of TF-IDF and TF-RF Feature Extraction on Product Review Sentiment

Sentiment analysis of product reviews is critical in understanding customer views and satisfaction, especially in the context of e-commerce applications. A marketplace provides channels where users can submit reviews of the products they purchase. However, due to the large number of reviews in a marketplace, analyzing them is no longer feasible to be performed manually. This research proposes a machine learning implementation to perform sentiment analysis on product reviews. In this research, the product review dataset on Shopee marketplace is used for sentiment analysis by comparing TF-IDF and TF-RF feature extraction using the SVM algorithm with stages of dataset, labeling, feature extraction and accuracy results. The importance of the comparison between TF-IDF and TF-RF feature extraction in this research is related to the need to evaluate and determine which feature extraction method is most effective in increasing the accuracy of sentiment analysis. TF-IDF and TF-RF are two methods commonly used in text analysis, and a comparison of their performance can provide deep insight into the effectiveness of each in the context of product sentiment analysis.Thus, through this comparison, this research aims to determine the best approach that can provide the highest accuracy results, so that the results can serve as a guide for further research. Based on the evaluation, the highest accuracy value is achieved at 92.87% by using TF-IDF and SVM classifiers which outperformed previous research.

The Beneficiary's Perception of their Awareness of Delay in Payment in Social Security Benefits in Tanzania

The study investigates beneficiaries' perceptions of their awareness of social security benefit delays, the relationship between employers' responsibility and social security benefit delays, and the effects of persistent NSSF bureaucracy on social security benefit delays in Tanzania. An explanatory study design was employed in this study with the use of a mixed quantitative and qualitative approach. The study included 150 NSSF customers and 5 key informants from employers. Data collection was conducted using a questionnaire and interview guide, respectively. This study examined NSSF beneficiaries' perceptions in Tanzania regarding delays in social security benefit payments. It reveals that a substantial proportion of customers attribute delays to employer actions, such as failures in timely contributions and inactivity in following up. The study underscores shared responsibility among customers, employers, and the system. It is concluded that addressing customer views through increased communication, employer engagement, and streamlined processes is critical for improving NSSF system efficiency and customer satisfaction. The study recommended that to improve the efficiency of benefit payments within Tanzania's National Social Security Fund (NSSF), it is advised to increase employer engagement and education, strengthen communication with stakeholders, revise policies to hold employers accountable, streamline bureaucratic processes, modernize operations, and investing in employee training

ANALISIS ELEMEN-ELEMEN BRAND EQUITY RUMAH SAKIT PKU MUHAMMADIYAH GOMBONG

Increasing competition in hospital, which in the view of many private hospitals are well established in Gombong, PKU Muhammadiyah Gombong hospitals must have a strong brand equity to maintain or retain old customers and interesting new customers. Research is important conducted to determine and analyze ratings and views of customer on the hospital, other than research about brand equity in the hospital still rarely done.
 To know the views of consumers on brand awareness, brand association, perceived quality and brand loyalty PKU Muhammadiyah Gombong Hospitals. The study was quantitative descriptive design. The study was conducted on 25 February - 3 June 2011 in the region Gombong. Population are all community Gombong had ever feel the services PKU Muhammadiyah Gombong Hospital. Number of sample was 100 respondents. Sampling design used was purposive sampling. Analysis of data used descriptive statistics, Cochran's test, the average value, semantic differential scale and importance vs. performance comparison
 PKU Muhammadiyah hospitals as a top of mind awareness Gombong society. Based on calculations by the Cochran test at the brand association, there are 9 associations are closely related. Based on the results of the analysis of perceived quality, there are seven attributes of a good scale range (3.40 to 4.20) and 3 attributes entered enough scale range (2.60 to 3.40). Analysis of brand loyalty found: Switcher buyers equal to 23%, category simply (3.01). Habitual buyers is equal to 55%, both categories (3.44). Satisfied buyer equal to 49%, both categories (3.46). Liking the brand equal 43%, both categories (3.51). Commited buyers by 33% and include enough category (2.79) PKU Muhammadiyah Gombong Hospitals have a strong enough brand equity.

THE MAGNIFICENCE OF THE BRAND AND ITS IMPACT ON WORD OF MOUTH (FIELD RESEARCH AT PEPSI COMPANY BAGHDAD

The current research aims to reveal the nature of the relationship between brand coolness and Word-of-Mouth, as the variables of the current research are considered critical variables in the literature of marketing management as well as their importance to any company, as all companies seek to have their brands characterized as coolness, which is reflected in the opinions of customers about those companies. It may lead to coolness about the companies, and in order to achieve the goal of the research, the researcher distributed (350) questionnaires to the employees of Pepsi Baghdad Company.(325) of them were obtained, and the number of valid questionnaires for analysis was (302) questionnaires, and they were analyzed using the statistical program SPSS v.26 Discussions between customers about the company, so the research recommends that the company, the research sample, and Iraqi companies in general should pay attention to their products in order to live up to being described as wonderful, which will benefit those companies and improve their image from the point of view of customers

The Exploration of Consumer Perception on Preserving Traditional Daqing Oil Pottery Motifs Design in China

This study investigates how Chinese consumers feel about traditional Daqing Oil Pottery themes being preserved. This study uncovers the significant cultural importance associated with these motifs, which have an influence on consumer choices and the region’s economic stability. One important aspect influencing Daqing Oil Pottery’s output and sales is shifting customer views. This study uses a use an organised database of secondary sources that includes academic publications and article journals. The results highlight the implications of the economy in comprehending and maintaining traditional art forms.

Digital innovation and de‐branching in the banking industry: Customer perception and satisfaction

AbstractIn the ever‐changing landscape of the banking industry, digital transformation has become a major challenge. Banks are transitioning towards digitalisation by utilising information and digital technologies while reducing their branch networks. This paper investigates the relationship between technological innovation and banking customers' perception and satisfaction. By analysing a comprehensive consumer finance survey, we assess how the digital transformation of banks is perceived by customers and its impact on their satisfaction. Our results demonstrate that customer perceptions of a bank's digital innovativeness are positively associated with effective digital transformation. Customers tend to be more satisfied with banks that have a higher degree of digitalisation. Furthermore, our findings reveal that customers view banks as more innovative when the reduction in bank branches since the pandemic has been more intense. These insights shed light on the technological transformation of banks and its influence on their customers, providing valuable information for banks seeking to navigate the digital landscape and improve customer satisfaction.

ANALISIS SENTIMEN TINGKAT KEPUASAN PELANGGAN TERHADAP LAYANAN KURIR J&T EXPRESS MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) BERDASARKAN ULASAN PENGGUNA DI GOOGLE PLAYSTORE

Courier Service Is One Of The Services That Are Widely Used By The Public, Especially In The Current Digital Era. In This Context, Courier Services Allow Shippers To Deliver Goods Or Documents Without The Need To Be Present Directly To The Destination Location. J & T Express, As One Of The Shipping Expedition Service Providers In Indonesia, Is The First Choice For Many People. Although Technology Continues To Evolve And Competition Is Increasingly Fierce, The Quality Of Courier Services Is A Key Factor That Customers Need To Pay Attention To. However, It Should Be Noted That The J&T Express Application In The Google Play Store Received A Low Rating, And This Is The Background Of This Study. the main focus of this study was to identify the level of customer satisfaction with j&t express courier services through reviews available on the google play store. within the framework of this study, sentiment analysis was conducted using the support vector machine algorithm, by applying crisp-dm methodology. the results showed that from the business understanding stage to the modeling stage, the performance of the support vector machine can be considered good. in addition, this study also resulted in an implementation that can be accessed through a website with the address jnt-sentiment.streamlit.app. hopefully, this research can contribute to j & t express in understanding the views of customers and improving the quality of their services

Comparing non-compliances and non-conformities: The different points of view of pig slaughterhouse operator, competent authority and customers

The food business operators (FBOs) hold the main responsibility for food safety, based on the Regulation (EC) No 852/2004 and realized by the application of the hazard analysis and critical control point (HACCP) principles. They should implement a self-checking system (SCS) and may adopt voluntary food safety management system based on international standards, that are believed to strengthen HACCP functioning. Both official controls conducted by the Competent Authorities (CAs) and private voluntary standards play essential roles in maintaining food safety. In addition, customer complaints are highlighted as valuable feedback for FBOs, contributing to continuous improvement efforts. The present study aimed (i) to compare the non-compliances assigned by the CA during official inspections and audits carried out in a large slaughterhouse with the non-conformities registered by the FBO in the SCS during a five-year period, (ii) to evaluate, in the same period of time, the customer complaints managed by the FBO as non-conformities being part of the Food Safety Management System, and (iii) to examine potential overlapping of SCS and official controls. The majority of non-conformities/non-compliances in the slaughterhouse were related to the finding of non-conforming products, maintenance deficiencies, and lack in housekeeping and hygiene. The types of observations varied among the three groups—FBO, CA, and customers—with different areas of focus. Both official controls and SCS are of crucial importance and can sometimes overlap, but the suggestion to reduce the frequency of official inspections should not be considered because such controls have different values and are both crucial. Moreover, those controls should nevertheless be complemented by attentive consideration of customer complaints.

Beyond 'single customer view': Player tracking's potential role in understanding and reducing gambling-related harm.

Usage of electronic gaming machines (EGMs) and on-line gambling is strongly associated with gambling-related harm. Player-tracking systems can monitor a gambler's activity across multiple sessions and/or operators, providing a clearer picture of the person's risk of harm with respect to these gambling formats and enabling harm reduction efforts. The Finnish and Norwegian state monopolies have player-tracking systems in place, while the United Kingdom is implementing an operator-led system called 'single customer view' for on-line gambling, and Australian states are proposing similar 'player cards' for land-based EGMs. Player tracking can advance harm reduction efforts in three ways. First, player tracking improves our understanding of gambling-related harm by providing data on how the population gambles, which can potentially be linked with operator, government and/or prevalence data sets. Secondly, player tracking can be used to implement harm reduction measures such as expenditure limits, self-exclusion and age verification. Thirdly, player tracking can provide a platform to evaluate harm reduction measures via gold-standard field trials. These potential benefits need to be weighed against various practical and ethical issues. The potential benefits of player-tracking systems would be maximized via systems administered independently of the gambling industry and implemented universally across all gambling in a given jurisdiction.