Satisfy Customer Demand Research Articles

System dynamics model: developing model for supplier selection with a focus on CSR criteria

The complexity and significance of decision-making in selecting suppliers highlight the need for a systematic and transparent approach. The more organizations rely on suppliers, the more harmful the direct and indirect consequences of poor decision-making are. This study attempted to identify factors affecting supplier selection and develop a system dynamics model for supplier selection by taking into account social corporate responsibility (CSR) practices. This model aims to increase CSR practices when selecting suppliers and thus help supply chain members gain competitive power and satisfy customer demands optimally. The system dynamics model for supplier selection was developed by considering profitability, productivity, social transparency, and customer satisfaction. To this end, first, the indicators affecting supplier selection were identified. Then, a cause–effect model was extracted by surveying subject-matter experts. Finally, the system dynamics model was developed. The final output of the third stage was a dynamic model of a supplier selection system that considers CSR practices. The results showed that profitability increases only by implementing the policy of reducing the average distance between suppliers and increasing the number of suppliers. This issue causes lower costs, reduced delivery time due to reduced average distance between suppliers, and increased suppliers, resulting in increased customer satisfaction and increased demand.

How perceived effectiveness of social media platform and satisfaction affect continuance intention in a pandemic: The moderating role of perceived benefit

ABSTRACT Firms facing a global pandemic need to shift to online supply to satisfy customer demand. This study develops a valid measure of the perceived effectiveness of social media platforms (PESMP) and analyzes its effect on customer satisfaction in predicting continuance intentions under the boundary condition of perceived benefit. Drawing on the uses and gratification theory and a sample of 508 customers, the authors substantiate perceived benefit’s moderating role. At high levels of perceived benefit, PESMP exerts a strong effect on satisfaction that increases continuance intention. Implications to increase strategic effectiveness are also discussed.

Study of Saudi Arabian Manufacturing and Service Organization Sustainability and Future Research Directions

Currently, organizations face a range of dynamic challenges to maintain long-term market sustainability. Examples of these challenges are developing and improving their product and or service quality, increasing operational efficiency, complying with safety regulations, enhancing the triple bottom line of agility in manufacturing products and satisfying customer demand. Saudi Arabia has a vision for 2030 where sustainability is one of the corner stones. Here the objective is to explore sustainability awareness in Saudi organizations and their commitment to sustainability; and to present a brief review of approaches adopted by researchers who have implemented sustainability evaluations in different organizations around the world. It is evident that Saudi manufacturing organizations continue to pursue long-term market sustainability, but researchers have not explored sustainability in detail. In particular, an assessment of the sustainability of Saudi manufacturing organizations is lagging. Further studies are needed to develop a model that can be used to assess the sustainability of Saudi manufacturing and service organizations.

Production routing for perishable products

This paper introduces the production routing problem for perishable products with fixed shelf life and gradual decay, where the age of products impacts the price that can be obtained when satisfying customer demands. In this problem, a single supplier is responsible for the production and distribution of perishable products to a set of customers. Fixed setup and variable production costs occur at the supplier location when production takes place, and routing costs are charged for the distribution activities. Additionally, inventory holding costs are incurred at both the production facility and the customer locations. Transshipments between customer locations are allowed on the basis of a unit transshipment cost. The objective is to maximise the total profit given by the sales revenue minus the sum of production, routing, inventory and transshipment costs. The problem is formulated as a mixed integer linear program and solved using a branch-and-cut and a hybrid, iterated local search-based heuristic. Based on the results of the computational experiments, we analyse the impact of perishability on the structure of the solutions. We explore perishability in the form of both product shelf life and decay, observing that larger decay rates lead to a reduction in total profit, as a result of both a decrease in revenues and an increase in the total cost. We further analyse the impact of different decay rates on the cost structure of the problem and the significance of transshipments for the management of perishability across the system. Finally, we adapt our hybrid method to solve the standard production routing problem. Comparison of our results with state-of-the-art solution methods on benchmark instances from the literature shows that our heuristic provides good quality solutions that are competitive with the scientific literature.

Supporting Luxury Hotel Recovered in Times of COVID-19 by Applying TRIZ Method: A Case Study in Taiwan

The current COVID-19 pandemic, which is alarming for another global economic recession, puts the sustainable development of the tourism system under high consideration. The tourism industry is a key generator of foreign exchange across the region. However, tourism is one of the sectors most affected by the global pandemic. Through a case study in Taiwan, the objective of this study is to show how an Evergreen hotel fixed itself on existing and recovering in the hospitality business during the COVID-19 pandemic in 2020 using the combination of the problem hierarchy analysis (PHA) and the Teoriya Resheniya Izobreatatelskih Zadatch (TRIZ) or the so-called theory of inventive problem-solving technique. Following PHA technique and extensive investigation, the management team determined that the most recent problems at the Evergreen hotel are in marketing and human resources. The 39 parameters and 40 principles of TRIZ were used to determine the improvement solution and create a solution strategy that simultaneously simplified critical control-point (CCP) processes and improved the correctness of tasks, increasing CCP efficiency and supporting and satisfying customer demands in the COVID-19 pandemic in the world in general and in Taiwan in particular. The results revealed that customer bookings grew over the four quarters of 2020 due to adjusting the cancellation policy, discounting, and segmenting the market from international to domestic, increasing the CCP efficiency percentage and customer rating score from 19% to 40% and 8.3 to 8.5 score, respectively. Aside from that, changing the hotel structure with a partnership with the Taixie company assisted Evergreen in reducing various cost pressures to manage the business and recover after a difficult period. This paper can be a useful reference for managers, investors, governments, and policymakers to improve the sustainability performance in the tourism industry.

Joint optimization of lot-sizing and pricing with backlogging

Lot-sizing and pricing are two important manufacturing decisions that impact together the profit of a company. Existing works address the joint lot-sizing and pricing problem without backlogging, although it is a usual strategy that permits to satisfy customer demand with delay. In this work, we study a new multi-product joint lot-sizing and pricing problem with backlogging and limited production capacity. The objective is to maximize the total company profit over a finite planning horizon. For the problem, a mixed integer nonlinear programming (MINLP) formulation is given. Then, several optimality properties are provided and a tighter MINLP model is established based on these properties. According to the NP-hard nature and non-linearity of the model, a model based heuristic that focuses on efficiently solving small-sized instances is proposed and a genetic algorithm (GA) with new progressive repair strategy is developed to address large-sized instances. Managerial insights are drawn based an illustrative example. Numerical experiments are conducted on 64 benchmark based instances and 105 randomly generated instances with up to 10 products and 12 periods, which validates the MINLP formulation and shows the efficiency of the proposed solution methods.

Toward a reliable and responsive E-commerce with IoT

Modern logistics becomes mostly web-centric, its goal overpassed the productivity in traditional warehouses to aim the effectiveness and satisfy customer demands in the context of E-commerce. This article presents a modern type of warehouse based on IoT, using existing technology such RFID solution, to increase inventory reliability by reducing the risk of human errors and it covers 90% of all warehouse operations. Through this article, we analyzed the main areas of improvement for RFID solution, such it does not cover the picking area; unlike in gross storage areas where every palette may contain an RFID Tag in permanent communication with ERP/WMS. However, in the retail area the products are not tracked (possibly but expensive), leaving low visibility on real-time inventory behind with the risk of inventory shortage for items already ordered by customers on the e-commerce platform or excess inventory. The solution we proposed covers this flaw, by creating smart picking areas, based on weighing to get primary data to be quantified. This solution increases inventory reliability and responsivity by helping the retail areas resupply and mastering the picking and preparation delays.

Enhancement of product design capability in the high-tech manufacturing industry

Satisfying customer demand represents a challenge for product designers because manufacturers must clearly understand what design aspects meet customer desires to obtain a competitive advantage in ...

Enhancing production agility using enterprise systems

ABSTRACT To satisfy customer demands and achieve organisational targets effectively, production operations in manufacturing companies must be nimble and responsive. The evolution of enterprise systems (ESs) technologies has made knowledge management (KM) strategies to acquire and share data possible in real-time using approaches such as business intelligence to provide information analytics for data-driven decision-making. This paper examines the use of an ES for improving production agility in New Zealand firms by investigating three implementation case studies. Findings reveal that ESs drive schedules, automate release of job orders and optimise resource capacities by capturing pertinent data in real-time to increase organisational agility in timely producing and dispatching products to customers. Although organisations sometimes get constrained in material availability in operations, the ES technology in conjunction with KM processes provides the connectivity and information support along with knowledge-based analytics to build-up production agility in manufacturing firms.

Emergency Shipment Decision in Newsvendor Model

Emergency shipments are considered as an efficacious approach for mitigating the risk of shortages and increasing resilience in inventory systems. In this study, we develop a new newsvendor model where the retailer has a single opportunity to trigger an emergency shipment during the selling season. Due to demand uncertainty, it might not be possible to satisfy customer demands during the season. Provision for requesting an emergency shipment within the season can reduce the possibility of imminent shortages. As emergency shipments affect the dynamic of the system over time, the timing of emergency shipments in addition to their sizes is of particular interest. We use the time-weighted holding cost to compute the expected holding cost and assume that any unmet demand is lost. The goal is to determine the pre-season order quantity and both size and time of the emergency shipment such that the expected profit is maximized. We find that the newsvendor problem under time-weighted holding cost has a different structure and provide a different optimal order quantity. Our numerical experiences indicate that triggering an emergency shipment during the selling season can significantly improve cost savings. The results of a set of computational experiments demonstrate the superior performance of our proposed model when compared with the classical newsvendor problem. A sensitivity analysis is conducted showing that in the classical model, the unit lost sale cost is the most effective input parameter on the expected profit value. Moreover, the selling price and unit holding cost significantly affect the size and time of the emergency shipment.

Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm

The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm is based on the hybridization of two metaheuristics, which are the bat algorithm (BA) and the generalized evolutionary walk algorithm (GEWA), also called BAG (bat algorithm with generalized flight). The approach is combined with the Ushakov method, the universal moment generating function (UMGF), to evaluate the reliability of the multi-state series-parallel system. The multi-objective design aims to minimize the design cost, and to maximize the reliability and the performance of the electric power generation system from solar and gas generators by taking into account the reliability indices. Power subsystem devices are labeled according to their reliabilities, costs and performances. Reliability hangs on an operational system, and implies likewise satisfying customer demand, so it depends on the amassed batch curve. Two different design allocation problems, commonly found in power systems planning, are solved to show the performance of the algorithm. The first is a bi-objective formulation that corresponds to the minimization of system investment cost and maximization of system availability. In the second, the multi-objective formulation seeks to maximize system availability, minimize system investment cost, and maximize the capacity of the system.

A capacity planning approach for sustainable-resilient supply chain network design under uncertainty: A case study of vaccine supply chain

This paper introduces a multi-objective mathematical model to design a sustainable-resilient supply chain based on strategic and tactical decision levels. The resolution is to proactively plan for an optimal configuration to satisfy customer demands when the firm is highly vulnerable to operational and disruption risks. Compared to previous studies, we take the application of capacity planning in terms of redundancy to design a supply chain network that is resilient toward the demand-side by an optimization framework. A real-world influenza vaccine supply chain is studied to validate the proposed model and examine the tradeoff between resilience and sustainability. A robust fuzzy optimization approach is employed to cope with uncertainties. Then, the multi-objective model is solved by applying multi-choice goal programming with a utility function approach. Accordingly, managerial insights are suggested by analyzing the effects of structural parameters on the quantitative results. It is revealed that having redundancies in the supply chain does not always increase the total costs.

Optimization of Rider Scheduling for a Food Delivery Service in O2O Business

Services such as Meituan and Uber Eats have revolutionized the way the customer can find and order from restaurants. Numerous independent restaurants are competing for orders placed by customers via online food ordering platforms. Ordering takeout food on smartphone apps has become more and more prevalent in recent years. There are some operational challenges that takeout food service providers have to deal with, e.g., customer demand fluctuates over time and region. In this sense, the service providers sometimes ignore the fact that some riders may be idle in several periods in regions, while, in contrast, there may be a shortage of riders in other situations. In order to address this problem, we introduce a two-stage model to optimize scheduling of riders for instant food deliveries. A service provider platform expectantly schedules the least quantity of riders to deliver within expected arrival time to satisfy customer demand in different regions and time periods. We introduce a two-stage model that adopts the method of mixed-integer programming (MIP), characterize relevant aspects of the scenario, and propose an optimization algorithm for scheduling riders. We also divide the delivery service region and time into smaller parts in terms of granularity. The large neighborhood search algorithm is validated through numerical experiments and is shown to meet the design objectives. Furthermore, this study reveals that the optimization of rider resource is beneficial to reduce overall cost of the delivery. Takeout food service platforms decide scheduling shifts (start time and duration) of the riders to achieve a service level target at minimum cost. Additional sensitivity analyses, such as the tightness of the order time windows associated with the orders and riders’ familiarity with delivery regions, are also discussed

English

–Abstract– There is an interlink, on management, planning, and cohesiveness remained a challenging factor to fully explore the Namibian Transportation and Supply Chain Management potential in the country. The problem identified is that Namibia maritime supply chain partners are facing challenges to work together to enhance the operations of the ports in Namibia due to a lack of a collaborative planning system. The study intended to analyze key elements and factors that are critical to Collaborative Planning, Forecasting and Replenishment CPFR as a measure to improve the cooperative of all stakeholders in the industry throughout the supply chain management system through improved transportation and cargo handling. Information shared between suppliers and retailers aids in planning, and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to- end supply chain process more efficient. The main objective of the study is to investigate the role of a collaborative planning system for maritime supply chain partners in enhancing port operations in Namibia. Seven Institutions, which are the partners in the maritime supply chain, namely Namport, TransNamib, Road fund administration, Roads authority, Air Namibia, Airport Company, and NCCI, participated in this study, whereby for each institution, 10 respondents were purposefully selected. An open-ended and closed ended questions, which will be used to uncover the role of cps in enhancing port operation in Namibia. 72% of participants felt that lack of planning system affected service delivery. Whilst, 85.3% agreed that there are factors that need to be addressed to enhance the planning system, and 83.6% felt that the planning system contributed to the enhancement of service delivery. It will be good if the Ministry of Works and Transport, supported by the National Keywords : Planning Commission, Spearheads this committee.

Inventory Timing: How to Serve a Stochastic Season

Problem Definition. Firms that sell products over a limited selling season often have only imperfect information about (a) the exact timing of that season, (b) the demand volume to expect, and (c) the temporal distribution of demand over the selling season. Given these uncertainties, firms must determine not only how much inventory to stock but also when to make that inventory available to customers. We ask: What is a firm’s optimal inventory quantity and timing for products sold during a stochastic selling season? Academic and Practical Relevance. Managers are frequently confronted with challenging inventory timing decisions, especially when the products they manage exhibit high inventory holding costs and substantial uncertainty concerning the pattern of customer demand. Although the newsvendor literature has developed a thorough understanding of the firm’s optimal inventory quantity, it has failed to inform decision makers about choosing the optimal inventory timing. Methodology. We develop a theoretical model of a firm that sells a product over a stochastic selling season, and we study how this firm should choose its inventory timing and inventory quantity so as to maximize expected profits. Results. We derive the firm’s optimal inventory policy—which comprises inventory timing and inventory quantity—and discuss the interaction effects between these two decisions. We also identify the effects of optimal inventory timing on a firm’s ability to satisfy customer demand and show how early inventory timing can be detrimental to customer service. Managerial Implications. Our core insights imply two immediate recommendations for managers. First, optimal inventory timing is an effective weapon for combatting both high inventory holding costs and high levels of uncertainty in the firm’s customer demand pattern. Second, naive decision rules (e.g., “earlier is better”) may reduce not only the firm’s profits but also its capacity to serve customer demand.

BUSINESS RESPONSE TO MARKET TENDENCIES: CONSUMERISM, AI, E-COMMERCE, AND THEIR INFLUENCE ON MODERN SOCIETIES

Businesses have a high reliance on consumer behavior due to the impact of tendencies and market forces. They continually adapt and change their performance to increase performance and consumer satisfaction in changing market conditions. Those forces include consumerism which requires substantial business preparation to satisfy customer demands. The development of AI leaves a visible trace in business-consumer communication, including moments of truth that can affect future communities. Compound components affect business marketing, advertising, and e-commerce presence. For this reason, this paper researches the influence of consumerism and the rise of AI on business accommodation and its role in modern societies.

Building Sustainable Contextual Ambidexterity through Routines: A Case Study from Information Technology Firms

The purpose of this paper is to explain the role that routines play in achieving sustainable organisational ambidexterity in information technology (IT) firms. Our exploratory analysis of four case studies reveals the key importance of routines in setting the context for sustainable ambidexterity. Companies build up contextual ambidexterity through routines derived from normalization of processes, normalization of skills, and normalization of results. The findings of the study show that routines support IT professionals to decide whether to exploit or explore in each particular case. Firstly, the enabling character of explicit routines as a result of the normalisation of work processes and the freedom that IT professionals have when implementing them, allows IT professionals to balance exploitation and exploration. Secondly, companies build up contextual ambidexterity through normalisation of skills. Hence, IT professionals develop embedded implicit routines as a result of training. Thirdly, the findings of the study reveal how routines are settled through the normalisation of results that orientates performance towards satisfying customer demands, as well as supporting professionals in their efforts to balance between exploitation and exploration which is necessary to achieve sustainable ambidexterity in IT firms.

Factors influencing the development of innovative business model in the IT industry

ABSTRACT Many countries have recently witnessed the structure of their economies shift from industrial production to service-sector activities. In particular, this shift has characterised Taiwan’s economy, which nevertheless has grown sluggish in the last few years. In addressing the sluggish environment, Taiwanese companies have been enhancing their business processes with new business models that innovatively satisfy customer demands. In the current study, we explore factors that powerfully support IT firms’ efforts to develop innovative business model. Having invented a STEP2 model for this task, we uncovered factors that are highly relevant to service innovation, technology adaptation, environmental transformation, process planning, and people requirements. For the current study, we collected 210 completed online surveys, of which we were able to analyse 195. We found that three factors – environmental transformation, process planning, and people requirements – are particularly useful for firms seeking to enhance the innovativeness of their services. We also found that service innovation affects the development of innovation-oriented business models. Thanks to this study’s STEP2 model, our findings should have significant theoretical and practical implications.

A Literature Review on Fuzzy Process Capability Analysis

Abstract Process capability analysis (PCA) that can be defined as the ability of any process to satisfy customer demands expressed via specification limits (SLs) is effectively utilized as an important function of statistical process control in order to examine process variability. PCA provides information about conforming and nonconforming production rates that indicate the amount of products that fall inside and outside of SLs, respectively. It is possible to classify processes as “capable” and “incapable” according to values of process capability indexes (PCIs). Therefore, PCA has a wide usage and critical effects on the manufacturing process. The fuzzy set theory can be successfully utilized in order to cope with vagueness and to add more flexibility and sensitiveness into traditional PCIs. For this aim, upper and lower specification limits can be expressed by means of linguistic variables. Fuzzy process capability indexes (FPCIs) can be produced by using fuzzy mean and fuzzy variance. There are many studies that utilized FPCIs for PCA in the literature. This study seeks to present a comprehensive literature review for publications related to FPCIs. These studies have been analyzed according to some features of them, such as year, document type, journal name, and country. Also, classifications including FPCI, application area, fuzzy parameters, and type of fuzzy sets have been presented in this study. Additionally, some statistical analyses have been conducted. As a result, we desired to provide a roadmap for researchers in this field and to present recent advances regarding FPCIs. The main aim of this article is to show possible future research areas on fuzzy PCA.

O uso da Pesquisa Operacional como instrumento fundamental para maximização do rendimento financeiro

O presente artigo tem como objetivo principal apresentar uma proposta de aplicação da Pesquisa Operacional com recurso a programação linear para maximizar o rendimento financeiro da empresa de material para construção civil de Malanje. O estudo foi realizado com base na utilização do método quantitativo. Entretanto, depois de formulado o problema, foram definidas as variáveis de decisão, formação das restrições, seguidamente se identificou a função objetivo de acordo os lucros estimados em cada produto da empresa. Com auxílio do algoritmo gráfico permitiu formular um problema Matemático com modelagem probabilística, das quais seis iterações foram realizadas para encontrar a melhor solução ótima que maximizasse o rendimento financeiro da empresa. Por meio do estudo realizado concluiu-se que, a solução ótima de um problema de programação linear para maximizar o rendimento da empresa é a solução admissível ou ponto fatível que apresenta valor máximo para a função objetivo. A partir desta pesquisa é possível compreender que as empresas que tendem permanecer competitivas no mercado devem fazer um conjunto de esforços para satisfazer a demanda do cliente.