Improve Customer Satisfaction Research Articles

Automated Inventory Management Systems with IoT Integration to Optimize Stock Levels and Reduce Carrying Costs for SMEs: A Comprehensive Review

Automated inventory management systems integrated with Internet of Things (IoT) technology represent a transformative approach for Small and Medium-sized Enterprises (SMEs) in optimizing their stock levels and reducing carrying costs. A literature review also shows that there is progress in developing automated solutions, such as IoT sensors, real- time data analytics, and cloud-based applications that improve inventory control. A study shows that the adoption of IoT in automation has seen improvement in the accuracy of inventory, a reduction in stockouts, and carrying costs among SMEs. Research suggests operational improvements including reduced downtime from real time tracking, reverse logistics systems with intuitive demand forecasting for ideal stock replenishment and automation of reordering systems while effectively managing working capital. Materials and Methods: Research methodology encompassed a comprehensive analysis of peer-reviewed literature, case studies, and empirical research focusing on automated inventory management systems with IoT integration in SMEs. Criteria for choosing the literature included articles focusing on the outcomes of IoT implementation, technical integration, and performance of inventory systems. Data extraction main concern was on the efficiencies of the SC such as inventory accuracy, carrying costs, stockouts, and ROI. Descriptive methods used involved comparisons between pre-implementation and post- implementation data, use of statistical tools for measurement of performance enhancement and assessment of factors important in the deployment of the system. Results Implementation of IoT-integrated automated inventory management systems demonstrated significant improvements across multiple performance metrics. Studies reported average inventory accuracy improvements of 25-35%, reduction in carrying costs [1] by 20-30%, and decrease in stockout incidents by 35-45%. Real-time monitoring capabilities led to improved demand forecasting accuracy by 40%, while automated reordering systems reduced manual processing time by 60%. Cloud-based platforms enabled better inventory visibility and control, resulting in working capital optimization of 15-25%. SMEs implementing integrated systems reported enhanced supplier collaboration, reduced lead times, and improved customer satisfaction levels. Cost-benefit analyses indicated positive ROI within 12-18 months of system deployment. Discussion Analysis reveals several key factors contributing to successful implementation of automated inventory management systems with IoT integration. Critical success factors include proper system architecture design, effective change management strategies, and comprehensive staff training programs. Integration challenges primarily revolve around initial investment costs, technical expertise requirements, and system interoperability concerns. Studies show that the greater gains are experienced by SMEs with higher ITOR and those engaged in intricate supply chain operations. Literature review also points to differences in implementation strategies across different sectors and in their recovery, with manufacturing and retail sectors having the highest levels of adoption and improvement. Conclusion IoT-integrated automated inventory management solutions should be adopted by SMEs and are affirmed by ample data to help optimize stock status and minimize carrying costs. The tangible benefits that could be noted are accuracy in inventory, less operational costs, visibility of supply chain, and optimal use of working capital. In appointing the factors affecting the implementation success, it requires the assessment of the technical feasibility and organisational readiness as well as the management of change strategies. Research shows that dynamic technology factors will continue to improve the system’s performance and increased availability to SMEs. Due to advancement in IoT technology, artificial intelligence and cloud computing, there are potential factors that may boost the performance and cost of automatically Managed inventory systems in the future.

Smart moves: Flipkart’s name-personalized nudging techniques to combat cart abandonment

Flipkart, a leading e-commerce platform, has made significant global strides by offering a diverse range of products, including electronics, fashion, and groceries. Flipkart has a significant problem with high cart abandonment rates, particularly on mobile devices, despite its success. This problem is severe because it damages marketing efforts, impacts customer retention, and causes a large loss of revenue. Complicated checkout procedures and unforeseen expenses are major contributors. Flipkart uses name-based personalized nudges to address this, giving customers a sense of familiarity and customization that makes them feel appreciated. Purchase completion is encouraged by these nudges, which include recovery emails that use the customer’s name and provide customized incentives. Challenges in putting these nudges into practice include protecting customer privacy and guaranteeing data accuracy. Nonetheless, the possible advantages of lowering abandonment rates and strengthening allegiance make it valuable. Flipkart also improves the shopping experience by strategically nudging customers. Transparent pricing, streamlined checkout procedures, guest checkout, a variety of payment methods, and conspicuous security badges are a few of them. To further promote transaction completion and reduce abandonment rates, several interventions are used, such as mobile optimization, exit-intent popups, and cart recovery emails. Flipkart’s dedication to establishing a smooth shopping experience and tackling the serious problem of cart abandonment is demonstrated by these initiatives. All things considered, even though putting these nudges into practice can be difficult, Flipkart’s creative strategy for addressing cart abandonment through personalization and name-based personalized nudges demonstrates its commitment to improving customer satisfaction and increasing conversion rates.

Leveraging the power of Data Analysis in Automobile and Financial industries

In an era defined by digital transformation, data analysis has become a cornerstone of decision-making and innovation in both the automobile and financial sectors. This paper explores how these two industries leverage data analysis to enhance efficiency, foster innovation, and improve customer satisfaction. For the automobile industry, data-driven insights enable manufacturers to optimize supply chains, predict maintenance needs, enhance safety, and advance connected and autonomous vehicle technologies. In parallel, financial institutions employ data analysis to streamline risk management, personalize customer experiences, detect fraud, and refine investment strategies. Through a comparative framework, this study highlights the similarities and unique challenges these industries face, particularly in terms of data privacy, regulatory compliance, and the technical demands of big data integration. Additionally, the paper discusses case studies that exemplify successful data-driven initiatives and details emerging trends—such as AI-enhanced analytics, real-time decision-making, and the expanding role of machine learning. Key findings reveal that while data analysis is universally transformative, its applications and outcomes differ based on each industry's operational priorities and regulatory landscapes. The paper also underscores that as the volume, variety, and velocity of data continue to rise, the future of data analysis will hinge on overcoming data quality challenges and bridging skill gaps. This abstract offers a foundational overview of the paper, detailing the essential role data analysis plays in driving growth and competitiveness within the automobile and financial sectors.

An online review on customer satisfaction of mid-to-high-end health and wellness hotels in China

The rapid development of information technology has enabled the collection of online review data, which provides a more precise representation of hotel guest satisfaction. It is crucial to investigate the factors that impact hotel guest satisfaction as identified through online review content. This study will examine relevant scholarly literature on online reviews and concentrate on 50 mid-to-high-end health and wellness hotels in China. Python is utilized to crawl the online review database, and a comprehensive analysis is conducted on the semantic keywords and categories present in customer online review statements. Service, traffic, catering, and other variables are identified as determinants of customer satisfaction in mid-to-high-end health and wellness hotels through factor analysis. This article will propose specific measures and recommendations to improve customer satisfaction in health and wellness hotels, attract more customers, and contribute to the sustainable development of the industry.

Harnessing Disruptive Technologies: Strategic Approach to Retail Product Innovation

Innovations in the retail industry, like Amazon's Just Walk Out (JWO) technology, are changing the way people shop by providing a cashierless experience. This article examines how to strategically utilize disruptive technologies for retail product innovation, with JWO as a case study. The examination summarizes JWO technology, its uptake, and the obstacles encountered during implementation. The research also explores the business dynamics of technological advancement, underlining the crucial role of disruptive technologies in improving customer satisfaction, operational effectiveness, and product creativity. The document points out the main drawbacks of JWO technology, such as restricted scalability, expensive implementation and operational costs, and the requirement for frequent technology updates. Suggestions for enhancing JWO technology and its utilization include implementing a licensing or subscription-based business model, incorporating modular design, and enhancing flexibility. The research also covers tactical factors for merchants when adopting innovative technologies, highlighting the significance of prioritizing customer needs, evaluating costs and benefits, considering scalability, building partnerships, and incorporating other technologies. The paper ends by emphasizing the capability of disruptive technologies to change the retail sector and the requirement for companies to find a balance between innovation and practical factors to thrive in a competitive environment. Keywords—Disruptive Technologies, Retail Product Innovation, Just Walk Out (JWO), Customer Satisfaction, Operational Efficiency, Machine Learning, Artificial Intelligence(AI), Technology Strategy, Machine learning (ML), Data.

Enhancing Supply Chain Sustainability and Reliability Through WSM and TOPSIS: A Symmetrical Real-World Case Study

Large corporations have recently demonstrated an increasing propensity to enhance the sustainability and reliability of their supply chains in order to comply with environmental regulations and improve customer satisfaction through on-time demand fulfillment. There are two phases to this study: mathematical modeling and model solution using precise techniques. In the first step, a mixed-integer linear programming model is developed. This model is an improvement of an existing supply chain model. Further, our suggested strategy is verified by using numerical data based on three criteria and four suppliers. The goals of the proposed model are to maximize supply chain reliability, economic profit, and social responsibilities by taking suppliers’ priorities into account. Modeled as a mixed-integer linear programming problem, the constraints on the problem include budget, emission, demand, allocation, facility, and shipping capacity. Power symmetry and information symmetry are incorporated in order to perform symmetric analysis. The weighted sum method (WSM) and the technique for order of preference by similarity to ideal solution (TOPSIS) are the two methods used in the second step of solving the model to identify the best supplier. In order to evaluate how well the proposed methodology was applied, a practical case was considered and implemented.

Exploring Consumer Satisfaction and Service Quality at Bhatbhateni Supermarket

Background: Customer satisfaction and service quality are pivotal to the success of businesses, particularly in the competitive retail landscape of Kathmandu. Bhatbhateni, as one of the leading retail chains in Nepal, plays a crucial role in offering a wide array of products and services. Understanding customer perceptions regarding service quality and satisfaction is essential for enhancing operational strategies and maintaining a competitive edge in this dynamic market. Objectives: This study aims to analyze the demographic profile of Bhatbhateni's customers, evaluate their perceptions of service quality and satisfaction, identify key service needs and expectations, and assess the likelihood of repurchase and recommendations among customers. Methods: A quantitative research approach was employed, utilizing structured questionnaires distributed to a sample of 120 customers of Bhatbhateni, selected through convenience sampling to ensure a diverse representation of gender and age. The questionnaire encompassed demographic inquiries and Likert scale items measuring customer satisfaction, service quality, and overall service experience. Data analysis involved descriptive statistics to summarize findings and identify trends in customer perceptions. Findings: The results indicated that the sample comprised 53.3% male and 46.7% female customers, with 61.7% of respondents aged between 15-25 years. A substantial 70.0% of respondents felt that Bhatbhateni understood their service needs effectively. In terms of satisfaction levels, 43.3% of customers reported being somewhat satisfied, while 12.5% expressed being very satisfied with the products. Moreover, 45.8% of respondents rated Bhatbhateni's quality management as good, and 41.7% positively rated staff responsiveness. Additionally, 48.3% indicated a high likelihood of repurchasing products, and 61.7% stated they would likely recommend Bhatbhateni to others. Conclusion: The study reveals a generally positive perception of service quality among Bhatbhateni's customers, highlighting key areas of strength and potential for improvement. Customer satisfaction is significantly influenced by the understanding of service needs and the quality of management. These findings suggest that Bhatbhateni is well-positioned for sustained growth through enhanced customer engagement and service delivery. Novelty: This research contributes valuable insights into the relationship between service quality and customer satisfaction within the specific context of Bhatbhateni, a prominent retail chain in Nepal. By employing a structured questionnaire and statistical analysis, the study adds to the limited existing literature on customer service perceptions in Nepal's retail sector. The findings can guide Bhatbhateni and similar businesses in developing targeted strategies to improve customer satisfaction and loyalty, ultimately enhancing business service management practices in the region.

The Self-Improving Customer Service System: How AI Learns from Every Interaction

This article explores the transformative impact of self-improving AI systems in customer service, examining the parallels between AI and human learning processes, the mechanics of AI self-improvement, and the advantages of AI's learning at scale. It delves into real-world applications and impacts across various industries, highlighting improvements in personalization, efficiency, accuracy, customer satisfaction, and cost reduction. The article also addresses ethical considerations such as data privacy, transparency, and bias mitigation, while offering a future outlook on advanced AI capabilities in emotional intelligence, predictive service, and seamless human-AI collaboration. Through a comprehensive analysis of current technologies and future possibilities, this study provides insights into how self-improving AI is revolutionizing customer service, promising more efficient, personalized, and satisfying experiences for customers.

Marketing Strategies in the Digital Age: Opportunities and Challenges

Purpose:Transformation and Response to Enterprise Marketing Strategies in the Digital AgeWith the rapid development of information technology, the digital era has come in all its aspects, bringing a new landscape to enterprise marketing strategy. The digital age brings many opportunities. First, there is more accurate market positioning, and enterprises use technologies such as big data, Can in-depth analysis of a variety of consumer data, accurate grasp of their needs and preferences, so as to clearly identify the target market, like millet through the analysis of user data, accurate positioning of young, the pursuit of cost-effective consumer groups, to launch products that meet their needs. Secondly, there is a wider distribution channel. The popularization of the Internet and social media has allowed enterprises to quickly spread their marketing information to all parts of the world, and Bytedance's products have utilized the advantages of their own platforms to achieve widespread information distribution. Moreover, more efficient customer interaction, enterprises can communicate with customers in real time through the online platform, timely access to feedback, improve customer satisfaction, such as Huawei through the online community interaction with users to improve products and services. However, the challenges cannot be ignored. Data security and privacy protection have become critical issues, and once a data breach occurs, it can seriously damage the reputation of a company, as some high-profile companies have been questioned over data security. The difficulty of accurate marketing is that the market changes rapidly, consumer demand is diverse and volatile, and it is difficult for enterprises to accurately grasp it at all times. The complexity of multichannel integration also causes problems for enterprises, and the characteristics and user groups of different channels are different, making integration difficult. Domestic and foreign enterprises have many successful experiences to learn from. For example, Apple pays attention to the user experience and has built a unique brand image and marketing model through the convergence of online and offline channels. In response to the challenge, enterprises should strengthen data security management and establish strict protection mechanisms. Continuous improvement of data analysis capabilities to better adapt to market changes; At the same time, we should focus on coordination between channels to achieve complementarity of strengths. In short, enterprises need to take full advantage of opportunities in the digital age, actively cope with challenges, and formulate effective marketing strategies in order to gain a foothold and develop in the fierce market competition.

Supply Chain Management and Marketing Integration for Competitive Advantage

Purpose: To explore the effect of the integration of supply chain management and marketing on the competitive advantage of enterprises. Approach/Methodology/Design: The relationship between supply chain management and marketing, the importance of integration and strategy were expounded through theoretical analysis, and the actual cases of Apple and Amazon were analyzed. Findings: It is found that supply chain management and marketing are closely related and interact with each other, and integration can improve customer satisfaction, reduce costs, improve enterprise efficiency and enhance innovation ability. Cases such as Brazil Company show the positive effects of integration, but there are also cases where relevant advantages are not fully utilized. Practical Implications: TIt helps enterprises, government, academia and other parties to understand the importance and application of the integration of supply chain management and marketing in enhancing competitiveness and achieving sustainable development.. Originality/value: Put forward relevant theories and strategies for the integration of supply chain management and marketing, provide new ideas and methods for enterprise operation, and verify its effectiveness and practical significance through actual case analysis.

Influence of Informational Internet Banking on Performance of Copedu PLC Microfinance

Purpose: This study investigates the influence of informational internet banking on the performance of COPEDU PLC Microfinance in Rwanda. It explores how access to online banking information affects customer satisfaction, retention, and overall financial performance. By focusing on non-transactional digital services, the study evaluates the extent to which informational internet banking impacts transparency, customer engagement, and financial literacy among clients. Methodology: The researcher employed a descriptive case study research design that integrated both qualitative and quantitative approaches. The study population comprised 74 individuals, and therefore, a census sampling technique was employed to select all 74 respondents. The researcher employed the SPSS software application to analyze the data. Mean, standard deviation, and percentages are utilized for data analysis. Pearson correlations were employed to establish the relationships among the variables. Findings: The regression analysis results demonstrated a significant correlation between the predictors (Informational internet banking, Transactional internet banking, and Communicative internet banking) and the dependent variable, Financial Performance, with a R value of 0.720, indicating a high degree of correlation. The R Square value of 0.519 signifies that around 51.9% of the variance in financial performance is elucidated by these predictors. The adjusted R Square of 0.497 provides a more precise estimate by considering the number of predictors in the model. A substantial majority of respondents (57.1%) agree that internet banking provides easy access to account information, reflected in a high mean score of 4.57. Additionally, 68.6% believe that the availability of internet banking services has improved customer satisfaction, with a mean of 4.64. The data suggests that informational internet banking has effectively reduced the need for in-person visits (61.4% agreement, mean 4.50) and has enhanced transparency in financial transactions (55.7% agreement, mean 4.56). Furthermore, respondents acknowledge that internet banking has positively impacted COPEDU's operational efficiency (57.1% agreement, mean 4.53) and improved the speed and convenience of accessing financial information (57.1% agreement, mean 4.49). Lastly, the provision of timely financial updates through internet banking was seen to contribute to better decision-making, with 50% of respondents agreeing (mean 4.44). Overall, the findings underscore the critical role of informational internet banking in enhancing customer satisfaction, operational efficiency, and informed decision-making at COPEDU PLC. In conclusion, the study demonstrates that informational internet banking significantly enhances customer satisfaction and operational efficiency at COPEDU PLC Microfinance, indicating its essential role in modern financial services. Unique Contribution to Theory, Practice and Policy: The research was underpinned by agency theory, contingency theory, behavioral theory, and information theory. It is recommended that COPEDU continues to invest in and promote its digital banking services, ensuring that clients are aware of the benefits and features available to them. For future research, it would be valuable to explore the long-term effects of digital banking on client retention and financial performance, as well as to examine the challenges and barriers faced by customers in utilizing these services effectively.

Transformative Impact of AI and Cloud Technologies: A Comparative Analysis across Healthcare, Retail, and Mobile Financial Services

This article examines the transformative impact of artificial intelligence (AI) and cloud technologies across healthcare, retail, and mobile financial services sectors. Through a comprehensive analysis of industry-specific applications, we explore how these technologies are revolutionizing operational efficiency, customer experiences, and innovation in each domain. In healthcare, we investigate the role of CI/CD automation and scalable cloud infrastructure in improving system reliability and patient care. The retail sector analysis focuses on AI-driven customer insights and supply chain optimization. For mobile financial services, we examine AI applications in fraud detection and real-time analytics. The findings reveal significant improvements in operational efficiency, decision-making processes, and customer satisfaction across all three industries. However, we also identify unique challenges and opportunities specific to each sector. This article contributes to the growing body of literature on digital transformation and provides valuable insights for industry professionals and policymakers navigating the integration of AI and cloud technologies in their respective fields.

AI-Driven Service Transformation : Revolutionizing Operational Excellence

Service industries are undergoing rapid transformation through the integration of artificial intelligence (AI) and automation. This article presents an AI-powered service delivery model that autonomously optimizes operations, improves customer satisfaction, and drives business growth. The article leverages AI algorithms to automate incident management, predict operational disruptions, and enhance customer experiences. Real-world implementations within retail, healthcare, and technology sectors demonstrate significant improvements in service efficiency, with operational costs reduced by 30% and customer satisfaction scores increasing by 30%. This article proposes AI-driven service enhancements as a game-changer in the delivery of complex, scalable, and reliable services.

Comparative Analysis of the Signal Strength of Two Radio Stations in Okene, Kogi State, Nigeria

There are significant concerns for the citizens of Okene and its surroundings; regarding the distortions experienced in radio signals due to increased attenuation, which have resulted in poor signal quality. This study carried out a comparative analysis of the signal strength of two radio broadcast stations in Okene, Kogi State, Nigeria, using a field strength meter. The study involved measuring the signal strength for each radio stations at six selected locations in Okene and surrounding area. The wavelength and free space path-loss was calculated at sixteen different locations. The results indicated an inverse relationship between the measured signal strengths and the path-loss, as well as the approximate distance amid antennas. The transmitting signal strength was 100.9dBµV (KA) and 102.2dBµV (KB). Distance from station where signal can be receive was 72.0km (KA) and 69.0km (KB). The free space path loss experienced was 109.01dB (KA) and 109.39dB (KB). Even though KA has a lower transmitting signal strength, its longer wavelength 3.21m and lower frequency 93.5MHz gives it an age over KB with higher frequency 109.5MHz and shorter wavelength 2.94m. However, it is recommended that the FM stations should strategically enhance their network infrastructure to improve service delivery, particularly where performance lags. Booster stations at approximately 69km away from the main stations can effectively enhance the signal, leading to better signal quality and improved customer satisfaction.

Impact of AI-Driven CRM on Customer Relationship Management and Business Growth in the Manufacturing Sector

The impact of AI technologies has changed major aspects of human lifestyle along with the operations of the business world at contemporary world. The dynamic shift has developed new processes and techniques within the manufacturing sector that is closely connected with the business improvement and customer relationship management. Based on this change, the research adopted a secondary qualitative design along with a case study approach to analyse the impact of AI-drive CRM on business growth and customer relationship management within the manufacturing industry. The findings suggested overall improvement of the business and vital enhancement of customer relationships within the industry as AI-driven CRM systems have improved customer satisfaction through seamless demand fulfilment.

Implementasi Vogel’s Approximation Method (VAM) dan Modified Distribution (Modi) untuk Minimasi Biaya Distribusi di PT Jimat Perkasa Farm

Efficient and effective distribution management is a key factor in the success of a company's operations. PT Jimat Perkasa Farm, which is engaged in the processing of seaweed waste for animal feed blends, faces significant challenges in minimizing distribution costs. This research aims to implement Vogel's Approximation Method (VAM) and Modified Distribution (MODI) to achieve an optimal solution in reducing distribution costs. The results show that the application of VAM as the initial solution and MODI as the optimal solution is able to produce significant distribution cost savings. The total distribution cost can be minimized from IDR 5,400,000 per month to IDR 5,275,000 per month, which shows a savings of IDR 125,000 / by 2.31% per month. This efficiency in distribution not only reduces operational costs but also improves the timeliness and reliability of delivery, which ultimately improves customer satisfaction and the company's competitiveness in the market

Optimizing Attended Home Delivery: Multiple recovery options and customer availability profiles to face synchronization failures

In the growing sector of Attended Home Delivery, unsynchronized deliveries between couriers and recipients affect both customers’ satisfaction and companies’ costs. Hence, reducing such failures improves companies’ service quality and logistics efficiency. To address this issue, we study an Attended Home Delivery Problem with Recovery Options (AHDPRO) in which customers specify their probability of being at home during different timeslots of the day and their preferred recovery option in case of a synchronization failure. The options include leaving the package in a predefined safe location, bringing it to a generic collection point, or scheduling a second delivery attempt. Each alternative involves different costs and, in most cases, additional operational decisions. The AHDPRO aims to complete all customer deliveries while minimizing overall routing times as well as the overall penalty due to the recovery actions implemented and weighted by the probability of a synchronization failure to occur. We propose a branch-and-cut algorithm, including valid inequalities and heuristic procedures, to solve a Mixed-Integer Linear Programming model based on an expanded graph. Using the developed method as a tool for evaluating costs and operations, we conduct an experimental campaign on scenarios adapted from the literature involving lexicographic-based optimization procedures able to address the multiple attributes of the solutions. The results obtained allow us to assess the impact of the different recovery options on the optimal solutions and their values. Additionally, the results yield several managerial insights for companies operating in the Attended Home Delivery sector, such as the timeslot length, perceived service quality, and other key operational factors contributing to efficient planning and improved customer satisfaction.

RPA Demystified: How Software Robots are Revolutionizing Customer Service

Robotic Process Automation (RPA) is revolutionizing customer service by introducing software robots capable of handling repetitive tasks with unprecedented efficiency and accuracy. This article explores the transformative impact of RPA on customer service operations, drawing parallels with everyday automation experiences to demystify the technology. Through case studies and empirical evidence, we examine how RPA streamlines processes such as data entry, ticket routing, and customer data retrieval, leading to significant improvements in operational efficiency and customer satisfaction. The article addresses common misconceptions about RPA, emphasizing its role as a complement to human workers rather than a replacement. We analyze the synergy between RPA and human customer service representatives, highlighting increased employee productivity and job satisfaction. The article also delves into the future prospects of RPA in customer service, including emerging trends like cognitive RPA, while discussing potential obstacles to widespread adoption and strategies for successful implementation. By presenting a comprehensive overview of RPA's capabilities, benefits, and challenges in the customer service domain, this article provides valuable insights for organizations seeking to enhance their customer service operations through automation.

A Structured Model for continuous improvement methodology deployment and sustainment: A Case Study

This research focuses on designing a clear methodology for problem-solving. It investigates the application of a defined ‘Lean’ methodology for the proactive application of process improvement activities using a phased digitized measurement and monitoring system. This case study in a Medtech organisation utilised the Plan, Do, Check, Act (PDCA) model to develop a Lean system and structure to support managing the process improvement or project management element of a Continuous Improvement (CI) framework. The results from the pilot of this study delivered financial gains and demonstrated how a robust structure and methodology to measure improvement activity and success provided a strong, sustainable foundation for customer satisfaction, efficiency, cost reduction and employee engagement improvement. It also highlighted the importance of focusing on proactive process improvement as part of a CI framework. The study provides valuable insights into the effective implementation of Lean principles and process improvement via a sustainable model, thereby contributing to the body of knowledge in this field.. This study demonstrated how the developed model supported process improvement activity underpinning the development of a wider continuous improvement culture to support Lean deployment and sustainment and that systems can drive behaviour. Additionally, this application in the healthcare manufacturing sector adds to the sparse application in the literature from this sector.

INFLUENCE OF AUTOMATED TELLER MACHINEAND MOBILE BANKINGON SMALL BUSINESS OPERATION IN MUBI METROPOLIS, ADAMAWA STATE, NIGERIA

The study examined the influence of E-banking components on small business operation in Mubi metropolis, Adamawa State, Nigeria. The study is a survey in the form of cross sectional study in which data were collected through questionnaire administered to 400 small business owners in Adamawa State. Data collected was subjected to percentage analysis and hypotheses were tested using regression analysis at 0.05 level of significance. The result influence of automated teller machine on business operation is statistically significant and positive (β = 0.942, t = 8.789, p < 0.05). Also, coefficients of the influence of mobile banking on small business operation is significant (β = 0.558, t = 9.800, p < 0.05). Hence the study concludes that automated teller machine (ATM) and mobile banking has significant and positive influence on small business operation in Mubi metropolis, Adamawa State, Nigeria. The study therefore, recommends that by considering the statistically significant and positive influence of e-banking components like automated teller machine (ATM) and mobile banking on business operations, small businesses should focus on establishing convenient and accessible banking components services. This can improve customer satisfaction by providing easy access to cash, ultimately leading to increased sales and transactions.