scholarly journals Revenue Management In Manufacturing: A Research Landscape

2010 ◽  
Vol 8 (2) ◽  
Author(s):  
S. Hossein Cheraghi ◽  
Mohammad Dadashzadeh ◽  
Prakash Venkitachalam
Keyword(s):  
Revenue Management ◽  
Airline Industry ◽  
Past History ◽  
Management Strategies ◽  
Demand Forecasting ◽  
Customer Relationship ◽  
Management Systems ◽  
Manufacturing Companies ◽  
Product Availability ◽  
Sales Channels

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; mso-pagination: none;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Revenue management is the science of using past history and current levels of order activity to forecast demand as accurately as possible in order to set and update pricing and product availability decisions across various sales channels to maximize profitability. In much the same way that revenue management has transformed the airline industry in selling tickets for the same flight at markedly different rates based upon product restrictions, time to departure, and the number of unsold seats, many manufacturing companies have started exploring innovative revenue management strategies in an effort to improve their operations and profitability. These strategies employ sophisticated demand forecasting and optimization models that are based on research from many areas, including management science and economics, and that can take advantage of the vast amount of data available through customer relationship management systems in order to calibrate the models. In this paper, we present an overview of revenue management systems and provide an extensive survey of published research along a landscape delineated by three fundamental dimensions of capacity management, pricing, and market segmentation.</span></span></p>

Providing a Pattern to Evalute CRM Systems Based on EFQM Model in SMEs

2012 ◽  
Vol 463-464 ◽  
pp. 1141-1146 ◽  
Author(s):  
Pegah Reihanifard ◽  
Mansoor Aminilari ◽  
Reza Askari Moghadam ◽  
Davood Vahdat ◽  
Soroush Mozaffari
Keyword(s):  
Customer Relationship Management ◽  
Management Strategies ◽  
Sanitary Ware ◽  
Customer Relationships ◽  
Customer Relationship ◽  
Management Systems ◽  
Unified Approach ◽  
Efficient Management ◽  
Efqm Model

Today, companies put their customers at the center of all activities and revise their marketing and sales strategies based on IT[1]. The companies, regardless of type of activity, size and structure, need to establish efficient management systems to evaluate their customer relationship system and provide other organizational tools to determine, lead, manage, and evaluate management strategies[2]. The purpose of this paper is to present a pattern based on EFQM model which is studied systematically in small and medium industries in order to get proper and unified approach in customer relationships by considering having proper approaches, results of approaches, and evaluating and reviewing of criteria .In this research we concentrate on the case study of Golsar Fars sanitary ware company among SMEs companies of sanitary ware industry in Iran in order to investigate the qualitative aspects of manifestations and see how the proposed pattern can be used by experts experienced in customer relationship management to help them to coordinate their activities with continuous improvement of the organization.

scholarly journals Maximizing revenue in airline industry through air cargo operations

2021 ◽  
Vol 244 ◽  
pp. 08019
Author(s):  
Nisara Paethrangsi
Keyword(s):  
Competitive Advantage ◽  
Revenue Management ◽  
Airline Industry ◽  
Online Survey ◽  
Management Strategies ◽  
Capacity Management ◽  
Primary Data ◽  
Pricing Strategies ◽  
Air Cargo ◽  
The Impact

This research aims 1) to identify the impact of pricing strategies on airlines’ revenues, 2) to identify the impact of non-pricing strategies on airlines’ revenues, 3) to explore the significance of revenue management to airlines competitive advantage. The behavioural-demand based pricing, psychological pricing, capacity management and over contract booking strategies are determined as independent variables. A dependent variable is the competitive advantage, and a mediator is revenue management. Primary data was collected from an online survey of 500 airline industry and revenue management strategies personnel; there were only 424 completed questionnaires in return. Results show that larger competitive advantage is associated with non- pricing strategy which is the over contract booking and there is a positive relationship between the psychological pricing and competitive advantage, as compared to the behavioural-demand based pricing and capacity management based strategic approaches.

scholarly journals A Welfare Assessment of Revenue Management Systems

2020 ◽  
Vol 19 (1) ◽  
pp. 1-41
Author(s):  
Nicolas Dupuis ◽  
Marc Ivaldi ◽  
Jerome Pouyet
Keyword(s):  
Theoretical Model ◽  
Revenue Management ◽  
Consumer Preferences ◽  
Consumer Surplus ◽  
Capacity Constraints ◽  
Management Systems ◽  
Optimal Pricing ◽  
Pricing Strategies ◽  
Welfare Impact ◽  
Welfare Assessment

AbstractWe study the welfare impact of revenue management, a practice which is widely spread in the transport industry, but whose impact on consumer surplus remains unclear. We develop a theoretical model of revenue management allowing for heterogeneity in product characteristics, capacity constraints, consumer preferences, and probabilities of arrival. We also introduce dynamic competition between revenue managers. We solve this model computationally and recover the optimal pricing strategies. We find that revenue management is generally welfare enhancing as it raises the number of sales.

scholarly journals Automotive OEM Demand Forecasting: A Comparative Study of Forecasting Algorithms and Strategies

2021 ◽  
Vol 11 (15) ◽  
pp. 6787
Author(s):  
Jože M. Rožanec ◽  
Blaž Kažič ◽  
Maja Škrjanc ◽  
Blaž Fortuna ◽  
Dunja Mladenić
Keyword(s):  
Machine Learning ◽  
Automotive Industry ◽  
Demand Management ◽  
Demand Forecasting ◽  
Machine Learning Algorithms ◽  
Superior Performance ◽  
Forecast Errors ◽  
Manufacturing Companies ◽  
Case Scenario ◽  
Crucial Component

Demand forecasting is a crucial component of demand management, directly impacting manufacturing companies’ planning, revenues, and actors through the supply chain. We evaluate 21 baseline, statistical, and machine learning algorithms to forecast smooth and erratic demand on a real-world use case scenario. The products’ data were obtained from a European original equipment manufacturer targeting the global automotive industry market. Our research shows that global machine learning models achieve superior performance than local models. We show that forecast errors from global models can be constrained by pooling product data based on the past demand magnitude. We also propose a set of metrics and criteria for a comprehensive understanding of demand forecasting models’ performance.

Revenue management and price optimization techniques in the hotel sector

2018 ◽  
Vol 24 (6) ◽  
pp. 720-752 ◽  
Author(s):  
Aldric Vives ◽  
Marta Jacob ◽  
Marga Payeras
Keyword(s):  
Revenue Management ◽  
Airline Industry ◽  
New Technologies ◽  
Customer Segmentation ◽  
Optimization Techniques ◽  
Hotel Management ◽  
Price Optimization ◽  
Hotel Sector ◽  
Measurement Effects

Pricing and revenue management (RM) techniques have become a popular field of research in hotel management literature. The sector’s background framework and evolution and the widespread use of new technologies have allowed a customer-oriented approach to be taken to pricing and the development of RM tools, while also contributing to better processes in hotel management performance at individual hotel level. Thus, price optimization (PO) methods that seek to maximize hotel revenue are based on inventory scarcity, customer segmentation and pricing. In the hotel sector, as in the airline industry, different pricing policies have a greater impact than competition measurement effects. This is mainly as differentiation strategies and specific policies at hotels can reduce the pressure of a competitive environment. The main contributions of the article are the presentation, description and classification of the principal RM and PO techniques in hotel sector literature.

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