Customer Cost Research Articles

An Expert-Based Analysis of ESG Reporting in the context of the Circular Economy

Existing literature has highlighted how Environmental Social Governance (ESG) reporting enables companies to drive their Circular Economy (CE) practices. However, current approaches to ESG reporting do not specifically consider how company activities and decisions about CE contribute to sustainable development. Indeed, CE has a great potential to ensure that companies actively participate in the achievement of the United Nations 2030 Agenda Goals although a more effective way to link CE and sustainability reporting processes is necessary. The present paper recognizes the importance of developing a standardized approach that aligns ESG metrics with CE practices to enhance both transparency and accountability. To this end, taking into consideration the relevance of the GRI guidelines to make the ESG performance of companies more transparent, an expert-based analysis of the importance of GRI topics to capture the ability of CE practices to create circular value is proposed. Creating circular value through CE improves the company’s profitability and resilience while reducing costs for customers, and benefits society and the environment. The use of the fuzzy AHP (F-AHP) method ensures that the relevance of the economic, environmental, and social performance is estimated to make ESG reporting more informative about the company's commitment to a restorative and regenerative business. The findings offer guidelines for using CE reporting information to compare the companies’ contributions to SDGs Keywords: ESG reporting, GRI standards, Circular Economy (CE), Fuzzy Analytic Hierarchy Process (F-AHP), Sustainable Development Goals (SDGs), circular value.

Folding and Functionalizing DNA Origami: A Versatile Approach Using a Reactive Polyamine.

DNA nanotechnology is a powerful synthetic approach to crafting diverse nanostructures through self-assembly. Chemical decoration of such nanostructures is often required to tailor their properties for specific applications. In this Letter, we introduce a pioneering method to direct the assembly and enable the functionalization of DNA nanostructures using an azide-bearing functional polyamine. We first demonstrate the successful polyamine-assisted folding of a scaffolded DNA origami nanostructure equipped with reactive azide groups. Leveraging this reactivity, we next showcase the decoration of the DNA origami via strain-promoted azide-alkyne cycloaddition with dibenzocyclooctyne-containing functional molecules. Specifically, we incorporate a fluorophore (Cy5), polyethylene glycol (PEG), and a hydrophobic phosphatidylethanolamine (PE) tag to tailor the properties of our DNA origami nanostructures. Our approach is expected to streamline and reduce the cost of chemical customization of intricate DNA nanostructures, paving the way for enhanced versatility and applicability.

Deep learning hybrid models for effective supply chain risk management: mitigating uncertainty while enhancing demand prediction

In today's rapidly evolving business landscape, effective supply chain management (SCM) is crucial for achieving success. Accurately predicting product demand is a significant challenge for companies, impacting customer satisfaction, inventory optimization, cost reduction, and operational efficiency. This study focuses on demand forecasting within intelligent supply chains (SCs) and supply chain risk management (SCRM), aiming to enhance overall SC efficiency and mitigate risks, highlighting the use of deep learning hybrid and singles models to address SCRM challenges, specifically in mitigating uncertainty and improving demand prediction accuracy. Our research paper investigates predictive modeling techniques for demand forecasting within the automotive sector. Specifically, we assess the effectiveness of Seasonal Autoregressive Integrated Moving Average (SARIMA), Long Short-Term Memory (LSTM), Artificial Neural Network (ANN), Recurrent Neural Network (RNN), and a hybrid RNN-ANN model with Gradient Boosting (GB). Through meticulous analysis and evaluation, we demonstrate the superior predictive accuracy of the hybrid model compared to individual models. The results indicate consistent outperformance of the hybrid model, as evidenced by lower Mean Absolute Error (MAE) and Mean Squared Error (MSE) values across electric and thermal product categories. This research aims to provide valuable insights and practical tools for businesses to refine their demand prediction processes. By addressing demand uncertainty, organizations can streamline their SCs, minimize costs, and establish a responsive and adaptable framework for sustainable growth.

Strategi Pengembangan Usaha Pada Toko Ikan Tenggiri Eman Carman Dengan Pendekatan Business Model Canvas dan Analisis SWOT

This study explores the business development strategy for Toko Ikan Tenggiri Eman Carman using the Business Model Canvas (BMC) framework and SWOT analysis. Traditional operations in the mackerel fish market face challenges such as fluctuating sales and dependency on fixed customer bases and suppliers. These issues result in financial instability and limited market reach. Applying the BMC framework analyzes nine essential components, including customer segments, key partnerships, value propositions, and cost structures. The SWOT analysis identifies internal strengths, weaknesses, and external opportunities and threats, providing a strategic roadmap for business development. This study highlights the need for digital transformation, such as utilizing social media and e-commerce platforms, to diversify sales channels and reduce reliance on traditional markets. Additionally, strategic partnerships with suppliers can stabilize costs and ensure product availability. Implementing these strategies aims to enhance business resilience, expand market access, and secure long-term sustainability. The practical implications of this research provide insights for small-scale business owners, particularly those relying on traditional markets, on how to adapt technology and digital marketing strategies to strengthen their position in an increasingly competitive market. By adopting these strategic steps, Toko Ikan Tenggiri Eman Carman can increase its competitiveness and achieve sustainable growth

Integration and Optimization of Route Planning and Inventory Management in Supply Chain Transaction Systems: A Comprehensive Analysis

This comprehensive article analysis explores the integration and optimization of route planning and inventory management within supply chain transaction systems, examining their transformative impact across various industries. The article investigates the evolution of modern logistics operations, emphasizing the crucial role of advanced technologies, blockchain frameworks, and integrated systems in enhancing operational efficiency. Through a detailed examination of core components including algorithmic foundations, real-time tracking systems, demand forecasting mechanisms, and unified data architectures, this article presents a holistic view of contemporary supply chain optimization. The article analysis encompasses multiple sectors, including retail, e-commerce, and manufacturing, demonstrating how integrated systems have revolutionized traditional approaches to inventory management and route optimization. By exploring performance metrics, return on investment, and future trends, this article provides valuable insights into the implementation strategies and scalability considerations essential for modern supply chain systems. The article highlights the significance of cross-functional optimization and cloud-based solutions in achieving operational excellence while maintaining high levels of customer satisfaction and cost efficiency.

THE EFFECT OF INFLATION ON SBI BANK

The relationship between inflation and the performance of major Indian banks, particularly the State Bank of India (SBI), reveals significant insights into macroeconomic stability and banking sector resilience. High inflation affects SBI's cost structures, loan demand, and non-performing asset (NPA) rates, with adverse impacts on profitability and asset quality. Elevated inflation rates often drive the Reserve Bank of India (RBI) to raise interest rates, indirectly impacting SBI’sloan growth and deposit mobilization.Higher interest rates increase loan costs for customers, suppressing credit demand and increasing default risks. SBI also faces higher operational costs and reduced profit margins under inflationary pressures. However, the bank’s large deposit base and robust capital position offer some resilience against inflationary shocks. Additionally, SBI's adoption of advanced risk management strategies and digitalization helps mitigate inflationary impacts, though prolonged inflationary phases can still strain its financial stability. Addressing these inflation-induced challenges requires active regulatory oversight, efficient risk management, and adaptive fiscal policies to ensure SBI’s sustained growth and stability. Keywords: Inflation, State Bank of India, non-performing assets, Reserve Bank of India, banking sector resilience,macroeconomic stability

Robust design methodologies to engineer multimaterial and multiscale bioprinters

Commonly used bioprinting technologies (e.g., material extrusion, material jetting) enable the fabrication of complex, multimaterial and multiscale scaffolds with controlled properties for tissue engineering applications. This enables the fabrication of scaffolds that more accurately replicate the structure of natural tissues. Despite the availability of commercial bioprinters, their high cost and lack of customization have driven researchers to modify existing devices or create entirely new platforms. Among all the available examples in literature, there is a strong need for more modular systems which are robustly designed taking into consideration the specific needs of bioprinting. In this context, the aim of this work is to introduce robust engineering methodologies to design and fabricate custom hardware and software for multimaterial and multiscale bioprinting. Firstly, we will identify the main design requirements that should be considered for a bioprinter (e.g., encumbrance, positioning resolution). Based on these requirements, we will then propose an analysis of the key building blocks of a bioprinter, including hardware (i.e., positioning system, toolheads, additional modules for extended functionalities), electronics (i.e., power supply, control boards), and software, introducing for each one the main concepts and equations for its optimal design. Throughout the work, we will use a customized bioprinting platform (namely, the BOOST bioprinter) as an example of the application of the proposed methodologies. Finally, we will present a validation of the methodologies and the bioprinter by fabricating high quality scaffolds through the combination of material extrusion and material jetting. The firmware developed during this work is available online as a support for developing more robust customized bioprinters.

Synergizing QCC and PDCA Approaches to Foster Kaizen Practices in Wingbox Production at Karoseri

This research applies the Quality Control Circle (QCC) method and the PDCA (Plan-Do-Check-Action) approach to overcome problems in hydraulic cylinder bracket mounts in a manufacturing company. At the "Plan" stage, a defect classification analysis, matrix diagram for problem classification, analysis of existing conditions, setting quality, cost, and morale targets, as well as Why-Why and 5W+1H analysis were conducted. At the "Do" stage, the cylinder bracket mounts was redesigned using UNP 5.4 material as a solution to the existing problems. At the "Check" stage, measurements of the improvement results were made to ensure the achievement of the planned targets, including the reduction of damage frequency and repair costs. The results of overcoming the problem of broken hydraulic cylinder bracket mounts showed a decrease in complaints during the 2-month period after implementation. The application of the QCC method and PDCA approach not only effectively addressed the problem, but also increased customer confidence, company sustainability, and worker morale. The next step is “Action” stage to ensure process continuity by standardizing through the creation of operation standards for the manufacture and installation of hydraulic cylinder bracket mounts. As a result, the material change from SPHC 6.0 to UNP 5.4 successfully resolved the damage problem and eliminated complaints within two months after implementation. After implementation, the company can reduce the cost expense of repair by IDR 1,413,510. This success had a positive impact on customer confidence, cost efficiency, and worker morale.

FedCust: Offloading hyperparameter customization for federated learning

Federated Learning (FL) is a new machine learning paradigm that enables training models collaboratively across clients without sharing private data. In FL, data is non-uniformly distributed among clients (i.e., data heterogeneity) and cannot be redistributed nor monitored like in conventional machine learning due to privacy constraints. Such data heterogeneity and privacy requirements bring new challenges for learning hyperparameter optimization as the training dynamics change across clients even within the same training round and they are difficult to be measured due to privacy. The state-of-the-art in hyperparameter customization can greatly improve FL model accuracy but also incur significant computing overheads and power consumption on client devices, and slowdown the training process. To address the prohibitively expensive cost challenge, we explore the possibility of offloading hyperparameter customization to servers. We propose FedCust, a framework that offloads expensive hyperparameter customization cost from the client devices to the central server without violating privacy constraints. Our key discovery is that it is not necessary to do hyperparameter customization for every client, and clients with similar data heterogeneity can use the same hyperparameters to achieve good training performance. We propose heterogeneity measurement metrics for clustering clients into groups such that clients within the same group share hyperparameters. FedCust uses the proxy data from initial model design to emulate different heterogeneity groups and perform hyperparameter customization on the server side without accessing client data nor information. To make the hyperparameter customization scalable, FedCust further employs a Bayesian-strengthened tuner to significantly accelerates the hyperparameter customization speed. Extensive evaluation demonstrates that FedCust achieves up to 7/2/4/4/6% better accuracy than the widely adopted one-size-fits-all approach on popular FL benchmarks FEMNIST, Shakespeare, Cifar100, Cifar10, and Fashion-MNIST respectively, while being scalable and reducing computation, memory, and energy consumption on the client devices, without compromising privacy constraints.

Omnichannel Strategy in Cloud-Based Contact Centers: A Blueprint for Success

This comprehensive technical article examines the evolution and implementation of omnichannel contact center solutions, focusing on the transition from traditional siloed systems to integrated cloud platforms. The article investigates the architectural framework, implementation challenges, and strategic advantages of modern contact center solutions, with particular emphasis on platforms like Genesys Cloud. Through detailed case studies and performance metrics, the research demonstrates how organizations across various sectors have achieved significant improvements in customer satisfaction, operational efficiency, and cost reduction through systematic implementation of omnichannel strategies. The article provides insights into emerging technologies, scalability considerations, and best practices for successful contact center transformation, while highlighting the critical role of AI-driven solutions and microservices architecture in enhancing customer experience and operational excellence.

Optimal Control of Service Systems with Heterogeneous Servers and Priority Customers

We study service systems with parallel servers and random customer arrivals and focus on the waiting cost of customers. Using a Markov decision process (MDP) modeling approach, we analytically characterize the structures of the optimal dynamic server assignment policies for two important systems, one consisting of multiple homogeneous servers and two classes of customers and the other consisting of two heterogeneous servers and multiple classes of customers. Based on the obtained results, we propose a threshold-type heuristic policy for the generalized system consisting of multiple heterogeneous servers and multiple classes of customers. To design such a heuristic policy, we first develop techniques for the performance evaluation of general threshold-type policies with any given threshold values. We then construct a path to search for the optimal threshold values. We compare the performance of the best threshold-type heuristic policy with that of the optimal policy and show that our proposed heuristic policy is computationally efficient yet generates great performance. To derive additional managerial insights, we compare the system under our threshold-type dynamic server assignment policy with other commonly seen and simple systems, such as the dedicated system and the work-conserving flexible priority system. The clear performance advantage observed from extensive numerical experiments demonstrates the importance and usefulness of dynamic server assignment control for systems serving multiple classes of customer arrivals. Finally, we extend our analysis to incorporate customer-dependent service rates and sojourn-time minimization performance metrics. This paper was accepted by Chung Piaw Teo, optimization. Funding: This work was supported by the Hong Kong Research Grants Council [16500921, 16505819] and the National Natural Science Foundation of China [72201233, 72301222]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01228 .

A Review on Nano/Microfluidic Devices for Cell Isolation Techniques: Recent Progress and Advances

Abstract: Micro/nanofluidic devices and systems have gained increasing interest in healthcare applications over the last few decades because of their low cost and ease of customization, with only a small volume of sample fluid required. Many biological queries are now being addressed using various types of single-molecule research. With this rapid rise, the disadvantages of these methods are also becoming obvious. Micro/nanofluidics-based biochemical analysis outperforms traditional approaches in terms of sample volume, turnaround time, ease of operation, and processing efficiency. A complex and multifunctional micro/nanofluidic platform may be used for single-cell manipulation, treatment, detection, and sequencing. We present an overview of the current advances in micro/nanofluidic technology for single-cell research, focusing on cell capture, treatment, and biochemical analyses. The promise of single-cell analysis using micro/nanofluidics is also highlighted.

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 utilized 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.

Packaging optimization model using cost-based behavioral perspective approach in food and beverage industry

The high competition in the food and beverage industry in Indonesia, where packaging has a very important function, with the main function to protect the product, as well as being a factor in attracting consumers' interest in making purchases. Packaging production is dominated by several companies, which when categorized are divided into middle-up manufacturing and middle-low manufacturing. The research is necessary to create an optimal packaging design model by considering the culture and habits of consumer. Capturing customer behavior and costs has a control function. Ethnographic studies are used to explore packaging elements that are important to consumer and Structural Equation Modeling (SEM) was used for data processing. The result provides a conceptual model as well as recommendations for food and beverage manufacturers in terms of the packaging used. Seven elements of packaging that deserve primary attention: design, image, typography, color, size, material and quality. Using habit and cost factors has the control variables, with maximum profit as the objective function. Recommendations for middle-up manufacturing are focused on four packaging elements: design, image, color and quality. It is recommended to maximize strategies for customer retention and improving customer loyalty. Middle-low manufacturing is focused on four packaging elements: color, size, material and quality. It is recommended to maximize strategies to encourage repeat business and boost productivity. The features identified in this research are very possible to be implemented by food and beverage manufacturer, along with recommended strategies. For example, at the middle and low manufacturing level, it is very important to pay attention to product availability in several sizes

Effects of virtual try-on technology as an innovative e-commerce tool on consumers' online purchase intentions

PurposeThe purpose of this study is to investigate the role of using augmented reality (AR) in the form of virtual try-on technology in consumers' purchase decision-making process.Design/methodology/approachThe study, executed in a beauty industry context, uses the value-based adoption model (VAM). Data were collected by means of a survey carried out on 238 Tunisian women. Subjects performed an experimental task using the virtual try-on (VTO) application in the L’Oréal website. Web-administered questionnaires were used to collect the data, which was processed using an exploratory factor analysis and partial least squares structural equation modeling.FindingsThe findings shows that perceived value is positively related to purchase intentions and it was affected by both perceived benefits and perceived costs. In particular, perceived benefit (perceived usefulness) was found to have a strong positive effect on perceived value. Moreover, it turns out that perceived enjoyment does not have a significant effect on the perceived value. In terms of perceived costs, perceived intrusiveness was found to limit perceived value. The results also show a significant relationship between AR characteristics and perceived benefits. For personal traits, personal innovativeness is found positively influencing perceived usefulness, but it shows no significant effect on perceived enjoyment.Practical implicationsCompanies should highlight the benefits for consumers (interactivity, informativeness and usefulness) and attempt to reduce the costs (intrusiveness) related to the use of VTO AR technology, which can play a substantial role in determining the perceived value and purchase intentions.Originality/valueThe existent literature, which examines the AR in e-tailing, shows weak acknowledgment of theories related to consumer barriers to AR adoption in e-tailing, they overlook the role of consumer psychology and individual differences in AR acceptance. Thus, this study contributes to the literature by enhancing the understanding of the roles that AR based VTO technology plays in determining consumers’ online purchase intentions by extending the application of perceived value theory and taking into account its characteristics and personal traits that play a role in weakening or strengthening the customer's benefits and cost perceptions.

Cost - benefit analysis of DISCOs by Optimal allocation of DGs and DSTATCOM using GTO algorithm

Electric power Distribution Companies (DISCOs) provide low-cost, reliable, and consistent voltage power from distribution substations. DISCOs have radial transmission lines with all buses as load buses and no generating buses. The voltage at each bus decreases, resulting in larger network losses and voltage variations, which lowers DISCO and customer costs and benefits. This study strategically uses Distributed Generation (DGs) and DSTATCOM to optimize cost-benefit analysis and voltage stability for Distribution Companies (DISCOs). We planned DG unit and DSTATCOM deployment using a new and comprehensive Group Teaching Optimization (GTO) method in this study. The algorithm considers Distribution Company and DG Owner profitability simultaneously. Group Teaching Optimization (GTO) is used on a 33-node test system. MATLAB simulations show the GTO's usefulness in Distribution System Operators.

Developing and validating an instrument for assessing E-entrepreneurial idea feasibility

Despite the critical importance of e-entrepreneurship idea generation for e-venture success, there remains a significant lack of valid and reliable instruments to evaluate the feasibility of e-entrepreneurial ideas proposed by undergraduates during entrepreneurship learning. This study addresses this gap by creating and validating a scale based on the Business Model Canvas with a sample of 299 participants. Following established scale development procedures, a 13-item scale with four factors emerged: value creation and customer relationship management, cost structure, business viability, and customer segmentation and personalization. The scale demonstrates satisfactory internal consistency and criterion-related validity, providing a reliable tool for assessing e-entrepreneurial idea feasibility in higher education, benefiting both educators and researchers.

The Influence Of Product Quality, Price, And Custumer Value On Custumer Satisfation Mediated By Product Competitiveness At The Golden Kids Shop Bandar Lampung

This research was conducted at Toko Golden Kids Bandar Lampung, a children's fashion store founded in 2022 at Simpur Center Mall. This shop offers various types of children's clothing with a wide variety of products. Even though it faces tough competition, Toko Golden Kids Bandar Lampung must continue to innovate to maintain a large customer base. Product competitiveness's function as a mediator in the relationship among product fine, customer value, and fee and purchaser pleasure is the situation of this take a look at. It also ambitions to ascertain the impact of product first-class, customer cost, and rate on product competitiveness and client satisfaction. crucial information became gotten through notion, meets and conveying surveys to 109 respondents selected making use of purposive testing strategies. The data analysis method uses a quantitative approach with SmartPLS. The research results show that product quality, customer value, and price each have a positive and significant influence on product competitiveness and customer satisfaction. Apart from that, product competitiveness is proven to mediate the relationship between product quality, customer value, and price on customer satisfaction. All research hypotheses are accepted. Based on the research results, it is recommended that the Golden Kids Bandar Lampung Store continue to improve product quality, optimize customer value, set competitive prices, and strengthen product competitiveness strategies. Continuous monitoring and evaluation of the influence of these variables is also important to support more appropriate decision making and the development of more effective strategies.

Optimizing last-mile delivery in E-Commerce logistics a multi-faceted approach

Efficient last-mile delivery is crucial in e-commerce logistics, impacting customer satisfaction, costs, and sustainability. This abstract explores strategies for optimization, utilizing a multi-faceted approach. Advanced technologies like route optimization algorithms and real-time tracking systems enhance delivery efficiency by minimizing transit times and optimizing resource use. Data analytics further refine routes based on variables like traffic and weather. Collaborative partnerships and decentralized logistics networks reduce individual deliveries and environmental impact. Micro-fulfilment centres in urban areas expedite deliveries, especially in densely populated regions. Customer-centric strategies include personalized delivery options and proactive communication. Time-specific delivery windows and alternative delivery locations cater to diverse preferences, enhancing satisfaction and loyalty. Transparent tracking mechanisms reduce failed deliveries and returns. In general, a multi-faceted approach combining technological innovation, collaboration, and customer-centricity is vital for optimizing last-mile delivery. By synergistically implementing these strategies, e-commerce stakeholders can overcome challenges, driving efficiency, satisfaction, and sustainability in the last mile.

Preventive Maintenance in the 3D Atomic IV Printer Machine using the Analytic Hierarchy Process

Preventive maintenance (PM) of equipment is a crucial aspect of effective manufacturing systems, as inadequate PM can lead to various negative issues, such as quality, productivity cost, customer cost, and maintenance costs. This paper presents a case study approach using the Analytic Hierarchy Process (AHP) and ranking of critical elements for the PM equipment of a 3D Atomic IV printer machine at The Instituto Tecnológico de Ciudad Juárez. AHP was used to find the equipment problem sensors and determine all the criteria weights and rank elements. The principal methodology is applied to a 3D Atomic IV printer to formulate a critical PM strategy.