Product Customer Research Articles

Tradition and Innovation in the Italian Wine Industry: The Best Practices of Casa Paladin

This study aims to make a significant contribution to the development of a model for integrating research in the wine sector, innovative knowledge, and family businesses with the traditional mode of production in the context of the introduction of modern production technologies with a view to sustainability and the improvement of services in tourism. From a methodological point of view, the research is based on the case study and, in particular, on Casa Paladin, a family business in the Italian wine sector, which bases its strategy on innovation in production processes and customer relations to obtain high product quality with the aim of meeting consumer needs. The findings underscore the crucial role of family businesses in preserving cultural and traditional elements in the wine sector, with technology and innovation serving as vital drivers for their development. Casa Paladin’s commitment to innovation in production processes and products is evident, emphasizing sustainability as a core element that impacts customer relationships and product quality. Enotourism, including tastings, festivals, and fairs, emerges as a significant aspect contributing to the promotion of the company’s history, culture, and traditions. This study posits Casa Paladin as a notable example in the Italian wine industry, offering transferable insights for other businesses. Its successful integration of culture, innovation, and sustainability contributes to a broader understanding of the contemporary role of family businesses in the Italian wine sector.

Evaluation and Improvement of Business Processes in the Operational Division Using Business Process Improvement (BPI) (Case Study: PT. Mitrasukses Engineering Indonesia

PT. Mitrasukses Engineering Indonesia (MEI) is a manufacturing company specializing in custom machine production. The company has an operational division responsible for managing product orders until they are delivered. The main problem in the operational division of PT. MEI is the inconsistency between product designs and customer needs, leading to machine design redesigns and delays in order processing. Therefore, a more detailed analysis of potential errors is required, followed by recommendations for improvement through business process improvement. The methodology used to analyze potential errors is the Failure Mode and Effect Analysis (FMEA) method. Meanwhile, the methodology used to provide improvement recommendations is the Business Process Improvement (BPI) method with the streamlining tools. The improvement measures adopted include streamlining tools such as Standardization, Upgrading, Simplification, Automation, and Error Proofing. Simulations will be conducted after modeling the improved business process based on the improvement recommendations. The simulations compare the time between the current business process model (as-is) and the improved business process model (to-be) to determine the percentage increase in efficiency. Efficiency occurs due to changes in process activities in the current business process that has been improved. The simulation results indicate an efficiency improvement in the product ordering process by 16.58%, material procurement process by 35.37%, production process by 38.85%, and product delivery process by 22.42%.

Determination of Mahkota Gold Pringsewu Customer Satisfaction

Because of their abundance, Pringsewu's gold stores face fierce competition. Service quality, product quality, product design, and gold cleaning quality are what distinguish one business from the others and help it maintain customer loyalty. The goal of this study is to discover and explain how marketing messages and product quality influence customer satisfaction. This research takes a quantitative approach. There were 110 participants in this research overall. Using the Simple Random Sampling approach, 86 respondents were selected from the Mahkota Gold Pringsewu customer base for this study. This study relied on primary data. The data for this study was gathered using a Likert scale questionnaire technique. According to the findings of the study on Determining Customer Satisfaction at Mahkota Gold Pringsewu, there is a positive and significant relationship between product quality and customer satisfaction; there is also a positive and significant relationship between product quality and marketing communication, and there is a positive and significant relationship between the two for Mahkota Gold Pringsewu customers. This implies that high-quality products and marketing messages have a big influence on consumer happiness.

THE INFLUENCE OF PRODUCTS AND PROMOTIONS ON CUSTOMERS' DECISIONS TO SELECT PRODUCTS AT PT. PRUDENTIAL LIFE ASSURANCE SYARIAH IN THE SUNGAI PENUH CITY

This research aims to determine whether products and promotions influence customers' decisions to use Sharia insurance products. The location of this research is at PT. Prudential Assurance Sungai Penuh City. Data collection techniques in this research are observation, questionnaires and documentation. Meanwhile, the data analysis techniques in this research are questionnaire instrument analysis (validity and reliability), normality test, multicollinearity test, multiple linear regression, coefficient of determination test, and hypothesis testing. The subjects in this research were agents and customers of Prudential Life Assurance insurance products. The population in this study was 217 customers, while the sample was 90 customers using education insurance products in 2023. The research results prove that product variables partially significantly affect the public interest in the Prudential Life Assurance insurance product in Sungai Penuh City. Partially, the product promotion variable only significantly affects the public interest in PT. Prudential Life Assurance insurance in Sungai Penuh City. In simultaneous testing, product and promotional variables significantly affect public interest in Prudential Life Assurance insurance in Sungai Penuh City.

THE INFLUENCE OF MARKETING MIX ON SATISFACTION AND LOYALTY OF RICE CUSTOMERS AT PT. KOMODITI TANI INDONESIA

Customers are the most crucial aspect of running a business, so companies need to maintain customer satisfaction. Customers who are satisfied with a product will generally have a loyal attitude towards that product. This research aims to analyze the influence of the marketing mix on customer satisfaction, customer loyalty, and rice customer loyalty at PT. Komoditi Tani Indonesia. The sampling method uses accidental sampling with a total of 68 respondents. The analysis used is SEM-PLS with the WarpPLS 8.0 program. The research results show that product, price, location, and employee variables have a significant effect on customer satisfaction. Product variables, price, location, physical facilities, and customer satisfaction significantly affect customer loyalty. The customer satisfaction variable mediates the relationship between product, price, and location variables on customer loyalty

STATISTICAL TECHNIQUES IN PRECISION METROLOGY, APPLICATIONS AND BEST PRACTICES

Statistical techniques play a pivotal role in precision metrology, ensuring accurate measurements and reliable data analysis in various industries. This review delves into the applications and best practices of statistical techniques in precision metrology, highlighting their significance in enhancing measurement accuracy, reducing uncertainties, and optimizing manufacturing processes. In precision metrology, statistical methods are employed to analyze measurement data, assess measurement uncertainty, and make informed decisions regarding process control and quality assurance. One of the fundamental applications of statistical techniques is in experimental design, where methodologies such as Design of Experiments (DOE) aid in optimizing measurement processes by identifying influential factors and their interactions. Moreover, statistical process control (SPC) techniques like control charts are widely utilized in monitoring and maintaining measurement processes within specified limits, thereby ensuring consistency and reliability in metrology operations. These techniques enable early detection of deviations or anomalies, facilitating timely corrective actions to prevent the production of non-conforming products. Furthermore, the application of statistical analysis in uncertainty evaluation is crucial for quantifying the reliability of measurement results. Techniques such as Monte Carlo simulation and GUM (Guide to the Expression of Uncertainty in Measurement) provide systematic approaches for assessing and expressing measurement uncertainty, considering various sources of error and their contributions to the overall uncertainty budget. In addition to applications, adopting best practices in statistical techniques is essential for ensuring the effectiveness and efficiency of precision metrology processes. This includes proper data collection, adherence to statistical assumptions, selection of appropriate statistical models, and interpretation of results with caution. Overall, this review underscores the importance of statistical techniques in precision metrology, emphasizing their role in improving measurement accuracy, reducing variability, and enhancing overall quality in manufacturing processes. By implementing robust statistical methodologies and adhering to best practices, organizations can achieve higher levels of precision, consistency, and reliability in their metrology operations, ultimately leading to improved product quality and customer satisfaction.
 Keywords: Statistics, Precision Metrology, Best Practices, Application, Review.

Geographical indications as a labelling strategy: an empirical investigation of negative bias and its managing conditions

Purpose This study aims to examine the influence of two significant product labelling strategies (geographical indication [GI] vs country-of-origin [COO]) on shaping customer product attitude and purchase likelihood, considering consumers’ ethnocentric and cosmopolitan tendencies. The authors also investigate the boundary conditions and intervening mechanisms to manage the adverse consumer product evaluations and present mitigating procedures which reinstate favourable product evaluations and purchase likelihood. Design/methodology/approach The collected data from these all these studies were analysed using ANOVA and mediation anlaysis. The study tests the proposed hypotheses using three follow-up experimental investigations. Findings The study found that GI (vs COO) labels have a more significant impact on customers’ product evaluation and likelihood of purchase and supported the dispositional effect of ethnocentric and cosmopolitan inclinations. Further, the results indicated that self-product congruence can efficiently regulate consumer dispositions. Also, the results confirmed the significant impact of product identification on influencing consumer attitudes. Practical implications The above-said insights add practical insights, particularly concerning product labelling. Also, the insights on product attitudes and purchase likelihood intricacies in the context of product labelling enable companies to comprehend better the significance of GI labels, COO labels and self-product congruence. Originality/value To the best of the authors’ knowledge, this is the first time a study has compared the role of two significant product labelling strategies (GI vs COO) in shaping customer product evaluations, confirmed its boundary conditions and shown how to transform them into helpful customer product outcomes.

Nurturing family business resilience through strategic supply chain management

PurposeThe study aspires to enhance comprehension of the intricate interplay between supply chain management (SCM) and resilience in family businesses, thereby offering valuable insights to managers and policymakers endeavouring to foster resilience in uncertain environments.Design/methodology/approachCommencing from the premise that family businesses (FBs) prioritize the preservation of socio-emotional wealth (SEW) when formulating strategic decisions, this study endeavours to advance understanding of supply chain practices adopted by FBs and their direct impact on resilience during crisis situations or economically challenging periods. Through an exploratory case study of nine FBs, the present research reveals four pivotal strategies in SCM that contribute to their resilience: (i) reorganization of inventory management; (ii) cultivating close relationships with suppliers; (iii) emphasizing product quality and customer retention; and (iv) implementing cost reduction measures to bolster resilience. The aim of the study is to provide an in-depth understanding of the intricate interplay between SCM and resilience in FBs, thereby offering valuable insights to managers and policymakers endeavouring to foster resilience in uncertain environments.FindingsOur approach offers a theoretical framework for SCM aligned with prior research on the interplay between characteristics of family businesses and resilience strategies. Furthermore, this paper illustrates how factors such as the emphasis on high-quality products and services by family businesses contribute to achieving non-economic objectives that owners adopt to reconcile family and business needs, creating intrinsic added value for the company. It reveals various challenges in SCM, including inventory organization changes, supplier closures and the significance of customer retention. Family businesses are implementing product and technology enhancements and leveraging digitization to enhance supply chain processes.Originality/valueThis paper contributes significantly to the field of FBs by highlighting the crucial role of SCM in enhancing business resilience during crises. It empirically examines how the SEW characteristics of FBs influence the reconfiguration of their supply chains to enhance resilience, presenting a theoretical model for this context. Our theoretical framework employs an SEW perspective to elucidate how FBs respond to the challenges posed by the COVID-19 pandemic by adapting their SCM processes to safeguard their social and emotional legitimacy, organizational visibility and reputation. These adaptations gain particular relevance during crises or turbulent conditions, potentially leading to alterations in how FBs formulate their supply chain strategies and manage supply chain-related processes.

Electrocatalytic reduction of simulated industrial CO2 and CO mixtures: Revising chronoamperometry to enable selective gas mixture reduction via cyclic voltammetry

While substantial advancements have been achieved in the electrocatalytic reduction of pure CO2 or CO, the reduction of carbon oxide mixtures remains underexplored, a key limitation in scaling the technology for industrial applications. This underexplored domain gains practical importance by considering carbon oxide mixtures, given that CO and CO2 together constitute a large proportion of diverse industrial gas streams. However, the simultaneous reduction of mixed CO and CO2 poses a potential challenge due to their differing optimal reduction potentials, which complicates an efficient reduction process. While cyclic voltammetry (CV) is typically used for characterization, which involves sweeping between positive and negative potentials, we utilized it to conduct reduction reactions within a defined negative potential window. This approach, serving as an alternative to conventional chronoamperometry that maintains a constant potential, ensures a continuous reduction reaction throughout the entire cycling process. By employing cycling between the optimized reduction potentials of CO2 (−1.4 V) and CO (−1.6 V), CV achieved an increase in production efficiency, ranging from 25 % to 40 % for predominant products (HCOOH and C2H4), in comparison to chronoamperometry. Meanwhile, the results underscored the dependency of performance enhancement on the scan rate of cycling, revealing plausible correlations with mass transfer and electrode surface dynamics. Furthermore, the findings indicated that the selectivity towards HCOOH and C2H4 is closely related to the CO2/CO ratios of gas sources. This provides insight into the potential for modulating selectivity of industrial gas reduction for improved product quality and customization.

Analisis Kualitas Produk, Kepuasan Pelanggan dan Promosi terhadap Keputusan Pembelian Ulang Produk (Studi Kasus pada Larissa Skincare Jember)

This study aims to analyze product quality, customer satisfaction, and the promotion concept of repurchasing decisions for Larissa Skin Care products in Jember. The type of data to be used is quantitative data. The primary data source that will be used in this study comes from a list of questions (questionnaires) that will be distributed to respondents. The questionnaire contains data on the characteristics of the respondents in the form of gender, age, profession, status, number of product purchases, number of treatments. The questionnaire also contains questions regarding the variables of product quality, customer satisfaction, promotions and repurchase decisions. The results showed that product quality has a significant effect on repurchasing decisions for Larissa Skin Care products in Jember. Then the customer has a significant effect on the repurchase decision of Larissa Skin Care product satisfaction in Jember. Lastly, promotions have a significant effect on repurchasing decisions for Larissa Skin Care products in Jember. Keywords: Customer Satisfaction, Product Quality, Promotion, Repurchasing Decisions.

SWOT ANALYSIS IN PRODUCTIVE MANAGEMENT OF CASH WAQF FUNDING AT MICRO WAQF BANK OF ALMUNA BERKAH MANDIRI KRAPYAK YOGYAKARTA

The role of institutions in managing cash waqf provided security guarantees and wider investment of funds. Here, the question arises of how to manage cash waqf funding at Bank Wakaf Mikro (BWM) using the SWOT approach. This research aimed to determine the strength factors, weakness factors, opportunity factors, and threat factors in the implementation of cash waqf fund management by BWM Almuna Berkah Mandiri Krapyak. This research was a type of field research using qualitative descriptive methods. Data collection techniques were observation, interviews, and documentation. Meanwhile, the data analysis technique was obtained from various sources through triangulation and carried out continuously until saturation. The results of this research could conclude that the strength factors in managing cash waqf funding at BWM Almuna Berkah Mandiri were good human resources and infrastructure. Meanwhile, the weak factor was that social media management was not running well, so promoting customer products was less than optimal. The opportunity factor was the ease of technology, where customers would find it easy to get information from the Micro Waqf Bank. Finally, the threat factor in managing cash waqf funding was the existence of customers who were in trouble, where customers needed to make installment payments at the agreed time.

Introduction of Collaborative Robotics in the Production of Automotive Parts: A Case Study

Incorporating collaborative applications constitutes a challenging and increasingly intricate objective within the context of small and medium-sized enterprises (SMEs). This challenge stems from the shortage of highly specialized personnel in these types of companies when it comes to adopting cutting-edge technologies. The lack of innovation in production processes, however, increases the risk that SMEs will not be able to adapt to rapid changes in the market and the growing needs of consumers, who today are evolving at an unprecedented pace. The importance of adopting collaborative applications can be found in their capacity to harmonize human adaptability with the precision of robotic technology. This synergy contributes to the establishment of a safer work environment while guaranteeing effective and efficient performance. These features not only lead to improved production line performance compared to traditional manual or stationary operations, but also highlight new perspectives in the design, production, and customization of new products. This, in turn, helps companies strengthen their competitiveness in the global market. In this scenario, the primary challenge centers around effectively putting these solutions into practice. Our research aims to highlight how significant benefits can be achieved, both in terms of performance improvements and economically, through the analysis of a simple yet illuminating case study.

From Nash Q-learning to nash-MADDPG: Advancements in multiagent control for multiproduct flexible manufacturing systems

The emergence of flexible manufacturing systems (FMS) capable of processing multiple product types is a result of the growing demand for product customization and personalization. Such multiproduct systems are characterized by a higher level of uncertainty and variability when compared to traditional manufacturing systems. This paper proposes a Nash integrated multiagent deep deterministic policy gradient method (Nash-MADDPG) to control the mobile robots’ assignment in a multiproduct FMS to enable intelligent decision-making, interaction, and dynamic learning capabilities. A mathematical model of a multiproduct FMS from a previous study is described, and system dynamic property is characterized by permanent production loss (PPL). Then, by observing PPL of the system and market demand for each product type, the multi-agent control scheme is developed to assign mobile robots to load/unload various product types at various machines. First, a Nash game is developed among the mobile robots and to improve the cooperation, a collaboration cost is defined. This collaboration cost is then used in the reward function of the multiagent deep deterministic policy gradient (MADDPG) algorithm. Second, the actions are jointly defined based on the action values of MADDPG, and the mobile robots’ strategies in the Nash game, which update the environment to a new state. The performance of the proposed method is verified by comparing it with conventional Nash Q-learning, vanilla MADDPG, Q-learning based single agent reinforcement learning (SARL) and a first-come-first-serve (FCFS) based control. The results demonstrate that the multi-agent control scheme under the proposed Nash-MADDPG is effective in dealing with cooperative FMS environment that involves complicated dynamics and uncertainties.

The Brand Loyalty Determinants of Indonesian Local Beauty Product Customers: Is it mediated by Customer Satisfaction and moderated by Brand Trust?

The purpose of this study is to investigate the impact of customer satisfaction mediators and brand trust moderators on brand loyalty among customers of a local beauty product in Indonesia. Researchers wanted to know how to boost customer loyalty to a local beauty product user in Indonesia. This study employed primary data collected via an online survey utilizing a Google form, with respondents chosen using purposive sampling. This study's respondents were women, with a total of 116 respondents aged 18-35 years who utilized a local beauty product in Indonesia. The Structural Equation Model (SEM) was used in this work as a research approach. According to the study's findings, utilitarian value and brand image directly and positively affect consumer satisfaction. Furthermore, brand image and customer satisfaction have a strong direct and positive impact on brand loyalty, and customer satisfaction can buffer the relationship between brand image and brand loyalty. While utilitarian value has no effect on brand loyalty, customer satisfaction cannot mitigate the association between utilitarian value and brand loyalty. Finally, the moderating influence of brand trust cannot affect the link between consumer pleasure and brand loyalty.

INTELLIGENT MONITORING SYSTEMS IN MANUFACTURING: CURRENT STATE AND FUTURE PERSPECTIVES

Intelligent Monitoring Systems (IMS) have emerged as indispensable tools in modern manufacturing, offering real-time insights into production processes, equipment performance, and quality control. This review provides an overview of the current state and future prospects of IMS in manufacturing environments. The current state of IMS in manufacturing involves the integration of advanced technologies such as Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and Big Data analytics. These systems collect vast amounts of data from sensors, machines, and production lines, enabling real-time monitoring and analysis of various parameters. By employing AI and ML algorithms, IMS can identify patterns, predict anomalies, and optimize production processes, leading to increased efficiency, reduced downtime, and improved product quality. IMS play a crucial role in predictive maintenance, where they can anticipate equipment failures before they occur, thereby minimizing unplanned downtime and maintenance costs. Moreover, IMS facilitate condition-based monitoring, allowing manufacturers to monitor the health and performance of machinery in real-time and schedule maintenance activities accordingly, optimizing resource allocation and prolonging equipment lifespan. Furthermore, IMS contribute to quality control by continuously monitoring production processes and detecting deviations from desired specifications. By leveraging AI-driven algorithms, IMS can automatically adjust process parameters to maintain product quality standards and minimize defects, thereby enhancing overall product reliability and customer satisfaction. Looking ahead, the future perspectives of IMS in manufacturing are promising, with advancements in areas such as edge computing, robotics, and augmented reality poised to revolutionize manufacturing operations further. Edge computing enables data processing and analysis to occur closer to the data source, reducing latency and enhancing real-time decision-making capabilities. Robotics integration with IMS facilitates autonomous manufacturing processes, while augmented reality technologies provide intuitive interfaces for operators to interact with IMS data in real-time. IMS represent a transformative technology in manufacturing, offering unprecedented levels of visibility, control, and optimization. As technology continues to evolve, IMS are poised to play an increasingly vital role in shaping the future of manufacturing, driving efficiency, productivity, and innovation..
 Keywords: Monitoring, System, Intelligent, Manufacturing, Review, Perspectives.

Indonesian E-commerce: The Influence and Factors on Tokopedia User Satisfaction and Loyalty

In particular, this study looks for a significant link between customer satisfaction and customer satisfaction, service quality, and user loyalty, product quality and customer loyalty, trust and customer satisfaction, trust and user loyalty, customer satisfaction on user loyalty, service quality, product quality, and trust in customer satisfaction on user loyalty. using a hypethetico-deductive research approach in conjunction with quantitative methods. The study's findings indicate that Trust has a significant and positive impact on both customer satisfaction and customer loyalty, that customer satisfaction has a positive and significant impact on customer loyalty, and that service quality has a positive and significant impact on customer satisfaction and that product quality has a positive and significant influence on customer satisfaction and that the results indicate that service quality and customer loyalty are both important positive and insignificant intervening variables. Furthermore, there is a positive and insignificant relationship between product quality and customer loyalty and satisfaction, as well as trust in customer loyalty and satisfaction. In Tokopedia, customer satisfaction has a positive and significant impact on customer loyalty. the research found, and customer satisfaction is an intervening variable that is not significant in the relationship between service quality and product quality with customer loyalty, insignificant in the relationship between service quality and product quality with customer loyalty, and trust has a positive and significant influence on customer satisfaction and customer loyalty in Tokopedia.

Does digitalization enhance the effects of lean production on social performance?

PurposeThis study aims to investigate whether Industry 4.0 digital technologies can enhance the effects of lean production on social performance.Design/methodology/approachSurvey data collected from China’s manufacturing industry are used to test research hypotheses.FindingsThe results reveal that the three dimensions of lean production (internal, customer and supplier) have a significant positive effect on social performance and that digital technology advancement (DTA) positively moderates these relationships. DTA adds only a marginal contribution to social performance.Practical implicationsThis study addresses a new challenging question from manufacturing firms: how to integrate lean, technology and people? The empirical findings provide timely and insightful practical guidance for managers to better understand the role of digital transformation in the traditional lean context.Originality/valueWhile digitalization is known to complement lean production, this study shows digitalization also complements the effects of lean production on social performance.

Smart Furniture Application

The Smart Furniture Application allows users to check for various furniture available at the online store and purchase online. The project consists of list of furniture products displayed in various models and designs. The user may browse these products as per categories. If the user likes a product he may add it to his shopping cart. Once user wishes to checkout he must register on the site first. He can then login using same id password next time. Here, we use flutter framework to make the entire frontend. The middle tier or code behind model is designed in firebase and sql serves as a backend to store furniture lists and inventory data. Thus, the Smart Furniture Application project brings an entire furniture shop online and makes it easy for both buyer and seller to make furniture deals. The application provides a user-friendly interface facilitating product browsing, purchase and secure monetary transactions. A key feature enables customers to personalize available furniture items directly within the web application. Through intuitive customization options, users can tailor products to their preferences before placing orders. The integration of smooth transaction capabilities ensures a convenient shopping experience while maintaining financial security. KEYWORDS – Furniture Purchasing Software, Firebase Management, Security And Privacy, Customization of Products.

INTEGRATING ARTIFICIAL INTELLIGENCE IN PERSONALIZED INSURANCE PRODUCTS: A PATHWAY TO ENHANCED CUSTOMER ENGAGEMENT

The integration of Artificial Intelligence (AI) in the insurance sector has ushered in a new era of personalized insurance products, offering enhanced customer engagement and satisfaction. This review explores the transformative potential of AI in reshaping the landscape of insurance services, focusing specifically on the augmentation of customer engagement through personalized offerings. AI-driven algorithms and machine learning techniques enable insurers to analyze vast amounts of data with unprecedented speed and accuracy, facilitating the customization of insurance products to meet individual customer needs. By leveraging data from various sources such as IoT devices, social media, and historical claims data, insurers can gain deeper insights into customer behavior, preferences, and risk profiles. Personalized insurance products not only cater to the unique requirements of customers but also foster greater engagement by offering tailored recommendations, proactive risk management solutions, and real-time assistance. Through predictive analytics, AI algorithms can anticipate customer needs and preferences, allowing insurers to offer timely and relevant services, thereby enhancing customer satisfaction and loyalty. Moreover, AI-powered chatbots and virtual assistants serve as accessible and responsive touchpoints for customers, providing instant support, guidance, and personalized recommendations throughout the insurance lifecycle. By streamlining communication channels and offering seamless interactions, AI technologies strengthen the bond between insurers and customers, fostering long-term relationships built on trust and transparency. The integration of AI in personalized insurance products represents a transformative pathway towards enhanced customer engagement. By harnessing the power of AI-driven analytics and automation, insurers can deliver tailor-made solutions that resonate with individual customers, driving higher levels of satisfaction, loyalty, and ultimately, business growth.
 Keywords: Artificial Intelligence, Insurance, Privacy-Enhanced, Customer, Engagement, Review.

Investigating the Simultaneous Performance of AI and Blockchain on E-banking Transaction

Although electronic banking networks are new to communities, it can be argued that there are good reasons for their expansion. The banking industry is aware of the power and ability of social networks and enables banks to reach customers more than traditional channels, but currently, banking in social networks is limited to product marketing, customer interaction and support. As the channels and service delivery mechanisms in banks develop, bank managers have the right to worry about the monitoring of transactions in such networks and it becomes their main concern. Although electronic banking networks are new to communities, it can be argued that there are good reasons for their expansion. Banking is aware of the power and capability of social networks and allows banks to reach customers more than traditional channels, but currently banking on social networks is limited to product marketing, customer interaction and support. It is As the channels of banks and service delivery mechanisms evolve, bank managers have the right to control transactions in such networks, and this becomes their main concern.