With the advancement of technologies, industries tries to adopt the advantages of the technology. Customers are busy in their daily life, and the online platform is the best option for retail, ...whereas traditional customers still prefer to visit the retail shop. Few customers choose the product online but buy it offline or
vice-versa
. Owing to all those circumstances, current study focuses on an intelligent dual channel (online-to-offline) strategy in industry to arrange the optimal services for customers. The selling price of the product vary with different channel, which helps to determine the demand of product for entire supply chain. Two important factors, backorder and lead-time are examined precisely through marginal value which helps to arrange optimal service and calculate the exact profit. The profit for a centralized and decentralized case are computed for both the players. Some propositions are developed to prove the global optimality. Numerical results prove that a centralized case provides 7.77% better profit than a decentralized case due to bonding between the players.
Resumo
The overall objective of this study was to analyze the results of the implementation of the Costing System in Sales Price (CSSP), using a cost matrix that considers the distribution of ...indirect costs and fixed expenses in seven small and medium-sized industrial companies, located in “Serra Gaúcha” (RS), through a Reference Apportionment (RA) that parameterizes the revenue with the market value of each product. Data were collected in the year 2015. This study also contextualizes and provides a cost structure in a format similar to the Income Statement (IS), using, as main information source, the accounting data, financial records, analysis of accounting books and production data which were combined with semi-structured interviews. To sum up, this research has established the Costing System in Sales Price (CSSP) and the Reference Apportionment (RA) as criteria for distribution of indirect costs, reinforcing the idea that the
sales price should follow the market logic.
Palavras-chave: Reference Apportionment. Sales price. Costing system.
•The study investigates the impact of higher Fed funds rates on mortgage lending of U.S. banks.•Results indicate that higher Fed funds rates cannot control mortgage lending of U.S. banks during high ...inflation rate and high house sales prices in absence of reserve requirements.•Instead, higher Fed funds rates seem to further increase both the mortgage loan to total loan ratio and the absolute amount of mortgage loans – which is the opposite of what the Fed intends to reach with a higher Fed funds rate.•Against the backdrop that the Fed cannot effectively control mortgage lending, the recent sharp decline in house prices has the potential to unleash a new financial crisis.
The U.S. is facing higher inflation since December 2020 along with higher house prices. After a sharp increase, house prices have started to decline very recently even more drastically – reminding us of the global financial crisis 2007–08. Rather late, from December 2021 onwards, the Fed started to increase the Fed funds rate. However, it is unclear whether the Fed funds rate can control bank lending activities – especially, mortgage lending. Surprisingly, our results suggest that the Fed funds rate fails to control mortgage lending during high inflation and high house prices in the absence of bank reserve requirements.
Academicians and practitioners have focused a lot of attention on the separate issues of pricing and inventory control in a competitive setting. However, integrating these choices in a competitive ...environment has received scant attention for deteriorating inventory systems from academics despite being crucial to practitioners. From this perspective, our research focuses on designing a supply chain model with inventory coordination to reflect time systems with improved accuracy and optimal control systems. In this research, we develop a two-layer supply chain model consisting of one manufacturer and one retailer incorporating the inventory classification of the retailer. Price-sensitive market demand and two-parameter time-varying Weibull distribution deterioration have been assumed to develop the mathematical model. First, a collective decision on price and inventory control of a deteriorating product has been evaluated in a duopoly environment. Secondly, to explore the decentralized scenario, we have proposed the NSGA-II algorithm to solve the bi-objective programming problem of the two-layer supply chain. The paper aims to explore product collaborative pricing policies and the inventory decision of the deteriorating item in two-layer supply chain coordination. Finally, numerical research is conducted to execute the centralized supply chain and NSGA-II application in a decentralized supply chain. The research findings can provide valuable insights for members of the two-layer supply chain to make optimal product pricing and inventory scheduling decisions.
PurposeConsidering the network externalities of online selling, this paper builds three different online direct selling models: manufacturer direct selling (MN model), network platform direct selling ...(NN model) and retailer direct selling (RN model). The optimal advertising and pricing decision and corporate profits under each selling model are investigated.Design/methodology/approachCombining the characteristics of online direct selling, this paper formulates direct selling models that are dominated by different companies as Stackelberg game models. Numerical analyses are carried out, along with the comparison of the equilibrium solutions for each model.FindingsThe authors' research shows that increasing network externalities is conducive to the development of enterprises. The network platform's profit is the lowest in the RN model and the highest in the NN one. The comparison of manufacturers' profits between the MN model and the NN model primarily depends on consumers' sensitivities for sales price and advertising promotion level. The manufacturer does not benefit from the RN model due to the lowest efficiency.Originality/valueCoupled with three different online direct selling models and detailed analyses of the optimal solutions, this study has enriched the theoretical foundation of online direct selling. Moreover, this study extends the research of network externalities to the field of e-commerce, revealing the network externalities' influence on the decision-making of the e-supply chain.
•There is at least 50% more ammonia being included inside the aviary than outside.•The chicken used in the production process influences the results of eco-efficiency.•Greatest impact is on the ...agricultural stage of the production of grains-feed animal.•Absent national inventories for unitary primary animal and plant production processes.•Taxes used for third party remuneration or capital were less than equity.
The consumption of poultry meat as a source of animal protein has been increasing worldwide, especially in emerging countries' economies. Due to the growing demand for this protein, we seek to evaluate the eco-efficiency of poultry production systems, namely positive pressure, dark house, and organic systems, in the South region of Brazil. To achieve the proposed objective, two methods were used: life cycle assessment and economic value added, considering the functional unit of one kg of live chicken ready for slaughter, specifically from the cradle to farm gate. The results show that most of the environmental impacts are from the production of grains for the manufacture of animal feed and, consequently, from the electric energy consumed by the equipment of the aviaries. Conventional systems show negative results for economic value added/kg, evidencing the destruction of the producers' economic value, that is, the capital invested is not remunerated proportionally to the risk assumed in the activity, with environmental impacts similar as dark house systems. Poultry produced in organic systems showed the best economic performance (economic value added/kg). However, they cause a slightly greater environmental impact than other systems. In order to minimize uncertainties regarding the results obtained, a sensitivity analysis and Monte Carlo simulation were performed, identifying net operating revenue and invested capital as the variables with the greatest and least impacts on the value of economic value added/kg in all types of production systems analyzed.
The expanding customer consciousness of ecological sustainability has motivated supply chain members to participate in green activities. In this paper, the coordination issue of a dual-channel supply ...chain is studied under consideration of the greening level of the items. The two-stage supply chain consists of a manufacturer and a retailer. The manufacturer is responsible for keeping the item’s greening level and sells the products through two channels (a) a direct online channel and (b) a traditional retail channel. Market demand depends on the selling price and greening level of the item. Furthermore, the pricing and greening strategies of the channel members are discussed under the centralized and decentralized scenarios. Compared to the centralized scenario, optimum pricing at the retail channel is higher in the decentralized scenario while the greening level of products is low. The outcomes exhibit that the profit of the supply chain in a decentralized scenario decreases compared to the centralized scenario. To enhance the supply chain profit, we have developed two coordinate mechanisms of the decentralized scenario with a cost-sharing contract and a profit-sharing contract. Our analysis shows that the profit-sharing contract can realize the coordination, but the cost-sharing contract cannot. A numerical example has been demonstrated to quantify the effectiveness of different contracts, and the model’s finding is demonstrated.
The article analyses a multi-channel, multi-echelon supply chain model for single items comprising the manufacturer, distributors and retailers as the members of the chain. The profit function of ...each individual member is formulated based on the demand rate of the customers at each stage as a linear function of sales prices. In decentralised and centralised systems, the proposed model suggests the optimal pricing strategies under two-part tariff and bargaining process. A numerical example is illustrated to justify the proposed model. Sensitivity analysis of key parameters is carried out for feasibility of the model.
Submarket segmentation outlines an essential prerequisite for monitoring housing market and formulating urban housing policies. Although examining segmentation based on a posteriori knowledge rather ...than a priori knowledge becomes the mainstream, it follows a data-driven approach without a solid theoretical foundation and involves subjective interventions. Additionally, earlier studies have overwhelmingly examined the dynamics of sales submarkets while overlooking those of rental submarkets. This paper demonstrates a novel approach to segmenting the housing market by integrating the hedonic model, geographically and temporally weighted regression (GTWR), and machine learning, and further applies it to unpack the dynamics of sales submarkets and rental submarkets from 2018 to 2020 in Shanghai, China. More specifically, using the home-fixed panel data of housing sales prices and rental prices for each residential quarter, we first establish a series of hedonic models using GTWR and then aggregate the residential quarters into a number of submarkets using an affinity propagation clustering algorithm based on the produced spatiotemporally explicit coefficients. To validate the identified submarkets, we compare them to the static submarkets delineated by the real estate industry with respect to the performances of hedonic models. Finally, the Jaccard and Rand indices are applied to compare the magnitude of spatiotemporal dynamics of sales submarkets and rental submarkets. Results show that hedonic models based on the identified submarkets through our proposed method perform better than those based on the static submarkets delineated by the real estate industry. We also discover that the submarkets present a complex change over three years, especially in central urban areas. The dynamics between sales submarkets and rental submarkets are of significant differences. In particular, rental submarkets are more stable than sales submarkets. Our approach provides a practical and efficient tool for urban housing market segmentation. Our study highlights that differentiated policies should be formulated for regulating sales submarkets and rental submarkets in order to enhance housing affordability.
•A novel approach to housing market segmentation is proposed that integrates the hedonic model, GTWR and machine learning.•The identified submarkets are validated to be more robust than those delineated by real estate industry.•Submarkets present complex temporal changes over time.•Rental submarkets are more stable than sales submarkets.•Differentiated policies are required for regulating sales submarkets and rental submarkets.
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