Search results for: supply demand model

Authors: Sutanto, Alexander Christy, N. Sutrisno

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The demand of a product is linearly dependent on the price and quality of the product. It is analog to the demand of the employee in job-seeker problem. This paper address a closed-loop supply chain (CLSC) where a university plays role as manufacturer that produce graduates as job-seeker according to the demand and promote them to a certain corporation through a trial. Unemployed occurs when the job-seeker failed the trial or dismissed. A third party accomodates the unemployed and sends them back to the university to increase their quality through training.

Keywords: CLSC, price, quality, job-seeker problem

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Authors: Nadia Adnan, Muhammad Mohsin Raza, Latha Ravindran

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Based on the principles above, the study presents an economic model of food waste for consumers, intermediaries, and producers. We discriminate between purchasing and selling, purchases versus customers consumption, and gross output versus sales for each intermediary. To compensate for waste at each level of the supply chain, agents must charge higher sales prices. The research model can produce more accurate predictions about how actions (public regulations or private efforts) to reduce food waste impact markets, including indirect (cascading) effects. With a formal model, researchers demonstrate the uniqueness of these interaction effects and simulate an empirical model calibrated to market characteristics and waste rates in Saudi Arabia. Researchers demonstrate that the effects of waste reduction differ per commodity, depending on supply and demand elasticities, degree of openness to international commerce, and the beginning rates of food loss and waste at each level of the value chain. Because of the consequential effects related to the supply chain, initiatives to minimize food waste will be strengthened in some circumstances and partially countered in others.

Keywords: food loss, food waste, supply chain management, Saudi Arabia, food supply

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Authors: Pappu Kumar, Ajai Singh, Anshuman Singh

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There are different water user sectors such as rural, urban, mining, subsistence and commercial irrigated agriculture, commercial forestry, industry, power generation which are present in the catchment in Subarnarekha River Basin and Ranchi city. There is an inequity issue in the access to water. The development of the rural area, construction of new power generation plants, along with the population growth, the requirement of unmet water demand and the consideration of environmental flows, the revitalization of small-scale irrigation schemes is going to increase the water demands in almost all the water-stressed catchment. The WEAP Model was developed by the Stockholm Environment Institute (SEI) to enable evaluation of planning and management issues associated with water resources development. The WEAP model can be used for both urban and rural areas and can address a wide range of issues including sectoral demand analyses, water conservation, water rights and allocation priorities, river flow simulation, reservoir operation, ecosystem requirements and project cost-benefit analyses. This model is a tool for integrated water resource management and planning like, forecasting water demand, supply, inflows, outflows, water use, reuse, water quality, priority areas and Hydropower generation, In the present study, efforts have been made to access the utility of the WEAP model for water supply and demand analysis for Ranchi city. A detailed works have been carried out and it was tried to ascertain that the WEAP model used for generating different scenario of water requirement, which could help for the future planning of water. The water supplied to Ranchi city was mostly contributed by our study river, Hatiya reservoir and ground water. Data was collected from various agencies like PHE Ranchi, census data of 2011, Doranda reservoir and meteorology department etc. This collected and generated data was given as input to the WEAP model. The model generated the trends for discharge of our study river up to next 2050 and same time also generated scenarios calculating our demand and supplies for feature. The results generated from the model outputs predicting the water require 12 million litter. The results will help in drafting policies for future regarding water supplies and demands under changing climatic scenarios.

Keywords: WEAP model, water demand analysis, Ranchi, scenarios

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Authors: Tamara Slišković, Tomislav Sekur

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This manuscript examines factors that affect demand and supply of the housing market in Croatia. The period from the beginning of this century, until 2008, was characterized by a strong expansion of construction, housing and real estate market in general. Demand for residential units was expanding, and this was supported by favorable lending conditions of banks. Indicators on the supply side, such as the number of newly built houses and the construction volume index were also increasing. Rapid growth of demand, along with the somewhat slower supply growth, led to the situation in which new apartments were sold before the completion of residential buildings. This resulted in a rise of housing price which was indication of a clear link between the housing prices with the supply and demand in the housing market. However, after 2008 general economic conditions in Croatia worsened and demand for housing has fallen dramatically, while supply descended at much slower pace. Given that there is a gap between supply and demand, it can be concluded that the housing market in Croatia is in imbalance. Such trend is accompanied by a relatively small decrease in housing price. The final result of such movements is the large number of unsold housing units at relatively high price levels. For this reason, it can be argued that housing prices are sticky and that, consequently, the price level in the aftermath of a crisis does not correspond to the discrepancy between supply and demand on the Croatian housing market. The degree of rigidity of the housing price can be determined by inclusion of the housing price as the explanatory variable in the housing demand function. Other independent variables are demographic variable (e.g. the number of households), the interest rate on housing loans, households' disposable income and rent. The equilibrium price is reached when the demand for housing equals its supply, and the speed of adjustment of actual prices to equilibrium prices reveals the extent to which the prices are rigid. The latter requires inclusion of the housing prices with time lag as an independent variable in estimating demand function. We also observe the supply side of the housing market, in order to explain to what extent housing prices explain the movement of new construction activity, and other variables that describe the supply. In this context, we test whether new construction on the Croatian market is dependent on current prices or prices with a time lag. Number of dwellings is used to approximate new construction (flow variable), while the housing prices (current or lagged), quantity of dwellings in the previous period (stock variable) and a series of costs related to new construction are independent variables. We conclude that the key reason for the imbalance in the Croatian housing market should be sought in the relative relationship of price elasticities of supply and demand.

Keywords: Croatian housing market, economic crisis, housing prices, supply imbalance, demand imbalance

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Authors: Jacky Hau

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The prevalence of emerging technologies disrupts various industries as well as consumer behavior. Data collection has been in the fingertip and inherited through enabled Internet-of-things (IOT) devices. Big data analytics (BDA) becomes possible and allows real-time demand network management (DNM) through leagile supply chain. To enhance further on its resilience and predictability, governance is going to be examined to promote supply chain transparency and trust in an efficient manner. Leagility combines lean thinking and agile techniques in supply chain management. It aims at reducing costs and waste, as well as maintaining responsiveness to any volatile consumer demand by means of adjusting the decoupling point where the product flow changes from push to pull. Leagility would only be successful when collaborative planning, forecasting, and replenishment (CPFR) process or alike is in place throughout the supply chain business entities. Governance and procurement of the supply chain, however, is crucial and challenging for the execution of CPFR as every entity has to walk-the-talk generously for the sake of overall benefits of supply chain performance, not to mention the complexity of exercising the polices at both of within across various supply chain business entities on account of organizational behavior and mutual trust. Empirical survey results showed that the effective timespan on demand forecasting had been drastically shortening in the magnitude of months to weeks planning horizon, thus agility shall come first and preferably following by lean approach in a timely manner.

Keywords: governance, leagility, procure-to-pay, source-to-contract

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Authors: Benga Ebouele, Thomas Tengen

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Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

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Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

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Authors: Mohammad Mahdi Paydar, Armin Cheraghalipour, Mostafa Hajiaghaei-Keshteli

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Nowadays, in advanced countries, agriculture as one of the most significant sectors of the economy, plays an important role in its political and economic independence. Due to farmers' lack of information about products' demand and lack of proper planning for harvest time, annually the considerable amount of products is corrupted. Besides, in this paper, we attempt to improve these unfavorable conditions via designing an effective supply chain network that tries to minimize total costs of agricultural products along with minimizing shortage in demand points. To validate the proposed model, a stochastic optimization approach by using a branch and bound solver of the LINGO software is utilized. Furthermore, to accumulate the data of parameters, a case study in Mazandaran province placed in the north of Iran has been applied. Finally, using ɛ-constraint approach, a Pareto front is obtained and one of its Pareto solutions as best solution is selected. Then, related results of this solution are explained. Finally, conclusions and suggestions for the future research are presented.

Keywords: perishable products, stochastic optimization, agricultural supply chain, ɛ-constraint

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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The paper discusses the main aspects involved in the development of a supply chain management system using the newly developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: demand forecasting, machine learning, risk management, supply chain design

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Authors: Nusrat T. Chowdhury

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Green Supply Chain Management (GSCM) is becoming a key to success for profitable businesses. The various activities contributing to carbon emissions in a supply chain are transportation, ordering and holding of inventory. This research work develops a mixed-integer nonlinear programming (MINLP) model that considers the scenario of a supply chain with multiple periods, multiple products and multiple suppliers. The model assumes that the demand is deterministic, the buyer has a limited storage space in each period, the buyer is responsible for the transportation cost, a supplier-dependent ordering cost applies for each period in which an order is placed on a supplier and inventory shortage is permissible. The model provides an optimal decision regarding what products to order, in what quantities, with which suppliers, and in which periods in order to maximize the profit. For the purpose of evaluating the carbon emissions, three different carbon regulating policies i.e., carbon cap-and-trade, the strict cap on carbon emission and carbon tax on emissions, have been considered. The proposed MINLP has been validated using a randomly generated data set.

Keywords: green supply chain, carbon emission, mixed integer non-linear program, inventory shortage, carbon cap-and-trade

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Siddhartha Paul, Debabrata Das

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Closed-loop supply chain (CLSC) management focuses on integrating forward and reverse flow of material as well as information to maximize value creation over the entire life-cycle of a product. Bullwhip effect in supply chain management refers to the phenomenon where a small variation in customers’ demand results in larger variation of orders at the upstream levels of supply chain. Since the quality and quantity of products returned to the collection centers (as a part of reverse logistics process) are uncertain, bullwhip effect is inevitable in CLSC. Therefore, in the present study, first, through an extensive literature survey, we identify all the important factors related to forward as well as reverse supply chain which causes bullwhip effect in CLSC. Second, we develop a system dynamics model to study the interrelationship among the factors and their effect on the performance of overall CLSC. Finally, the results of the simulation study suggest that demand forecasting, lead times, information sharing, inventory and work in progress adjustment rate, supply shortages, batch ordering, price variations, erratic human behavior, parameter correcting, delivery time delays, return rate of used products, manufacturing and remanufacturing capacity constraints are the important factors which have a significant influence on system’s performance, specifically on bullwhip effect in a CLSC.

Keywords: bullwhip effect, closed-loop supply chain, system dynamics, variance ratio

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Authors: Ulrike Dowie, Ralph Grothmann

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Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

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Authors: Chaimongkol Limpianchob

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This work addresses the problem of production planning that arises in the production of aromatic coconuts from Samudsakhorn province in Thailand. The planning involves the forwarding of aromatic coconuts from the harvest areas to the factory, which is classified into two groups; self-owned areas and contracted areas, the decisions of aromatic coconuts flow in the plant, and addressing a question of which warehouse will be in use. The problem is formulated as a mixed-integer linear programming model within supply chain management framework. The objective function seeks to minimize the total cost including the harvesting, labor and inventory costs. Constraints on the system include the production activities in the company and demand requirements. Numerical results are presented to demonstrate the feasibility of coconuts supply chain model compared with base case.

Keywords: aromatic coconut, supply chain management, production planning, mixed-integer linear programming

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Authors: Ghaleb Y. Abbasi, Israa Abu Rumman

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This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.

Keywords: ARIMA models, sales demand forecasting, time series, R code

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Authors: Saeed Poormoaied

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Perishability and developing an intelligent control policy for perishable items are the major concerns of marketing managers in a supply chain. In this study, we address a two-echelon supply chain problem for perishable items with a single vendor and a single buyer. The buyer adopts an aged-based continuous review policy which works by taking both the stock level and the aging process of items into account. The vendor works under the warehouse framework, where its lot size is determined with respect to the batch size of the buyer. The model holds for a positive and fixed lead time for the buyer, and zero lead time for the vendor. The demand follows a Poisson process and any unmet demand is lost. We provide exact analytic expressions for the operational characteristics of the system by using the renewal reward theorem. Items have a fixed lifetime after which they become unusable and are disposed of from the buyer's system. The age of items starts when they are unpacked and ready for the consumption at the buyer. When items are held by the vendor, there is no aging process which results in no perishing at the vendor's site. The model is developed under the centralized framework, which takes the expected profit of both vendor and buyer into consideration. The goal is to determine the optimal policy parameters under the service level constraint at the retailer's site. A sensitivity analysis is performed to investigate the effect of the key input parameters on the expected profit and order quantity in the supply chain. The efficiency of the proposed age-based policy is also evaluated through a numerical study. Our results show that when the unit perishing cost is negligible, a significant cost saving is achieved.

Keywords: two-echelon supply chain, perishable items, age-based policy, renewal reward theorem

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Ethan Nikookar, Yalda Boroushaki, Larissa Statsenko, Jorge Ochoa Paniagua

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Given the serious impact that supply chain disruptions can have on a firm's bottom-line performance, both industry and academia are interested in supply chain resilience, a capability of the supply chain that enables it to cope with disruptions. To date, much of the research has focused on the antecedents of supply chain resilience. This line of research has suggested various firm-level capabilities that are associated with greater supply chain resilience. A consensus has emerged among researchers that supply chain flexibility holds the greatest potential to create resilience. Supply chain flexibility achieves resilience by creating readiness to respond to disruptions with little cost and time by means of reconfiguring supply chain resources to mitigate the impacts of the disruption. Decisions related to supply chain disruptions are made by supply chain managers; however, the role played by supply chain managers' reference networks has been overlooked in the supply chain resilience literature. This study aims to understand the impact of supply chain managers on their firms' supply chain resilience. Drawing on social capital theory and social network theory, this paper proposes a conceptual model to explore the role of supply chain managers in developing the resilience of supply chains. Our model posits that higher level of supply chain managers' embeddedness in their reference network is associated with increased resilience of their firms' supply chain. A reference network includes individuals from whom supply chain managers seek advice on supply chain related matters. The relationships between supply chain managers' embeddedness in reference network and supply chain resilience are mediated by supply chain flexibility.

Keywords: supply chain resilience, embeddedness, reference networks, social capitals

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Authors: Raja Kannusamy

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The research focuses on reducing food waste in the restaurant industry. A study has been conducted on the chain of retail restaurant outlets. It has been observed that the food wastages are due to the inefficient inventory management systems practiced in the restaurant outlets. The major food items which are wasted more in quantity are being selected across the retail chain outlets. A moving average forecasting method has been applied for the selected food items so that their future demand could be predicted accurately and food wastage could be avoided. It has been found that the moving average prediction method helps in predicting forecasts accurately. The demand values obtained from the moving average method have been compared to the actual demand values and are found to be similar with minimum variations. The inventory optimization technique helps in reducing food wastage in restaurant supply chain outlets.

Keywords: food wastage, restaurant supply chain, inventory optimisation, demand forecasting

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Authors: Qamar Iqbal

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Companies strive to improve their forecasting methods to predict the fluctuations in customer demand. These fluctuation and variation in demand affect the manufacturing operations and can limit a company’s ability to fulfill customer demand on time. Companies keep the inventory buffer and maintain the stocking levels to reduce the impact of demand variation. A mid-size company deals with thousands of stock keeping units (skus). It is neither easy and nor efficient to control and manage each sku. Inventory classification provides a tool to the management to increase their ability to support customer demand. The paper presents a framework that shows how inventory classification can play a role to increase supply chain responsiveness. A case study will be presented to further elaborate the method both for build-to-order and build-to-forecast manufacturing environments. Results will be compared that will show which manufacturing setting has advantage over another under different circumstances. The outcome of this study is very useful to the management because this will give them an insight on how inventory classification can be used to increase their ability to respond to changing customer needs.

Keywords: inventory classification, supply chain responsiveness, forecast, manufacturing environment

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Authors: Showkat Ahmad Bhat, M. S. Bhatt

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The study evaluates the ex-post impact of institutional credit on agricultural output. It first examines the key factors that influence the accessibility of institutional credit by farm households. For quantitative analysis both program participant and non-participant respondents were drawn and cross-sectional survey data were collected from 412 households in Pulwama District of Jammu & Kashmir (India). Propensity Score Matching Method was employed to analyze the impact of the institutional credit on agricultural output. Results show that institutional credit has a positive and significant impact on the agricultural output measured in terms of farm income and crop productivity. To estimate the accessibility of credit, an examination of both demand side and supply side factors were carried out. The demand for credit was measured with respect to respondents who applied for credit. Supply side credit allocation measured in terms of the proportion of ‘credit amount’ farmers obtained. Logit and Two-limit Tobit Regression Models were used to investigate the determinants that influence the accessibility of formal credit for Demand for and supply of credit respectively. The estimated results suggested that the demand for credit is positively and significantly affected by the factors such as: age of the household head, formal education, membership, cash crop grown, farm size and saving account. All the variables were found significantly increasing the household’s likelihood to demand for and supply of credit from banks. However, the impact of these factors varies considerably across the credit markets. Factors which were found negatively and significantly influencing the accessibility of credit were: ‘square of the age’, household assets and rate of interest. The credit constraints analysis suggested that square of the age; household assets and rate of interest were the three most important factors that increased the probability of being constrained. The study finally discusses these results in detail and draws some recommendations.

Keywords: institutional credit, agriculture, propensity score matching logit model, Tobit model

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Authors: Rahil Saeedi

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The imbalance in truck parking supply and demand can create important safety issues for truck drivers and the public. Research has shown that breaks at specific intervals can increase drivers’ alertness by reducing the monotony of the task. However, if fatigued truck drivers are unable to find a safe parking spot for rest, they may continue to drive or choose to park at remote and insecure areas or undesignated locations. All of these situations pose serious safety and security risks to truck drivers and other roadway users. This study uses 5-year truck crash data in Ohio to develop and test a framework for identifying crashes that happen as a result of imbalances in truck parking supply and demand. The societal impacts of these crashes are then interpreted as monetary values, calculated using the costs associated with various crash severity levels.

Keywords: truck parking, road safety, crash data, geofencing, driver fatigue, undesignated parking

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Authors: Renata Konadu

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In Ghana, electricity has become the main form of energy which all sectors of the economy rely on for their businesses. Therefore, as the economy grows, the demand and consumption of electricity also grow alongside due to the heavy dependence on it. However, since the supply of electricity has not increased to match the demand, there has been frequent power outages and load shedding affecting business performances. To solve this problem and advance policies to secure electricity in Ghana, it is imperative that those factors that cause consumption to increase be analysed by considering the three classes of consumers; residential, industrial and non-residential. The main argument, however, is that, export of electricity to other neighbouring countries should be included in the electricity consumption model and considered as one of the significant factors which can decrease or increase consumption. The author made use of multivariate time series data from 1980-2010 and econometric models such as Ordinary Least Squares (OLS) and Vector Error Correction Model. Findings show that GDP growth, urban population growth, electricity exports and industry value added to GDP were cointegrated. The results also showed that there is unidirectional causality from electricity export and GDP growth and Industry value added to GDP to electricity consumption in the long run. However, in the short run, there was found to be a directional causality among all the variables and electricity consumption. The results have useful implication for energy policy makers especially with regards to electricity consumption, demand, and supply.

Keywords: electricity consumption, energy policy, GDP growth, vector error correction model

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Authors: Ammatu Alhassan

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Quality healthcare delivery is a crucial indicator in assessing the overall developmental status of a country. There are many limitations in the Ghanaian healthcare supply chain due to the lack of studies about the correlation between quality health service and the healthcare supply chain. Patients who visit various healthcare providers face unpleasant experiences such as delays in the availability of their medications. In this study, an assessment of the quality of services provided to Ghanaian outpatients who visit public healthcare providers was investigated to establish its effect on the healthcare supply chain using a conceptual model. The Donabedian’s structure, process, and outcome theory for service quality evaluation were used to analyse 20 Ghanaian hospitals. The data obtained was tested using the structural equation model (SEM). The findings from this research will help us to improve the overall quality of the Ghanaian healthcare supply chain. The model which will be developed will help us to understand better the linkage between quality healthcare and the healthcare supply chain as well as serving as a reference tool for future healthcare research in Ghana.

Keywords: Ghana, healthcare, outpatients, supply chain

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Authors: Sameh S. Namnqani, Yaqoob Y. Abobakar, Ahmed M. Alsewehri, Khaled M. AlQethami

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The main objective of this research is to know the impact of the application of the electronic supply system on the performance of the supply department of health organizations. To reach this goal, the study adopted independent variables to measure the dependent variable (performance of the supply department), namely: integration with suppliers, integration with intermediaries and distributors and knowledge of supply size, inventory, and demand. The study used the descriptive method and was aided by the questionnaire tool that was distributed to a sample of workers in the Supply Chain Management Department of King Abdullah Medical City. After the statistical analysis, the results showed that: The 70 sample members strongly agree with the (electronic integration with suppliers) axis with a p-value of 0.001, especially with regard to the following: Opening formal and informal communication channels between management and suppliers (Mean 4.59) and exchanging information with suppliers with transparency and clarity (Mean 4.50). It also clarified that the sample members agree on the axis of (electronic integration with brokers and distributors) with a p-value of 0.001 and this is represented in the following elements: Exchange of information between management, brokers and distributors with transparency, clarity (Mean 4.18) , and finding a close cooperation relationship between management, brokers and distributors (Mean 4.13). The results also indicated that the respondents agreed to some extent on the axis (knowledge of the size of supply, stock, and demand) with a p-value of 0.001. It also indicated that the respondents strongly agree with the existence of a relationship between electronic procurement and (the performance of the procurement department in health organizations) with a p-value of 0.001, which is represented in the following: transparency and clarity in dealing with suppliers and intermediaries to prevent fraud and manipulation (Mean 4.50) and reduce the costs of supplying the needs of the health organization (Mean 4.50). From the results, the study recommended several recommendations, the most important of which are: that health organizations work to increase the level of information sharing between them and suppliers in order to achieve the implementation of electronic procurement in the supply management of health organizations. Attention to using electronic data interchange methods and using modern programs that make supply management able to exchange information with brokers and distributors to find out the volume of supply, inventory, and demand. To know the volume of supply, inventory, and demand, it recommended the application of scientific methods of supply for storage. Take advantage of information technology, for example, electronic data exchange techniques and documents, where it can help in contact with suppliers, brokers, and distributors, and know the volume of supply, inventory, and demand, which contributes to improving the performance of the supply department in health organizations.

Keywords: healthcare supply chain, performance, electronic system, ERP

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Authors: Sourour Ramzi, Claudia Sarrico

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Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

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Authors: Yuan-Jye Tseng, Yi-Shiuan Chen

Abstract:

The paper presented a sustainable design model for integrated evaluation of the design and supply chain of a product for the sustainable objectives. To design a product, there can be alternative ways to assign the detailed specifications to fulfill the same design objectives. In the design alternative cases, different material and manufacturing processes with various supply chain activities may be required for the production. Therefore, it is required to evaluate the different design cases based on the sustainable objectives. In this research, a closed-loop design model is developed by integrating the forward design model and reverse design model. From the supply chain point of view, the decisions in the forward design model are connected with the forward supply chain. The decisions in the reverse design model are connected with the reverse supply chain considering the sustainable objectives. The purpose of this research is to develop a mathematical model for analyzing the design cases by integrated evaluating the criteria in the closed-loop design and the closed-loop supply chain. The decision variables are built to represent the design cases of the forward design and reverse design. The cost parameters in a forward design include the costs of material and manufacturing processes. The cost parameters in a reverse design include the costs of recycling, disassembly, reusing, remanufacturing, and disposing. The mathematical model is formulated to minimize the total cost under the design constraints. In practical applications, the decisions of the mathematical model can be used for selecting a design case for the purpose of sustainable design of a product. An example product is demonstrated in the paper. The test result shows that the sustainable design model is useful for integrated evaluation of the design and the supply chain to achieve the sustainable objectives.

Keywords: closed-loop design, closed-loop supply chain, design evaluation, supply chain management, sustainable design model

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Authors: José M Martín-Moreno, Rafaela Pérez, Jesús Ruiz

Abstract:

In this paper we use a small open economy Dynamic Stochastic General Equilibrium Model (DSGE) for the Spanish economy to search for a deeper characterization of the determinants of Spain’s macroeconomic fluctuations throughout the period 1970-2008. In order to do this, we distinguish between tradable and non-tradable goods to take into account the fact that the presence of non-tradable goods in this economy is one of the largest in the world. We estimate a DSGE model with supply and demand shocks (sectorial productivity, public spending, international real interest rate and preferences) using Kalman Filter techniques. We find the following results. First of all, our variance decomposition analysis suggests that 1) the preference shock basically accounts for private consumption volatility, 2) the idiosyncratic productivity shock accounts for non-tradable output volatility, and 3) the sectorial productivity shock along with the international interest rate both greatly account for tradable output. Secondly, the model closely replicates the time path observed in the data for the Spanish economy and finally, the model captures the main cyclical qualitative features of this economy reasonably well.

Keywords: business cycle, DSGE models, Kalman filter estimation, small open economy

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Authors: T. Benazzouz, K. Auhmani

Abstract:

This paper presents a Hospital 4.0 Maturity Assessment Model based on the Industry 4.0 concepts. The self-assessment model defines current and target states of digital transformation by considering multiple aspects of a hospital and a healthcare supply chain. The developed model was validated and evaluated on real-life cases. The resulting model consisted of 5 domains: Technology, Strategy 4.0, Human resources 4.0 & Culture 4.0, Supply chain 4.0 management, and Patient journeys management. Each domain is further divided into several sub-domains, totally 34 sub-domains are identified, that reflect different facets of a hospital 4.0 mature organization.

Keywords: hospital 4.0, Industry 4.0, maturity assessment model, supply chain 4.0, patient

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Authors: Li Qiaoming

Abstract:

The outbreak of Coronavirus disease 2019 (COVID-19) in early 2020 brought new opportunities to the development of the digital creative industry in China. Based on the realistic foundation of the development of the digital creative industry in China, an analysis was conducted on the mechanism of action of the pandemic on this industry from both sides of supply and demand by sorting out its concept, connotation, and related theories. To be specific, the demand side experienced changes due to the changes in the consumption habits of residents, the sharp increase in gross domestic time (GDT), the satisfaction of the psychological needs of users, search for substitutes for offline consumption, and other factors. An analysis was carried out on the mechanism of action of the pandemic on the digital creative industry from the production link, supply subjects, product characteristics, and transmission link of the supply side. Then, a detailed discussion was held on the manifestation forms of the impact of the pandemic from the dimensions of time and space. Finally, this paper discussed the main development focuses of the digital creative industry in the post-pandemic era from the aspects of the government, industries, and enterprises.

Keywords: COVID-19, demand and supply relationship, digital creative industries, industry shocks

Procedia PDF Downloads 124