Online Learning and Optimization for Revenue Management Problems with Add-on Discounts

We study in this paper a revenue-management problem with add-on discounts. The problem is motivated by the practice in the video game industry by which a retailer offers discounts on selected supportive products (e.g., video games) to customers who have also purchased the core products (e.g., video game consoles). We formulate this problem as an optimization problem to determine the prices of different products and the selection of products for add-on discounts. In the base model, we focus on an independent demand structure. To overcome the computational challenge of this optimization problem, we propose an efficient fully polynomial-time approximation scheme (FPTAS) algorithm that solves the problem approximately to any desired accuracy. Moreover, we consider the problem in the setting in which the retailer has no prior knowledge of the demand functions of different products. To solve this joint learning and optimization problem, we propose an upper confidence bound–based learning algorithm that uses the FPTAS optimization algorithm as a subroutine. We show that our learning algorithm can converge to the optimal algorithm that has access to the true demand functions, and the convergence rate is tight up to a certain logarithmic term. We further show that these results for the independent demand model can be extended to multinomial logit choice models. In addition, we conduct numerical experiments with the real-world transaction data we collect from a popular video gaming brand’s online store on Tmall.com. The experiment results illustrate our learning algorithm’s robust performance and fast convergence in various scenarios. We also compare our algorithm with the optimal policy that does not use any add-on discount. The comparison results show the advantages of using the add-on discount strategy in practice. This paper was accepted by J. George Shanthikumar, big data analytics.

Integration of tree source and sink activities.

Tree crop modeling could be instrumental in facilitating integration of numerous aspects of the development, growth and physiology of fruit tree crops and provide a valuable tool for testing concepts for understanding how fruit trees work, if it could be achieved. This chapter presents a synopsis of how modeling of fruit trees was approached. It focuses on the development of a mechanistic, compartmental model of mature peach tree carbon partitioning over a growing season. The model was termed a compartmental model because carbohydrates were only distributed to the collective compartments of fruits, leaves, stems and large branches, and the trunk according to their relative demand functions as the season progressed. Roots were only given carbohydrates when the demands of all of the other organs were fulfilled. This model demonstrated that carbohydrate partitioning in trees could be modeled without deterministic, empirically derived, partitioning coefficients and was useful for indicating periods of the growing season when calculated photosynthetic assimilation was not adequate to supply calculated carbohydrate demands of growing organs. The development of the described model is so complex that the modeling work will never be fully completed. However, to demonstrate the utility of this modeling approach, it was decided to develop an L-Almond model using the same approach.

The relationship between logistics and trade marketing in FMCG companies

Logistics and marketing are usually concerned with satisfying the needs and wants of customers, respectively through their supply and demand functions in the marketplace. In order for organizations to successfully provide more value to customers, it is necessary to combine logistics and marketing functions. Globally, the importance of transport in every nation's economy is increasing every year, as its level of development has a major impact on the competitiveness of a nation's economy. The relevance of the study is that the relationship between logistics and marketing is crucial to serve FMCG market customers. A successful relationship between logistics and marketing, represents a source of competitive advantage to provide better customer service while keeping the cost of goods low. This paper presents the theoretical basis for the logistics organization of Kazakhstan's FMCG market. The current situation of domestic FMCG trade is presented and the contribution to the country's GDP is described. The main aspects and functions of logistics and marketing for finding joint areas and conflicts are also given. The principles of market supply chain management are described, the integration of logistics and marketing is analyzed using the concepts of trade marketing in distribution systems of modern companies as an example, and the logistics approach to trade and marketing activities is described. An important outcome of the analysis is the definition of marketing logistics as a source of competitive advantage, together with a description of digital marketing logistics technologies and the risks of their application.

The income elasticity of lottery revisited: a worldwide perspective

Using panel data information from The WLA Global Lottery Data Compendium this paper estimates aggregate demand functions for lottery tickets in order to examine variation in the income elasticity of lottery tickets worldwide. The analysis uses a panel data quantile regression approach. The estimated elasticities are compared across income quartiles and world regions. The results provide evidence that a significant variation in the income elasticities across both geographic areas and the income distribution exists. Also, a clear heterogeneity in the incidence of lottery expenditures is observed. Overall, it is found that lottery is a normal good.

THE IMPACT OF ZAKAT ON MONEY DEMAND FUNCTION: EVIDENCE FROM MUZAKKI IN INDONESIA

Most research in the Islamic economy on the money demand have employed the Keynesian approach, while in this research money demand functions are derived from a microeconomic approach. Thus, the aim of this study is to test and analyze some of the key factors in Islamic money demand model with the microeconomics-based approach, and then, in accordance with Islamic principles, chooses muzakki as the best sample. The data source for this study is 200 muzakki in Java, with a period of 2020. Structural Equation Modelling (SEM) is adopted to examine the relationship between the seven constructs, i.e., zakat, PLS rate, state, regulation, goods and services, conspicuous consumption, and money demand. The systemic relationship between the structures indicates that the integrated model of demand for money has a strong zakat relationship, while reliability and validity have been established. Zakat plays a key role in applying the established paradigm of demand for money in relation to goods and services. Zakat significantly affects both goods and services as well as models of money demand. This proposed new model equation is intended to help each household economic actor increase the demand for philanthropic money. As many muzakki are spread throughout Indonesia, it is expected that the welfare of the poor and the low-income society will gradually improve and, finally, the distribution of income in Indonesia will be on an equal footing.

Input Demand and Output Supply Elasticities of Coarse Cereals in India: A Translog Profit and Sure Approach

Aims: The aim was to estimate the output supply and input demand elasticities of maize, jowar and bajra production, using the restricted normalised translog profit function, for the major producing states of India (Andhra Pradesh, Maharashtra and Rajasthan). Study Design: A stratified multi-stage random sampling design was adopted for carrying out the sampling. Place and Duration of Study: The study pertains to cross sectional plot level data for the period 2013-14 and 2017-18. The study is based on secondary data, collected from Directorate of Economics & Statistics, Ministry of Agriculture, Government of India. Methodology: For the present studied crops (maize, jowar and bajra), those states were selected which covered maximum area, i.e, 85% of the total area under the cultivation. Socio-economic data of farmers such as age, sex, level of education, occupation, size of landholding were collected. The translog profit function approach was used as the econometric technique to estimate output supply, and input demand functions. Labour, fertiliser and seeds are taken as variable inputs. Statistical software STATA version 16 was used for the analysis. Results: The results suggest that the changes in market prices of inputs and output significantly affect the farmers’ profits, crop produce supply and the use of resources in the cultivation of these crops. The supply elasticities of maize, jowar and bajra with respect to its own prices are positive and statistically significant indicating that increase in support prices can boost the supply of these nutri-grains and farmers profits. Labour demand for these crops in the country is elastic and significant to its own price. Conclusion: During both the periods, 2013-14 (typical monsoon year) and 2017-18 (drought year), the elasticities derived are statistically robust as almost all of them carried compatible signs and in line with the theory. Promoting these crops can contribute to labour absorption.

On the Risks of Using the Sequential Product-Level SSNIP Approach to Identify Relevant Antitrust Markets‡

In a recent influential paper Coate et al. (2021) have criticized the sequential product-level approach to market definition in merger review. They argue that a simultaneous market-level approach to critical loss is more appropriate than a product-level critical loss analysis, because under certain plausible demand scenarios (nonlinear demand functions) the latter could yield the wrong answer on market definition—i.e., excessively broad or narrow markets. We extend their analysis by showing that a sequential product-level approach actually leads to an excessively narrow market definition when the typical nonlinear demand functions used in merger analysis are employed.

Registers or surveys – does the type of microdata matter for empirical analyses of consumption behavior?

In recent years it has come into focus whether longitudinal microdata on consumption derived from administrative registers can constitute an attractive supplement to survey data. This paper explores the consistency between register-imputed and survey-based consumption figures at the household level for Denmark over the period 2002–15. Moreover, it presents estimated consumer demand functions based on the two types of microdata for the same households. The paper finds no significant differences between the marginal propensities to consume out of income estimated on the basis of the two data sources. Furthermore, it demonstrates a close match between total private consumption in the national-accounts statistics and the register-based consumption microdata aggregated over all households.