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Grocery retailers have access to detailed data on consumer purchases within their own chains. Previous research has used across-chain scanner panel data to develop optimal price cuts targeted to individual households but whether such a targeting strategy will work with only within-chain data is unknown. The purpose of this research is to address this specific question.

The authors use scanner panel data from multiple categories to create across-chain and within-chain purchase histories for the same consumers. They then estimate models of purchase decisions on the two datasets and compare their performance.

Within-chain data fares significantly worse on both fit and prediction criteria. Retailers' upside to customizing is minimal compared to those reported for manufacturers. Finally, customized prices based on the within-chain model significantly underperform the promise of across-chain data.

Store choice is not modelled. Research also needs to be replicated in other contexts. The authors conclude that limited purchase histories may not yield accurate enough estimates of marketing mix responsiveness, and that across-chain purchase histories are essential for effective targeted price cuts.

Loyalty card data may be useful for other purposes, like experimenting with segment-specific discounts, but its value in customizing prices at individual level is limited without adding other sources of information.

Previous research on price customization has been based almost exclusively on across-store data. However, retailers only have access to their own chain-specific data. This is the first study to comprehensively compare price customization based on within- and across-chain purchase data and show that the upside potential for price customization based on the former information set is quite limited.

The constantly changing prices, promotions, and packaging options have made decision making more complex for consumers of packaged goods. The purpose of this paper is to explore how price and promotions influence consumer propensity to buy a certain package size.

Scanner panel data for shelf-stable salad dressing obtained from Information Resources Inc. were used to compute the proportion of large packages bought, the relative price paid for large packages, propensity to use various types of promotions, and a behavioral covariate for each household. Data of over 5,600 households were analyzed using a multiple regression analysis for hypothesis testing.

The positive nature of relationship between the relative price of large packages and the proportion of large packages bought demonstrates the suboptimal nature of consumer decision making. The inefficiency is partially attributable to the abundance of promotions, to consumers’ lack of price awareness, and to the use of heuristics by consumers. Also, consumers who are prone to use promotions such as displays and temporary price reductions tend to purchase larger packages. They are more likely to buy impulsively and base their decisions on heuristics. In contrast, consumers who are influenced by featured price cuts and who utilize coupons tend to purchase smaller packages.

Data were obtained from grocery stores; only a single product category was studied.

Offer coupons and advertise featured price cuts on small packages to increase the sales of smaller packages. To move large packages successfully, retailers should rely more on in-store displays and temporary price reductions.

The impact of price and promotions on package size propensity has never been investigated. This study is also one of the few that uses a household-level analysis based on observable purchase data for consumer packaged goods.

This paper presents an empirical study on store brand demand and its determinants. A two‐stage model is considered, in which the consumer decides whether to buy store brands, as well as how to allocate category expenditure between retail and manufacturer brands. The first stage identifies the segment of store brand customers and the second level determines customer demand. The model incorporates consumer characteristics and examines their effects in the light of behavioural data. Discrete and continuous outcomes flow from the same preference structure and are determined by consumer characteristics. The results provide insights into explanatory factors and useful implications for brand management. Extensions of the present work are also discussed.

The purpose of this paper is to examine economic debates over the conception of barriers to entry and speculates which definitions can be applicable to the telecommunications industry, more specifically, the residential broadband market. Also, it seeks to clarify the various industrial factors that could prevent or mar the success of entry into the residential telecommunications market and it also seeks to introduce an analytical framework that can be adopted for evaluating the barriers to entry.

The approach takes the form of a literature review.

It clarifies the various industrial factors that could prevent or mar the success of entry into the residential telecommunications market and introduces an analytical framework that can be adopted for evaluating the barriers to entry.

Although market entry barriers are crucial industrial factors that influence the market share and profit of firms already in the market, very little research has specifically examined barriers in the telecommunications and broadband industry.

The theoretical basis for this case is a focus on vertical integration, first-mover advantage and competitive dynamics. Vertical integration is based on Williamson’s (1979) theory of transaction-cost economics as it relates to vertical integration; the discussion on first-mover advantage is built off of Suarez and Lanzolla’s (2005) dynamics of first-mover advantage; and the analyzes on competitive dynamics derives from the MacMillan et al. (1985) early empirical tests of interfirm rivalry dynamics.

The authors conducted extensive research using the following sources: IBISWorld, MergentOnline and academic journals, trade magazines and websites. Additionally, the authors successfully piloted the case on more than 350 undergraduate students enrolled in a business and corporate strategy course.

Peloton used vertical integration to control the creation of its own software, bikes, exercise classes and retail outlets. In doing so, Peloton was one of the first companies in the industry to have near full control of the production process (Gross and Caisman, 2019). Due to this integration, Peloton was one of the fitness equipment industry leaders. However, Peloton’s high level of vertical integration coupled with rapid growth led to lackluster profitability. Given the rise in popularity of in-home exercise equipment, Peloton had room to continue its growth, but the question remained whether it was strategically positioned to do so.

This case is best taught in undergraduate and graduate strategy courses. For undergraduate courses, it could be incorporated into lessons on competitive dynamics, internal analysis and first-mover advantage and strategic positioning. For graduate courses, it could be incorporated into lessons on vertical integration and delving more in-depth into the long-term sustainability of having a first-mover advantage.

To achieve a full understanding of the role of marketing from plan to profit requires a knowledge of the basic building blocks. This textbook introduces the key concepts in the art or science of marketing to practising managers. Understanding your customers and consumers, the 4 Ps (Product, Place, Price and Promotion) provides the basic tools for effective marketing. Deploying your resources and informing your managerial decision making is dealt with in Unit VII introducing marketing intelligence, competition, budgeting and organisational issues. The logical conclusion of this effort is achieving sales and the particular techniques involved are explored in the final section.

Affordable homeownership is a policy that is often accorded a great deal of policy attention by governments of many countries. This paper aims to examine the market implications of setting a housing price to income ratio target for a market segment by the government.

The policy requires active intervention by the government with regard to the targeted sector. The paper uses a simple model of the housing market with a homeownership affordability target to derive the market implications of such targets.

In the presence of uncertainty and resource constraints, the objective of homeownership affordability is achieved for the targeted group at the expense of greater volatility in residential construction activity. When the size of the targeted sector is significant in size, there are spillover price and crowding out effects on the non‐targeted housing market segment.

This results in political pressure on the government to expand homeownership affordability targets to increasing segments of the population. Housing price to income ratios tend to be fairly constant over time and across targeted groups, the housing supply is relatively price inelastic and the income elasticity of housing demand is less than one.

The Singapore government intervenes extensively in the housing sector to ensure homeownership affordability, with a resulting homeownership rate of 91 percent for the resident population. The above hypotheses regarding the implications of setting housing price to income ratio targets are tested using the Singapore housing market.

This paper adds to the literature by analyzing the market implications of setting homeownership affordability targets in the context of a targeted housing segment.

The main objective in writing this paper and conducting this research is to enhance the productivity in manufacturing operations by making them cost effective.

This paper presents a target‐costing system and model developed for the turning operation and it has a user interface designed in Microsoft Visual Basic® with a database developed by using Microsoft Access®. An algorithm is developed to apply the concepts of target‐costing that selects the machining parameters and then determines the machining cost. A geometric programming model (Gopalakrishnan and Al‐Khayyal) was used in the development of this system.

The research determined that target‐costing models can be developed for the manufacturing industry and can be implemented in realistic manufacturing environment. The research also showcased the utility of the target‐costing model in terms of the underlying detailed system level parameters.

The research focuses on one manufacturing process but can be extended to other manufacturing processes and business cost and profit centers for providing overall and enhanced benefits at the corporate levels.

The research details the development of a model that has been validated using practical shop floor data, hence implying its application in a wide variety of situations.

The original value of the paper lies in identifying the critical parameters and modeling approach towards target‐costing.

The assignment of targets to instruments in developing countries cannot satisfactorily follow any simple universal rule. Which approach is appropriate is influenced by whether the economy is dominated by primary exports, by the importance of the domestic bond market and bank credit, by the extent of existing restriction in foreign exchange and financial markets, by the presence or absence of persistent high inflation, and by the existence or non‐existence of an active international market in the country's currency. Eighteen observations and maxims on stabilisation policy are tentatively drawn (pp. 64–8) from the material reviewed, and the maxims are partly summarised (pp. 69–71) in a schematic assignment, with variations, of targets to instruments.