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This classroom activity helps students tie together the concepts of absorption costing for inventory, selling and administrative (SA) cost calculations, and sales price decisions. It shows students how all costs fit together and are used to make business and pricing decisions, synthesizing discrete sections of most managerial or cost accounting books into a complete process. The activity is designed to be run in one 75-minute class session using an Excel template that allows students to focus on business decisions and less on the mechanics of completing calculations. The seven segments of the activity have students calculate target cost, allocate items of overhead into production and service departments, calculate absorption product cost, allocate SA to the production departments, determine the full cost, evaluate product viability, and calculate target price. At the end of the activity, students better understand how all these cost items fit together in a manufacturing setting.

In this paper, the authors explore the consequences of showrooming and price matching strategy to combat showrooming under the consideration that brick-and-mortar (BM) stores and online retailers hold different costs.

The authors use a duopoly model to analyze the impact of showrooming behavior on competition between a BM store and an online retailer with different types of customers and different costs. Then, they consider the price matching strategy that a BM store could employ to combat showrooming and explore the effect of such a strategy.

Showrooming behavior is detrimental to the profit of the BM store, and the online retailer suffers a loss of their profit unless the relative cost of the BM store is high and only part of the customers exhibit showrooming behavior. As the fraction of customers who seek price matching increases, profits of both the BM store and the online retailer initially decrease and then may increase, even if there is no showrooming.

Unlike existing studies that ignore different costs between online and offline retailers, the authors set different costs between the BM store and the online retailer to consider the effects of showrooming and price matching strategy.

The purpose of this paper is to assess the long-run and short-run drivers of real house prices in Nigeria from 1991Q1 to 2020Q4.

Vector autoregression and cointegration tests were used to assess the key drivers of Nigeria’s real house prices in the long run and short run.

The empirical findings revealed that household disposable income is the most important determinant of house prices in Nigeria. House prices increased by 1.6% and 60.8% in response to a 1% increase in disposable income in the long run and short run, respectively, while real mortgage credits pushed up house prices by 5% and have no long-run effects, suggesting that most Nigerians depend on their money income rather than credits in securing a home. In addition, prices of oil sector products and real interest rates had negative and significant relationship with house prices, while positive correlations were found for real effective exchange rate and real housing investments regardless of the time horizon. The impact of construction costs and cement prices was also documented.

This is likely a pioneering study of its kind to focus on the determinants of real house prices in Nigeria. It is probably the first study, the best of the author’s knowledge, to empirically examine the impact of the oil sector on house prices in the country.

Social media networks make their services freely available to all users. Users pay for the service received with the time and attention taken by the advertisements. This chapter argues that social media platforms are a unique form of monopoly driven by “the more the merrier” effect (i.e., network effects) in users' consumption. These monopolies exercise market power, not by charging higher prices to users but by “tying” larger amounts of advertising to their content. Traditional antitrust instruments designed to address excessive pricing and reduced output by monopolies need to be reframed to tame the attention economy problems in the social media industry. This chapter discusses five antitrust instruments grouped in three categories: structural, behavioral, and market-based remedies. Market-based solutions are the least explored in the literature, despite being the most promising instruments to lower the attention costs imposed on users, while preserving the economies of scope in production and the network effects in consumption, and possibly maintaining free access to social media, as we know it today.

This paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.

The author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.

Long-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.

This research applies to markets that require some home equity contributions from buyers of housing services.

Stakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.

Existing literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

The purpose of this paper is to develop a systematic literature review on the sunk cost effect from consumers’ perspectives. By applying a comprehensive approach, this paper aims to synthesise and discuss the impact of financial and behavioural sunk costs on consumers’ decisions, judgements and behaviour before and after purchasing. This study also identifies potential research avenues to inspire further studies.

Following a search in the Scopus and Web of Science databases, a systematic literature review was conducted by identifying and analysing 56 peer-reviewed articles published between 1985 and 2022 (November). Descriptive and content analysis was implemented based on the selected papers to examine and synthesise the effect of sunk costs on consumers’ choices, evaluations and actions in a comprehensive approach; uncover research gaps; and recommend paths for future research.

The research results found in the literature are discussed according to five related themes: factors affecting the sunk cost effect; the impact of past investments on purchasing decisions; consumers’ post-purchasing evaluation, behaviour and choices; the mental amortisation of price; and the sunk cost effect on loyalty and switching.

The originality of this study lies in the comprehensive approach to the sunk cost effect from consumers’ perspectives. This review paper synthesises and discusses the research results found in the literature related to financial and behavioural sunk costs that can influence consumers’ decisions, judgements and behaviour before and after paying for a good or service.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.

The purpose of this study is to provide a unique competitive advantage to businesses in providing a wide range of products to prospective customers. To the best of the author’s knowledge, there is no study to discuss the impact of customer-centric retailing on total supply chain profit under price competition between organized and unorganized retailers.

This paper considers a supply chain comprising of organized and unorganized retailers and a single manufacturer. This paper proposes three mathematical models considering a customer-centric approach in a competitive environment. Stackelberg game is used to examine how members of the chain interact, and Nash equilibrium was used to find optimal strategies for players under different customer-centric approaches.

The results show that the total supply chain profit is higher when both organized and unorganized retailers use a customer-centric approach independently instead of collaborating process. The result, in addition, establishes that when the dissatisfying cost exceeds a certain threshold (1.5), the total profit is higher for the organized customer-centric effort model compared to the other two models.

The main contribution of the study is to examine the effect of customer-centric retailing, considering dissatisfying costs on supply chains profit and individual decision-making under price competition between organized retailers and unorganized retailers. The authors developed different mathematical models in the different customer-centric approach.

A challenge in implementing Universal Design (UD) is the perceived additional cost, which acts as a barrier to its widespread adoption. The few studies that have examined the cost for UD apply a theoretical research approach, failing to account for the unique design context that influences construction costs. This article presents a research methodology to calculate the UD cost in a realistic, context-dependent manner.

To address this gap, “Research-by-Design” is applied in a case study approach involving twelve cases from three typologies: secondary schools, town halls and small retail shops. Two scenarios are compared to the existing situation: (1) “renovating into a 100% inclusive building” and (2) “building fully inclusive right away”.

Although the methodology is time-consuming, it allows for a fair, realistic and detailed comparison between costs in different scenarios and cases. Findings show how financial implications are strongly related to its scale. Both “renovation” and “new build” scenarios involve costs, but these are considerably lower for the latter. “Circulation” and “Exterior stairs and ramps” are among the most expensive to renovate, but have almost no additional cost in the examined cases for the “new build scenario”.

The research methodology presented in this study is time-consuming, which may limit its feasibility for large-scale cost assessments in diverse contexts.

The research methodology proposed in this study provides valuable insights for architects, designers and stakeholders involved in the implementation of UD. It offers a realistic and context-dependent approach to assess the cost implications of UD, enabling informed decision-making during the design and construction phases.

By revealing the specific cost implications of UD in different building contexts, this study contributes to promoting greater accessibility and inclusion in the built environment.

The applied approach distinguishes this study for its ability to provide rich contextual information on actual cost implications for UD. By considering real cases and their unique design contexts, valuable insights are offered into the true costs of implementing UD in the built environment.

This paper aims to explore factors influencing apartment price volatility in the two biggest cities in Vietnam, Hanoi and Ho Chi Minh City.

The study uses the supply and demand approach and provides a literature review of previous studies to develop four main hypotheses using four determinants of apartment price volatility in Vietnam: gross domestic product (GDP), inflation rate, lending interest rate and construction cost. Subsequently, the Vector Error Correction Model (VECM) is used to analyze a monthly data sample of 117.

The research highlights the important role of construction costs in apartment price volatility in the two largest cities. Moreover, there are significant differences in how all four determinants affect apartment price volatility in the two cities. In addition, there is a long-run relationship between the determinants and apartment price volatility in both Hanoi and Ho Chi Minh City.

Limitations related to data transparency of the real estate industry in Vietnam lead to three main limitations of this paper, including: this paper only collects a sample of 117 valid monthly observations; apartment price volatility is calculated by changes in the apartment price index instead of apartment price standard deviation; and this paper is limited by only four determinants, those being GDP, inflation rate, lending interest rate and construction cost.

The study provides evidence of differences in how the above determinants affect apartment price volatility in Hanoi and Ho Chi Minh City, which helps investors and policymakers to make informed decisions relating to the real estate market in the two biggest cities in Vietnam.

This paper makes several recommendations to policymakers and investors in Vietnam to ensure a stable real estate market, contributing to the stability of the national economy.

This paper provides a new approach using VECM to analyze both long-run and short-run relationships between macroeconomic and sectoral independent variables and apartment price volatility in the two biggest cities in Vietnam.