Optimal Product Line Design Research Articles

Optimal product line design strategy for green and non-green products with blockchain technology

Optimal product line design strategy for green and non-green products with blockchain technology

Multi-Device Consumption of Digital Goods: Optimal Product Line Design with Bundling

Multi-Device Consumption of Digital Goods: Optimal Product Line Design with Bundling

The optimal product-line design and incentive mechanism in a supply chain with customer environmental awareness

<p style='text-indent:20px;'>Due to the increasing awareness of sustainable development, the manufacturer's product-line design gets wide attention. Nowadays, the traditional manufacturer that produces non-green products is considering whether to introduce upgraded green products. This paper studies the manufacturer's optimal product-line design considering the quality difference between non-green and green products. Besides, our model also investigates the difference in unit production cost, green research and development (R&D) investment, and market segmentation. The results show that, from the manufacturer's perspective, producing green products is a better choice when non-green products are of low quality. In addition, the retailer is always inclined to sell green products. Further, the consumers' preference for non-green and green products is divided. And the consumer surplus under different product-line designs is analysed. Finally, two contracts are proposed and compared to encourage the manufacturer to produce green products.</p>

Product line extension with a green added product: Impacts of segmented consumer preference on supply chain improvement and consumer surplus

<p style='text-indent:20px;'>With the enhancement of environmental protection, more and more enterprises begin to develop green products. However, the high cost of green R&D leads to an increase of product price, which reduces the competitiveness of green products. In this paper, we model a supply chain which consists of one manufacturer and one retailer providing a primary product and a substitutable green added product in the market. In order to capture the impact of consumer behavior on the supply chain members' decision-making, we classify the market into two segments and assume that high-end green consumers have higher preferences for green products than ordinary consumers. Different to existing research, we assume ordinary consumers hold a positive but lower green preference compared to the green consumers. When analyzing the impacts of consumers' green preferences, we find that there exist specific boundaries of cost and market potential which define the optimal pricing strategy and product line design. Regarding profits, we find that when the green preferences of high-end and low-end consumers increase in the same proportion, the high-end market may not bring greater supply chain revenue. In particular, the marginal profit increase of the manufacturer is always greater than that of the retailer.</p>

Optimal product line design with reference price effects

A reference price is the price expectation of consumers for a product. When considering whether to buy a product, consumers usually compare its price with the reference price, which leads to psychological gain-loss utility affecting the consumers’ willingness to pay for the product. In this paper, we incorporate a reference price into the product line design problem and investigate the strategic implications of reference price effects for both the firm and consumers. We first study the optimal quality-price bundle design problem of a monopolistic firm and investigate the impact of reference price effects on the optimal quality and price decision when the number of products in the line is given. We show that as the importance of price comparison increases, the optimal range of qualities in the product line narrows. Specifically, the lowest quality in the product line is distorted upward, while the quality gap between adjacent products narrows. In particular, when consumers attach great importance to price comparison, the reference price effects may cause the firm to abandon discrimination among consumers and instead offer just a single product. We also investigate the optimal product variety setting problem considering a fixed setup cost incurred for each product in the choice set. Our numerical studies using synthetic and real-world data demonstrate that the demand model with reference price has better goodness of fit and prediction accuracy. The impact of neglecting reference price in the product line design problem is significant, potentially leading to substantial profit loss. Finally, we extend our work through general discussions of the model and through the dynamic pricing problem incorporating temporal reference price effects.

Optimal product line design using Tabu Search

Product design constitutes a critical process for a firm, which if not implemented effectively it may even question its viability. The optimal product line design is an NP-hard problem, where a company aims at designing a set of products that will optimize a specific objective. Whilst Tabu Search (TS) has effectively solved a large number of combinatorial optimization problems, it has not yet been evaluated in product design. In this paper we design and implement a TS algorithm, which is applied to both artificial and actual consumer-related data preferences for specific products. The algorithm’s performance is evaluated against previous approaches like Genetic Algorithm and Simulated Annealing. The results indicate that the proposed approach outperforms nine tested heuristics in terms of accuracy and efficiency. It also constitutes a more robust technique, and can be effectively generalized to larger problem sizes, which include higher number of products, attributes, or levels. Finally, a novel variant of TS capable of reducing execution time called Tabu Search Class Move, is introduced.

Clonal selection algorithms for optimal product line design: A comparative study

Product design constitutes a critical process for a firm to stay competitive. Whilst the biologically inspired Clonal Selection Algorithms (CSA) have been applied to efficiently solve several combinatorial optimization problems, they have not yet been tested for optimal product lines. By adopting a previous comparative analysis with real and simulated conjoint data, we adapt and compare in this context 23 CSA variants. Our comparison demonstrates the efficiency of specific cloning, selection and somatic hypermutation operators against other optimization algorithms, such as Simulated Annealing and Genetic Algorithm. To further investigate the robustness of each method to combinatorial size, we extend the previous paradigm to larger product lines and different optimization objectives. The consequent performance variation elucidates how each operator shifts the search focus of CSAs. Collectively, our study demonstrates the importance of a fine balance between global and local search in such combinatorial problems, and the ability of CSAs to achieve it.

Reducing channel inefficiency in product line design

It is well known that the optimal product line design in a manufacturer-retailer distribution channel is different from the optimal design achieved under a centralized channel. Channel inefficiencies are observed due to the potential misalignment of the manufacturer's and the retailer's segment targeting strategies. We show that this result in the literature is based on a crucial assumption that the product is comprised of only one attribute, and that one segment's preference structure dominates the other segment's preference structure. In this paper, we generalize the problem by considering a multiple-attribute product line design problem that includes the case of a non-dominating preference structure. Interestingly, we show that channel inefficiencies may become an issue in this non-dominating preference structure only when the market segments are significantly different in the overall part worth across the product attributes. We also show the potential of two important operations management concepts firms can use as an attempt to improve channel efficiency. Contrary to the predominant result in the literature on commonality in the centralized channel, we show that offering commonality in the decentralized channel may actually improve channel efficiency even in the absence of cost saving. Furthermore, firms can benefit from the implementation of decentralized product design where the retailer also takes part in designing product attributes. The overall part worth difference between the two segments appears to have a strong influence on the change in channel profits. These findings give rise to previously unrecognized opportunities for firms to redesign their product lines.

Product line design with vertical and horizontal consumer heterogeneity: the effect of distribution channel structure on the optimal quality and customization levels

Purpose The purpose of this study is to analyze the problem of optimal product line design in marketing channels where consumers are heterogeneous in both horizontal and vertical dimensions. Design/methodology/approach This paper develops a model to evaluate when it is preferable for a firm to extend the product line in a vertical or horizontal direction. Consumers are modeled as being vertically heterogeneous with respect to their valuation of quality and horizontally heterogeneous with respect to their preference on the esthetic component of the product. These model characteristics allow us to consider a broader set of product line extension strategies. By considering both a vertically integrated channel and a decentralized channel, this study investigates how channel structure influences optimal product line design. The problem with supplemental numerical analyses is mathematically analyzed. Findings The analysis shows that a horizontal product line extension strategy that offers the customized product can be used as an alternative to a vertical product line extension strategy. If the fixed cost is not too high, offering the customized product with low quality may be preferred to the quality-based segmentation strategy. Furthermore, the analysis shows that the channel structure is influential as the preference for the horizontal product line extension strategy is more pronounced in the decentralized channel than in the centralized channel. Research limitations/implications The analysis presented in this paper is limited by the consideration of full market coverage. Further research is needed to see how the results can be generalized to the case with partial market coverage. Practical implications The analysis suggests that a firm may consider product customization as part of its product line strategy. Information regarding market characteristics and channel structure is important when deciding on the optimal product line design. Originality/value The model reflects a more realistic marketing strategy and channel structure than previous studies that typically consider product line extension in only one direction and focus on the centralized distribution channel. Combining the standard product line extension and customization strategies also represents an important contribution to the literature. These extensions produce interesting new results and insights into a firm’s optimal product line design strategy.

Fuzzy self-tuning differential evolution for optimal product line design

Designing a successful product line is a critical decision for a firm to stay competitive. By offering a line of products, the manufacturer can maximize profits or market share through satisfying more consumers than a single product would. The optimal Product Line Design (PLD) problem is classified as NP-hard. This paper proposes a Fuzzy Self-Tuning Differential Evolution (FSTDE) for PLD, which exploits Fuzzy Logic to automatically calculate the parameters independently for each solution during the optimization, thus resulting to a settings-free version of DE. The proposed method is compared to the most successful mutation strategies of the algorithm as well as previous approaches to the PLD problem, like Genetic Algorithm and Simulated Annealing, using both actual and artificial data of consumer preferences. The comparison results demonstrate that FSTDE is an attractive alternative approach to the PLD problem.

Product line design and quality differentiation for green and non-green products in a supply chain

Motivated by the real practices in the circular economy, this paper aims to identify optimal product line design for green and non-green products in terms of quality differentiation. We develop a price and quality driven consumer choice model in a two-echelon supply chain through using a game-theoretical approach. Our study shows that no matter how high or low the product quality difference is, when the consumers’ willingness to pay (WTP) for responsibility is relatively low, a single product line strategy will be prioritised over a two-product line strategy; whereas when the consumers’ WTP for responsibility is relatively high, a two-product line strategy is more desirable. Moreover, we find that enhancing product quality could increase consumer welfare and reduce environmental impact. Only when green and non-green product quality difference is large enough, designing and selling green products is beneficial to consumers, brings the slightest pressure on the environment, and generates the highest social welfare. Furthermore, we extend the model by introducing a simplified contract and find that a simplified contract is not able to increase the manufacturer's profit, but may increase the retailer's profit and consumer surplus as well as generate better performance in environmental protection and social welfare.

Balancing product differentiation and cost saving in the presence of consumer deliberation

AbstractThis paper investigates the manufacturer's optimal product line design under different production strategies when customers with different preference structures (dominating or nondominating) need to incur the deliberation cost to uncover customers' valuations of product quality. We characterize the optimal price, quality, and profit under different production strategies and preference structures. Our results demonstrate that the optimal product line under both production strategies is threshold‐controlled, and there exists a deliberation cost threshold, below which the manufacturer provides efficient quality for high‐valuation customers and distorts the quality of low‐end products, while above such a threshold, the manufacturer increases the quality dispersion between high‐end and low‐end products. We also find that the adoption of commonality will increase the manufacturer's profit only if the cost‐saving effect is relatively significant. Contrary to the existing literature, we finally reveal that commonality can reduce cannibalization in the nondominating preference structure scenario if the deliberation cost is low and the cost‐saving effect is strong or if the deliberation cost is sufficiently high.

Store Brand Quality and Retailer’s Product Line Design

This study analyzes a retailer’s store brand quality decision in vertically differentiated product categories. We analyze a game theoretic model composed of one or two national brand manufacturers and a retailer, who strategically chooses the quality level(s) of its store brand(s) relative to the well-established national brand position(s) to maximize its category profit. Our analysis reveals that the nature of a retailer’s store brand quality positioning is quite different from the manufacturer’s national brand positioning decision, and that the best position for a store brand is not “as close to a national brand as possible” as previous studies suggest. Instead, the optimal quality position of each store brand is remarkably sensitive to the distribution of consumers’ willingness-to-pay. In particular, the relative proportions of quality sensitive consumers and price sensitive consumers determine the balance of three key strategic forces — the market expansion force, the retail margin force, and the consumer profitability force, leading to different optimal product line designs for store brands across different category environments. Interestingly, against multiple incumbent national brands, the retailer’s optimal product line design includes a store brand positioned at the highest quality level in the category only if most consumers are moderately quality conscious. We also analyze the implications of national brands’ brand equity for retailers’ store brand strategy.

Selling a Product Line Through a Retailer When Demand Is Stochastic: Analysis of Price-Only Contracts

Problem description: In practice, many consumer products are produced and stocked in product lines rather than in single product variants. The issue is that manufacturers and retailers often do not agree on the product line length (i.e., the number of variants included in the product line). The focus of this study is to understand how product line length and stocking quantities depend on how demand risk is contractually allocated. Academic/practical relevance: Our model combines assortment and stocking decisions in the presence of stochastic demand; previous models could address either assortment or stocking issues, but not necessarily both. Methodology: We present a game-theoretic model of a bilateral supply chain in which a manufacturer (he) sells up to two differentiated products through a retailer (she). He decides which products to produce, their wholesale prices, and how to allocate demand risk. We theorize that he can either retain the risk (by adopting a pull contract) or that he can pass it onto the retailer (by adopting a push contract). She responds by choosing assortment, quantities, and retail prices. By solving the model, we develop a descriptive theory that clarifies his incentive to expand his product offering and to reallocate demand risk within the supply chain. Results: Depending on the level of product differentiation, we identify three regions. When product differentiation is either low (commodities) or high (specialized products), the contract choice affects order quantities but not assortment. In these regions, the manufacturer’s contract choice can be explained by looking at elasticity of wholesale demand. For products with some differentiation, the manufacturer’s contract choice affects both order quantities and assortment. In this region, the manufacturer’s contract choice can be explained by looking at the additive effect of demand elasticity and sales expansion from the extended product line net of cannibalization. Managerial implications: Our paper can be seen as a first step toward developing a link between optimal product line design and optimal risk allocation in a bilateral supply chain.

Redesigning product lines in a period of economic crisis: a hybrid simulated annealing algorithm with crossover

The optimal product line design is an NP-hard optimization problem in marketing that involves a number of decisions, such as product line length and configuration. Simulated annealing constitutes the best performing approach so far, but with extremely large running times. In the current study simulated annealing is hybridized with an evolutionary algorithm to improve its search efficiency and alleviate its performance dependence on the selection of the parameters related to its cooling schedule. The presented approach outperforms genetic algorithms and classic simulated annealing, through the use of crossover as a neighborhood operator, along with the restricted tournament selection as the replacement strategy of the evolutionary algorithm’s population. Moreover, the paper describes the way that the proposed hybrid metaheuristic can be used for redesigning a firm’s product line. The issue of redesigning product lines becomes even more important in periods of economic crisis, as firms must adapt their offerings to new evolving patterns of consumer buying behavior and reduced levels of consumer’s purchasing power. The applicability of the proposed approach is illustrated through the case of the 2008 automotive industry crisis, by showing how the North American car manufacturers could have redesigned their lines on time, based on the configuration of the competitive products in the market as well as the new customer preferences emerged during the economic recession.

Does channel decentralization lead to low quality product lines?

Purpose – The purpose of this study is to analyze the problem of optimal product line design in marketing channels. Design/methodology/approach – This paper develops a game theoretic model, in which a firm markets a line of a limited number of products at different quality levels to serve a market composed of multiple consumer segments. The consumer segments are modeled as clusters of somewhat heterogeneous consumers as typically observed in the real world. These model characteristics allow us to consider a broader set of targeting strategies such as sub-segmentation and partial cannibalization which have not been considered previously. By considering both a vertically integrated channel and a decentralized channel, we investigate how channel structure influences optimal product line design. We analyze the model mathematically with supplemental numerical analyses. Findings – Our analysis shows that “quality distortion” in product line design is not limited to the low-end product, as previously reported, but can happen to the high-end product. The direction of these quality distortions may be downward or upward, leading to either increased or decreased differentiation between the two products. Furthermore, channel decentralization makes it more likely for the firm to strategically choose upward partial cannibalization or sub-segmentation. Consequently, contrary to previous studies, we demonstrate that there exist conditions under which channel decentralization leads to higher product quality. Originality/value – Our model reflects a more realistic market environment and a firm’s practical constraints than previous studies, which typically assume perfect homogeneity within each segment and/or the feasibility of offering an infinite number of products. This extension produces interesting new results and insights that provide more practical implications for a firm’s optimal product line design strategy.

Consumer Deliberation and Product Line Design

This paper studies optimal product line design when consumers need to incur costly deliberation to uncover their valuations for quality. To induce deliberation, a firm must maintain quality dispersion and cut the price of the high-end product so that consumers are motivated to deliberate in the hope that high-end consumption fits their needs. To prevent deliberation, the firm may have to offer downgraded quality at a low price so that an impulsive purchase will not appear too wasteful. Whether the firm should induce deliberation depends on how much surplus it creates by aligning the supply of quality with heterogeneous demand for quality and how much surplus it captures during this process. Interestingly, equilibrium firm profit, consumer surplus, and social welfare can all increase with the cost of deliberation. We extend the model to accommodate consumers' heterogeneous prior beliefs of their valuations for quality. We also discuss how market research could benefit from taking into account the endogeneity of consumer deliberation.

An approach to competitive product line design using conjoint data

In today’s highly competitive environment, where market oriented firms aim to maximize profits through customer satisfaction, there is an increasing need to design a product line, rather than a single product. The main goal of designing a profit maximizing product line is to target the ‘right product’ to the ‘right customer’. Although conjoint analysis has turned out to be one of the most widely used techniques for product line design, it falls to explicitly consider retaliatory reactions from competitors. In this paper, we propose a new conjoint-based approach to competitive new product line design, employing the Nash equilibrium concept. The optimal product line design problem for each firm is formulated as a nonlinear integer programming problem. In the absence of a closed-form solution, to compute the Nash equilibrium and to determine the optimal product line, we propose a two-phase procedure: a sequential iterative procedure in the first phase, and backward induction in the second. To solve the optimization problem in each of the iterations of the sequential procedure, we used the branch-and-bound method. The proposed approach is illustrated under several scenarios of competition using previously published conjoint data.

Enhancing marketing with engineering: Optimal product line design for heterogeneous markets

Successful product line design and development often require a balance of technical and market tradeoffs. Quantitative methods for optimizing product attribute levels using preference elicitation (e.g., conjoint) data are useful for many product types. However, products with substantial engineering content involve critical tradeoffs in the ability to achieve those desired attribute levels. Technical tradeoffs in product design must be made with an eye toward market consequences, particularly when heterogeneous market preferences make differentiation and strategic positioning critical to capturing a range of market segments and avoiding cannibalization. We present a unified methodology for product line optimization that coordinates positioning and design models to achieve realizable firm-level optima. The approach overcomes several shortcomings of prior product line optimization models by incorporating a general Bayesian account of consumer preference heterogeneity, managing attributes over a continuous domain to alleviate issues of combinatorial complexity, and avoiding solutions that are impossible to realize. The method is demonstrated for a line of dial-readout scales, using physical models and conjoint-based consumer choice data. The results show that the optimal number of products in the line is not necessarily equal to the number of market segments, that an optimal single product for a heterogeneous market differs from that for a homogeneous one, and that the representational form for consumer heterogeneity has a substantial impact on the design and profitability of the resulting optimal product line — even for the design of a single product. The method is managerially valuable because it yields product line solutions efficiently, accounting for marketing-based preference heterogeneity as well as engineering-based constraints with which product attributes can be realized.

Leadtime-Variety Tradeoff in Product Differentiation

The literature on mass customization generally focuses on the tradeoff between higher revenues from better matching customer preferences with product specifications, and higher costs of offering a broader—possibly fully customized—product line. Less well understood is the tradeoff between the increased ability to precisely meet customer preferences and the increased leadtime from order placement to delivery often associated with customized products. In this paper, we use a locational customer choice model to formulate a firm's integrated product line design problem that involves variety, leadtime (or inventory), and pricing decisions. We propose a dynamic programming based solution procedure that amounts to solving a shortest path problem on an acyclic network, and derive some structural results on the optimal product line design. We find that unimodal preferences generally result in hybrid product lines, with standard products clustering around the mode and custom products covering the tails, in contrast with the all-custom or all-standard product lines that are optimal under uniform preferences. We also numerically examine how the firm should adjust its leadtime and variety in response to changes in parameters such as customer dispersion and operational scale. We find that the tradeoff between leadtime and variety is sometimes nonintuitive and complex.