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\"Remove built-in supply chain weak points to more effectively balance supply and demand Demand-Driven Inventory Optimization and Replenishment shows how companies can support supply chain metrics and business initiatives by removing the weak points built into their inventory systems. Beginning with a thorough examination of Just in Time, Efficient Consumer Response, and Collaborative Forecasting, Planning, and Replenishment, this book walks you through the mathematical shortcuts set up in your management system that prevent you from attaining supply chain excellence. This expanded second edition includes new coverage of inventory performance, business verticals, business initiatives, and metrics, alongside case studies that illustrate how optimized inventory and replenishment delivers results across retail, high-tech, men's clothing, and food sectors. Inventory optimization allows you to avoid out-of-stock situations without impacting the bottom line with excessive inventory maintenance. By keeping just the right amount of inventory on hand, your company is better able to meet demand without sacrificing the cost-effectiveness of other supply chain strategies. The trick, however, is determining "just the right amount"--and this book provides the background and practical guidance you need to do just that. Examine the major supply chain strategies of the last 30 years Remove the shortcuts that prohibit supply chain excellence Optimize your supply/demand balance in any vertical Overcome systemic weaknesses to strengthen the bottom line Inventory optimization is benefitting companies around the world, as exemplified here by case studies involving Matas, CV Voorfruit, Tesco, PWT, Wistron, and Amway. When inefficiencies are built into the system, it's only smart business to identify and remove them--and implement a new streamlined process that runs like a well-oiled machine. Demand-Driven Inventory Optimization and Replenishment is an essential resource for exceptional supply chain management\"-- Provided by publisher.

This study aims to assess the customer demand and satisfaction through social and environmental CSR practices based on tourist's perception in Bangladesh hotel sector. Data were collected through the survey questionnaire across the three famous tourist destination cities (Dhaka, Chittagong and Cox's bazar) of Bangladesh. The valid sample size of this study was 402 and respondents were selected executing systematic sampling technique. Data were analysed through SmratPLS 3.0 software. From the findings, it was found that both social and environmental CSR has a positive association with customer demand, whereas, only social CSR is positively associated with customer satisfaction and environmental CSR has no significant association with customer satisfaction. Also, customer demand positively associated with customer satisfac tion.

Purpose: Purpose of this study includes the quantification of the impact of transportation efficiency onto the workstations the transportation serves in term of throughput and total lead time elapsed by product. Besides, it aims to synchronize the capacity available among workstations throughout a production line by studying the upper limit of throughput could be afforded by each workstation as well as their connection with each other. This study is also done on the purpose of promoting fulfillment of customer demand at shorter delivery time and minimal equipment utilization. Investigation on implementation of Overall Equipment Effectiveness (OEE) in an aerospace part-manufacturing company is studied to track out the potential opportunities to be improved. Design/methodology/approach: Site observation is conducted on all the five manufacturing workstations in the aforementioned aerospace part manufacturing company. Time data of both automated processes and manual processes are collected and they are used to construct simulation model. From that, various scenarios of transportation efficiency are simulated in Experiment 1. In addition, Experiment 2 is also set to examine the maximum capacity of each workstation. All of these are to highlight the relationship between workstation and processes and to verify the condition of imbalanced capacity among workstations in the company. In short, this has necessitated the integration of workstation and transportation activities within the company. These are followed by proposal of measures to quantify the wastes identified. Findings: The paper finds that implementation of OEE alone does not consider the reasonability of customer demand fulfillment. The results show that both transportation efficiency and imbalanced capacity throughout production system are not emphasized by OEE implementation in the case company. Therefore, responsibility of all workstations and transportation process in delivering demand on time are quantified. Transportation process which serves as the connectors of manufacturing processes is quantified and monitored by proposed Transportation Measure (TM) whereas workstations are measured using novel availability and performance ratio. Research limitations/implications: Future research should be conducted to examine the impact of other station within a company such as warehouse and logistic department to the performance of equipment and materials in manufacturing workstation. Besides, the material availability as well as the skills or performance of man power could be further incorporated into the measures to consider all the entities involved in manufacturing processes. Practical implications: The proposed availability and performance ratio for both transportation and manufacturing processes, which are related to each other, help in promoting better effectiveness of production system in terms of production amount and lead time. Besides, reasonable utilization equipment and minimal consumption of material are incorporated in the measures to promote Lean way in fulfilling customer demand. The effectiveness of entire production line is examined as a unity with joint responsibility under varying transportation efficiency and cycle time of each workstation. Both measures could be implemented together to optimize the production system and quantify the hidden wastes which are neglected in the OEE implementation. Originality/value: The novel availability and performance ratio are proposed to consider customer demand, historical equipment utilization and Takt time of each workstation to examine the possibility and reasonability of demand fulfillment. This prevents both over-processing and overproduction issues which are invisible in OEE. Furthermore, delay propagation throughout production system and interrelationship between processes are quantified under transportation measure. Other novelty of the paper is that it monitors the waiting time and lead time spent in each workstation at the same time considering utilization of workstation. The proposed Transportation Measure (TM) aims to reduce the queue length and waiting time at destination workstation at minimal utilization of forklift. It also promotes less capacity investment in transportation and prioritizes its scheduling according to urgency of destination workstation.

Purpose: The purpose of this paper is to analyze the impacts of over meeting customer demands on the product development process, which is on the basis of the quantitative model of customer demands, development cost and time. Then propose the corresponding product development optimization decision. Design/methodology/approach: First of all, investigate to obtain the customer demand information, and then quantify customer demands weights by using variation coefficient method. Secondly, analyses the relationship between customer demands and product development time and cost based on the quality function deployment and establish corresponding mathematical model. On this basis, put forward the concept of customer demand saturation and optimization decision method of product development, and then apply it in the notebook development process of a company. Finally, when customer demand is saturated, it also needs to prove the consistency of strengthening satisfies customer demands and high attention degree customer demands, and the stability of customer demand saturation under different parameters. Findings: The development cost and the time will rise sharply when over meeting the customer demand. On the basis of considering the customer demand saturation, the relationship between customer demand and development time cost is quantified and balanced. And also there is basically consistent between the sequence of meeting customer demands and customer demands survey results. Originality/value: The paper proposes a model of customer demand saturation. It proves the correctness and effectiveness on the product development decision method.

Objective of the Study: This study aims to examine the key drivers of effective green new product development (GNPD) performance. Specifically, it explores the relationships between customer demand, competitive pressure, customer participation, and GNPD performance through the theoretical lens of the demand-based view. The study seeks to demonstrate how demand-based view influence green GNPD, with a particular focus on the mediating role of customer participation.  Methodology: A quantitative research approach was employed, utilizing survey data collected from 81 Malaysian electrical and electronics (E&E) manufacturing firms. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed relationships among customer demand, competitive pressure, customer participation, and GNPD performance.  Originality: This study contributes to the literature by addressing a theoretical gap in the demand-based view, which has been underutilised in explaining green product innovation. By integrating customer demand, competitive pressure and customer participation into the GNPD framework, this study provides new insights into the antecedents of successful green innovation. The findings have academic relevance by extending the application of the demand-based view to sustainability-driven product development.  Main Results: The results indicate that competitive pressure positively influences customer participation in GNPD, which in turn mediates the relationship between competitive pressure and GNPD performance. However, no significant relationship was found between customer demand and customer participation. These findings underscore the importance of competitive dynamics in driving customer engagement and sustainability initiatives, especially in emerging markets. Theoretical Contributions: This study use the demand-based view as the underpinning and positioning customer participation as a crucial mechanism through which customer and competitive pressures translate into GNPD success. Managerial Contributions: For managers, the study highlights the necessity of actively engaging and integrating customers throughout the GNPD process to meet market demand for sustainability. By understanding the role of competitive pressure in fostering customer participation, businesses can enhance their green innovation strategies. Objetivo del Estudio: Este estudio tiene como objetivo examinar los principales impulsores del rendimiento efectivo en el desarrollo de nuevos productos ecológicos (GNPD). Específicamente, explora las relaciones entre la demanda del cliente, la presión competitiva, la participación del cliente y el rendimiento del GNPD a través de la lente teórica de la visión basada en la demanda. El estudio busca demostrar cómo la visión basada en la demanda influye en el GNPD verde, con un enfoque particular en el papel mediador de la participación del cliente. Metodología: Se empleó un enfoque de investigación cuantitativa, utilizando datos de encuestas recopilados de 81 empresas manufactureras del sector eléctrico y electrónico (E&E) en Malaysia. Los datos fueron analizados mediante Modelado de Ecuaciones Estructurales por Mínimos Cuadrados Parciales (PLS-SEM) para probar las relaciones propuestas entre la demanda del cliente, la presión competitiva, la participación del cliente y el rendimiento del GNPD. Originalidad: Este estudio contribuye a la literatura abordando una brecha teórica en la visión basada en la demanda, que ha sido subutilizada para explicar la innovación de productos ecológicos. Al integrar la demanda del cliente, la presión competitiva y la participación del cliente en el marco de GNPD, este estudio proporciona nuevas perspectivas sobre los antecedentes del éxito de la innovación ecológica. Los hallazgos tienen relevancia académica al extender la aplicación de la visión basada en la demanda al desarrollo de productos impulsados por la sostenibilidad. Resultados Principales: Los resultados indican que la presión competitiva influye positivamente en la participación del cliente en el GNPD, que a su vez media la relación entre la presión competitiva y el rendimiento del GNPD. Sin embargo, no se encontró una relación significativa entre la demanda del cliente y la participación del cliente. Estos hallazgos destacan la importancia de la dinámica competitiva para impulsar la participación del cliente y las iniciativas de sostenibilidad, especialmente en mercados emergentes. Contribuciones Teóricas: Este estudio utiliza la visión basada en la demanda como base teórica y posiciona la participación del cliente como un mecanismo crucial a través del cual las presiones del cliente y la competencia se traducen en el éxito del GNPD. Contribuciones Gerenciales: Para los gerentes, el estudio resalta la necesidad de involucrar e integrar activamente a los clientes en todo el proceso de GNPD para satisfacer la demanda del mercado por sostenibilidad. Al comprender el papel de la presión competitiva en el fomento de la participación del cliente, las empresas pueden mejorar sus estrategias de innovación ecológica. Objetivo do Estudo: Este estudo tem como objetivo examinar os principais fatores que impulsionam o desempenho eficaz do desenvolvimento de novos produtos verdes (GNPD). Especificamente, explora as relações entre demanda do cliente, pressão competitiva, participação do cliente e desempenho do GNPD sob a perspectiva teórica da visão baseada na demanda. O estudo busca demonstrar como a visão baseada na demanda influencia o GNPD verde, com foco particular no papel mediador da participação do cliente. Metodologia: Foi adotada uma abordagem de pesquisa quantitativa, utilizando dados de pesquisa coletados de 81 empresas do setor elétrico e eletrônico (E&E) na Malaysia. Os dados foram analisados por meio da Modelagem de Equações Estruturais com Mínimos Quadrados Parciais (PLS-SEM) para testar as relações propostas entre demanda do cliente, pressão competitiva, participação do cliente e desempenho do GNPD. Originalidade: Este estudo contribui para a literatura ao abordar uma lacuna teórica na visão baseada na demanda, que tem sido pouco utilizada para explicar a inovação de produtos verdes. Ao integrar demanda do cliente, pressão competitiva e participação do cliente no modelo de GNPD, este estudo fornece novos insights sobre os fatores que impulsionam o sucesso da inovação sustentável. Os resultados têm relevância acadêmica ao expandir a aplicação da visão baseada na demanda para o desenvolvimento de produtos orientados à sustentabilidade. Principais Resultados: Os resultados indicam que a pressão competitiva influencia positivamente a participação do cliente no GNPD, que, por sua vez, medeia a relação entre pressão competitiva e desempenho do GNPD. No entanto, não foi encontrada uma relação significativa entre demanda do cliente e participação do cliente. Esses achados destacam a importância da dinâmica competitiva na promoção do engajamento do cliente e das iniciativas de sustentabilidade, especialmente em mercados emergentes. Contribuições Teóricas: Este estudo utiliza a visão baseada na demanda como base teórica e posiciona a participação do cliente como um mecanismo essencial pelo qual as pressões dos clientes e da concorrência se traduzem no sucesso do GNPD. Contribuições Gerenciais: Para os gestores, o estudo destaca a necessidade de envolver e integrar ativamente os clientes em todo o processo de GNPD para atender à demanda do mercado por sustentabilidade. Ao compreender o papel da pressão competitiva na promoção da participação do cliente, as empresas podem aprimorar suas estratégias de inovação verde.

Accurate short-term load forecasting (STLF) is essential for power grid systems to ensure reliability, security and cost efficiency. Thanks to advanced smart sensor technologies, time-series data related to power load can be captured for STLF. Recent research shows that deep neural networks (DNNs) are capable of achieving accurate STLP since they are effective in predicting nonlinear and complicated time-series data. To perform STLP, existing DNNs use time-varying dynamics of either past load consumption or past power correlated features such as weather, meteorology or date. However, the existing DNN approaches do not use the time-invariant features of users, such as building spaces, ages, isolation material, number of building floors or building purposes, to enhance STLF. In fact, those time-invariant features are correlated to user load consumption. Integrating time-invariant features enhances STLF. In this paper, a fuzzy clustering-based DNN is proposed by using both time-varying and time-invariant features to perform STLF. The fuzzy clustering first groups users with similar time-invariant behaviours. DNN models are then developed using past time-varying features. Since the time-invariant features have already been learned by the fuzzy clustering, the DNN model does not need to learn the time-invariant features; therefore, a simpler DNN model can be generated. In addition, the DNN model only learns the time-varying features of users in the same cluster; a more effective learning can be performed by the DNN and more accurate predictions can be achieved. The performance of the proposed fuzzy clustering-based DNN is evaluated by performing STLF, where both time-varying features and time-invariant features are included. Experimental results show that the proposed fuzzy clustering-based DNN outperforms the commonly used long short-term memory networks and convolution neural networks.

With the rapid growth of e-commerce and rising demand for faster, reliable last mile delivery, optimizing the spatial layout of terminal logistics facilities is critical. This paper proposes a two-stage location framework for mini-depots and lockers considering spatiotemporal customer demand. In the first stage, Affinity Propagation (AP) clustering identifies candidate mini-depot locations and locker layouts based on temporal and spatial demand characteristics. In the second stage, an Adaptive Heuristic Electric Eel Foraging Optimization (AHEEFO) determines the optimal mini-depot location strategy to minimize total cost. A dataset of 1157 Beijing customer points, including latitude, longitude and demand information, is used for model validation. Results show that Scenario 2, with dispersed demand, outperforms Scenario 1 and traditional strategies in both total cost and customer satisfaction; dispersed demand can be effectively supported via crowdsourced delivery and locker layout, whereas concentrated demand requires more professional courier resources. Comparative experiments reveal AP clustering is more stable, reducing clustering-stage cost by 13.57% compared with K-means, and AHEEFO outperforms other algorithms in cost optimization, computational efficiency, and significance tests under random demand surges. Finally, the sensitivity analysis highlights the effects of different algorithmic and operational parameters, offering valuable insights for both managerial practice and academic research.

PurposeThis study aims to analyse the resilience of customer demand management post-coronavirus disease 2019, using fast fashion as an example. The paper provides insights for potential applications to micro-, small and medium enterprises (MSMEs).Design/methodology/approachBased on the qualitative analysis and an integrated Plan-Do-Check-Act (PDCA)-decision making trial and evaluation laboratory (DEMATEL)-fuzzy technique for order of preference by similarity to the ideal solution (TOPSIS) methodology of fuzzy multi-criteria decision-making, we explored and prioritised the enablers of resilience management for fast-fashion MSMEs.FindingsThe results reveal that the highest priority enabler is maintaining customer loyalty. Other enablers are associated with e-commerce endorsement, a customer-focussed assortment of items and flexible store operations.Research limitations/implicationsThe study findings will enable fast-fashion MSMEs to develop effective actions and priorities in operations efforts to promote post-pandemic recovery.Originality/valueDespite the importance of the resilience project and the changing fast-fashion customer patterns, only a handful of studies have explored how resilience can be managed in this field. Thus, the findings can contribute to closing this gap in the context of operations resilience research as well as MSME operations.

Extant research provides valuable knowledge about how firms can satisfy their customers. However, it is unclear how customers themselves contribute to their satisfaction. From a basis in the job demands–resources model, the authors propose a customer demands–resources model. In this model, customer demands (negative customer behaviors) and customer resources (positive customer behaviors) affect customer satisfaction through frontline employees’ customer-oriented attitudes and customer-oriented behaviors. Using dyadic data from 141 frontline employees and 375 customers, this study identifies customer behaviors as an important source of customer satisfaction. Customer demands impede frontline employees’ customer-oriented attitudes and customer satisfaction through frontline employees’ emotional exhaustion, whereas customer resources indirectly increase customer satisfaction. Customer resources also buffer the negative effect of customer demands on frontline employees’ customer-oriented attitudes.

PurposeThe purpose of this paper is to examine the role of market innovation in driving service performance in the context of environmental pressures. This paper argues from the complexity theory that the development and the implementation of market innovation must critically examine the effect of customer demand and competitive intensity in the innovation efforts of service firms.Design/methodology/approachData from different sub-sectors of the services industry of a growing emerging African economy are used. Structural equation modeling was used in analyzing the interconnection among environmental pressures, market innovation and firm performance.FindingsThe study found that both market demand and competition impact on innovation development positively. However, in terms of the moderation effects, competition negatively moderates the relationship between innovation and performance, while customer demand moderates the relationship positively.Practical implicationsThe implications are that the implementation of market innovation must be reduced in low demand periods and high competitive periods in order to maximize financial and non-financial performance benefits for the service firm.Originality/valueThe current study complements the complexity theory by stating that the complex nature of business environment presents both opportunities and threats. However, for effective sense making out of the information provided by environment, service firms must evaluate environmental effect differently. While a factor may promote the development of strategy, same environmental factor may hinder the positive influence such strategy may have on overall firm performance.