Product Mix Decisions Research Articles

Environmental regulation and firms' product mix: The role of firms' product-specific capabilities

Understanding how firms respond to environmental regulation through product-mix decisions is critical to assessing the broader impact of such policies. This paper contributes to the literature by incorporating intra-firm dynamics and examining how these interact with firms’ capabilities to adjust their product scope and mix in response to environmental regulations, which are influenced by the costs of these adjustments. The empirical evidence suggests that targeted firms reallocated resources away from pollution-intensive products, indicating the policy’s effectiveness. Moreover, the relationship between environmental regulations and firms’ product-mix decisions is contingent on their ability to adapt their portfolios. Lastly, firms with different ownership structures display varying capacities to develop and sustain particular products.

An integrated Optimization Model of Product Mix, Assortment Packing, and Distribution in A Fashion Footwear Company

Recognizing the paramount importance of operational effectiveness and resource management in supply chain management (SCM) of the fashion industry, this study addresses a specific challenge faced by a prominent Indonesian fashion footwear company. The inefficiency is due to repetitive sorting and packaging processes during product distribution, which significantly impact optimal production mixes and product distribution from the distribution center to the point of sale. A crucial aspect is also the optimization of the delivery route. To address these challenges and minimize the total cost of ownership, the study proposes an integrated optimization model. This model simultaneously determines the optimal production quantity, assortment packaging, and distribution channels, taking into account decision variables related to distribution in configuration boxes, overload and underload products, as well as production numbers that respond to store-specific demand fluctuations. A notable contribution of this research is the integration of product mix decisions into the assortment packaging and distribution model, which represents a novel approach. The optimal solution determined using the LINGO 18.0 software highlights the significant influence of product penalty costs and product demand parameters on the objective function, while shipping costs have no noticeable influence. By emphasizing the integration of product mix decisions into the optimization framework, this research contributes significantly to improving the understanding and practical application of efficient supply chain management in the fashion industry.

Network optimization for optimal product mix decisions in a graphite mining production process

PurposeThe purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.Design/methodology/approachThe network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.FindingsThe selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.Originality/valueThis study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.

Navigating pharmaceutical product decisions: A comprehensive review

Product management in the pharmaceutical industry is a complex and challenging role that involves overseeing the entire life cycle of a drug product, from development through commercialization and beyond. It requires a deep understanding of the regulatory environment, market dynamics, and patient needs, as well as strong leadership and management skills By classifying product decisions into these categories, businesses can prioritize their efforts and allocate resources effectively. Strategic decisions, for example, may require more resources and involve more stakeholders than operational decisions, but they can also have a greater impact on the success of the product. By making informed product line and product mix decisions, businesses can effectively meet customer needs and grow their market share. By using product portfolio analysis, businesses can make informed decisions about which products to invest in, which to divest or improve, and which new products or markets to pursue. This analysis helps businesses align their product offerings with their overall business strategy and maximize their profitability and growth potential.

Exploratory decision robustness analysis of the theory of constraints focusing process using system dynamics modeling

The classic P and Q problem is used to illustrate Throughput Accounting (TA) concepts proposed by the Theory of Constraints (TOC). Since the release of Throughput Accounting, several studies have been conducted, both to discuss it and to consider uncertainties. However, these uncertainties are included in isolation in each research. This limitation distances the analysis from the reality of companies, in which variations and uncertainties occur simultaneously. This study aims to verify whether decisions based on Throughput Accounting are robust when simultaneous variations occur, bringing the problem closer to the reality of companies. A System Dynamics model based on the P and Q problem was used, including simultaneous variability in different parameters. Finally, an analysis of the prevalent variables for decision-making was performed using Artificial Neural Networks. The results suggest robustness of decisions, even in systems with simultaneous variations. One contribution to the literature consists of the demonstration that the Throughput Accounting heuristic is robust in stochastic conditions, even though the original proposal was deterministic. Another contribution lies in the identification of the prevalent variables, so far unexplored by the literature. Finally, the robustness of Throughput Accounting to support product mix and constraint identification decisions in companies is evident in dynamic scenarios that feature variability.

Determining the optimal product mix in multiple constraints manufacturing environment: an application in the textile industry

Theory of constraints (TOC) is an approach to production planning and control by focusing on the constraints of an organization to increase throughput by effectively managing constraints. TOC approach has been applied in many sectors, and efficient results have been taken. One of the application areas of TOC is product mix decisions. Product mix decisions are important for multi-product manufacturing systems because they affect the performance measures of the companies. This study aims to present how TOC is applied to determine the optimum product mix in a multiple- constraint environment in the textile industry. To achieve this, we first select three basic products of a textile company and examine the production processes of these products from TOC perspective. Next, we perform a bottleneck process and identify three bottlenecks for the problem. Then, based on our bottleneck process results, we generate three scenarios. Upon assessing these scenarios, we determine the most appropriate product mix by implementing the TOC approach. Finally, we employ a goal programming approach to solve the product mix problem and compare its results with those obtained by the TOC.

A Study on Application of Linear Programming on Product Mix for Profit Maximization and Cost Optimization

Objectives: This research aims to sneak into the retailer\'s perception about that customer segment and plan a product mix accordingly. The focus is on small players in small towns not having deep pockets to synergize the product mix decisions effectively. Methods: The data used in this research paper is from Hatchers, a medium-sized enterprise with zero budget for software for product mix decisions. The data was collected through face-to-face interviews with ten representatives and five supervisors in compliance with the existing documents and existing datasheet obtained from the production department, which was slightly updated to make the final output. The data was for one season, i.e., April to March. The data was analyzed to study pre-Linear Programming and post-Linear Programing profits. Findings: This examination distinguishes the current asset usage level and the benefit of every period of one of the apparel producing organizations, utilizing a linear programming procedure. Actual consumption of resources (product wise) was calculated to evaluate profit post applying Linear Programing to see the wastage and cost. There was a 54% increase post LP compared to the product-wise resource utilization. Similarly, the profit using Linear programming was more than double as wastage and costing were minimum, and revenue was high. Novelty: The article focused on the simple basic principle of linear programming for identifying product mix using Excel(Solver). LINGO. The software solutions become costlier for small firms, whereas Excel is more accessible and cost-efficient. There is a gap in existing literature as previous research has not focused on this aspect for small business houses where adapting software solutions is challenging. Keywords: Linear Programming, Profit maximization, Product Mix, Production, cost optimization

Product Line Flexibility for Agile and Adaptable Operations

Firms increasingly need to manage uncertainty and become more agile and adaptable. This study considers how a multi‐product firm can use its product mix, resource capacity allocation, and pricing decisions to manage challenges such as structural economic shifts or changes in consumers' willingness‐to‐pay. Firms that seek to develop and use such a product line face a fundamental trade‐off. On the one hand, multiple products compete for the demand externally (i.e., cannibalization effects), as well as for the limited resource capacity internally. On the other hand, a multi‐product firm does have the ability to change the product mix and to adjust the production quantity and pricing of each product in order to manipulate supply and demand as conditions change. In this study, we demonstrate that a multi‐product firm can become more agile and adaptable under consumer purchasing behavior uncertainty by employing postponement in product mix, quantity, and pricing decisions, and by allocating capacities appropriately. In particular, we show that a firm can use its product line flexibility to make strategic adjustments after understanding the realized economic conditions, and to decide whether to follow a focus or segmentation strategy. We also extend the model to look at the value of resource flexibility and find that it has little or no benefit above and beyond the product line flexibility studied here.

Product mix decisions with complete shipment and multiple physical resources as constraints

Over the last three decades, the theory of constraints (TOCs) has emerged as a complete management philosophy. Fox extended the application of TOC to the product mix situations and suggested the theory of constraints heuristics (TOChs). This algorithm was applicable to single constraint situations only and later, Fredendall and Lea (1997) modified it to revised theory of constraints heuristics (RTOChs) for multiple constraint situations. Neither of these heuristics is applicable to the situations where complete shipment to different customers is an additional constraint over and above the physical constraints. In this paper, some modifications are suggested in RTOCh proposed by Fredendall and Lea (1997). By applying these modifications, the heuristics can be used in the complete shipment constraint situations. The working of this modified heuristics has been explained by taking two illustrative examples. By comparing the results obtained from the proposed heuristics with those obtained from the integer linear programming model, it has been proven that the heuristics give satisfactory results. Since the proposed heuristics provides the sequence of manufacturing, the effect of contingencies on actual output will be minimum. Ease of usage and better actual output are the advantages of proposed heuristic over integer linear programming.

Forty Years and Still Evolving: The Theory of Constraints

This manuscript presents a literature review of the Theory of Constraints. The literature is divided into three periods: the early (1980-1995), the expansion (1996-2014) and the past five years (2015-2019). The theory has been applied to production efficiency, supply chain management, cost accounting, product-mix decisions, and strategic decision-making. It has evolved into a more mature management philosophy and thinking process. The theory has become integrated with other related or competitive theories and has withstood the test of time as an effective and intuitive approach to thinking about a broad range of functional areas, problems, and methods of decision-making.

Financial Constraints and Product Market Decisions: The Role of Production Cycles

This paper studies how financial frictions affect product market decisions. As different products have different production cycles and generate cash-flow at different maturities, companies may adjust product mix in order to alleviate financial constraints. I use the wine sector in Portugal as a laboratory because product mix decisions can be identified and linked to cash-flow maturity. I exploit a banking regulatory shock which impacted negatively on credit availability, and I find that credit constrained firms change their product mix in response to the shock. Firms shift from long cash-flow maturity products to shorter ones. My results suggest that the adverse impact of financial constraints on product markets may be exacerbated with longer, less-flexible, production cycles.

A Study of Product Mix for Mobiles (With Special Reference to Airtel and BSNL)

The product mix of a company, which is generally defined as the total composite of products offered by a particular organization, consists of both product lines and individual products. A product line is a group of products within the product mix that are closely related, either because they function similarly, are sold to the same customer groups, are marketed through the same types of outlets, or fall within given price ranges. Product mix consistency refers to the functional closeness of the company's products. Increasing product mix width or depth or decreasing consistency may not necessarily be a step toward improvement. Product mix decisions should be based on company resources and market needs. The Boston Consulting Group matrix is an aid in product mix decision-making. It organizes the product mix in a matrix based on the market share and market growth rate of products. A product with a high market share and high market growth rate is called a star product.

Product Mix Decisions with Complete Shipment and Multiple Physical Resources as Constraints

Over the last three decades, the theory of constraints (TOCs) has emerged as a complete management philosophy. Fox extended the application of TOC to the product mix situations and suggested the theory of constraints heuristics (TOChs). This algorithm was applicable to single constraint situations only and later, Fredendall and Lea (1997) modified it to revised theory of constraints heuristics (RTOChs) for multiple constraint situations. Neither of these heuristics is applicable to the situations where complete shipment to different customers is an additional constraint over and above the physical constraints. In this paper, some modifications are suggested in RTOCh proposed by Fredendall and Lea (1997). By applying these modifications, the heuristics can be used in the complete shipment constraint situations. The working of this modified heuristics has been explained by taking two illustrative examples. By comparing the results obtained from the proposed heuristics with those obtained from the integer linear programming model, it has been proven that the heuristics give satisfactory results. Since the proposed heuristics provides the sequence of manufacturing, the effect of contingencies on actual output will be minimum. Ease of usage and better actual output are the advantages of proposed heuristic over integer linear programming.

Activity-Based Standard Costing Product-Mix Decision in the Future Digital Era: Green Recycling Steel-Scrap Material for Steel Industry

According to the advanced technologies of digitalization and automation, the interconnection with each individual object is created from data acquisitions into data feedback in the integrated platform of the Manufacturing Execution System (MES). MES automatically and immediately links various functional systems. The time of electronic production management is coming soon, and Activity-Based Standard Costing (ABSC) will be used in the new era. On the other hand, there are environmental protection issues; thus, the high-tech method of the Electric Arc Furnace (EAF) uses the complicated recycling material of steel-scrap, which hypothetically enhances product-mix decisions, as based on the ABSC theory, with a mathematical programming approach.

The effect of county non-attainment status on the product mix of plants in the pulp, paper, and paperboard industries

ABSTRACTThis paper examines the effect of ground-level ozone county non-attainment status on the product-mix decisions of plants in the pulp, paper, and paperboard industries. Plants located in non-attainment counties face more stringent standards than plants located in attainment counties. These standards may plausibly induce firms to reduce output of pollution-intensive products (products that lead to ozone-forming emissions of volatile organic compounds) or drop some of these products entirely. Using a difference-in-differences strategy, we find evidence that plants in non-attainment counties (treatment group) are more likely to drop pollution-intensive products relative to non-pollution-intensive products compared to plants in attainment counties (control group).

Green Production Planning and Control Model with ABC under Industry 4.0 for the Paper Industry

In the last 20 years, with the liberalization of the economy, and the trend of industrial globalization, people have gradually paid more attention to environmental protection. With the tremendous advances in information technology, enterprises facing such a severe impact on the business operations, business administrative models must be innovative and adaptable in order to survive and flourish. The paper industry is not only a highly polluting industry, but in the case of long-term overcapacity, the price of paper products is often suppressed, which lowers profitability. The purpose of this study, which is based on the production data of a paper company, is to pose a mathematical programming decision model which integrates green manufacturing technologies, activity-based costing (ABC), and the theory of constraint (TOC); this model should assist in preparing the best production plans, and achieve the optimal profitable product mix. In addition, this study also proposes that the most popular related technologies developed by Industry 4.0 be applied to production control in recent years in order to enhance production efficiency and quality. The findings of this study should contribute to the improvement of the competitiveness of the paper industry, and provide insights into the value of an integrated mathematical programming model applied for product-mix decision. At the same time, we have also applied the related technologies developed by Industry 4.0 to machine maintenance and quality control in manufacturing workshops. With its tremendous benefits, we can actively arouse the industry’s understanding of, and attention to, Industry 4.0, thereby increasing the interest in industrial 4.0-related technology investments.

Carbon Taxes and Carbon Right Costs Analysis for the Tire Industry

As enterprises are the major perpetrators of global climate change, concerns about global warming, climate change, and global greenhouse gas emissions continue to attract attention, and have become international concerns. The tire industry, which is a high-pollution, high-carbon emission industry, is facing pressure to reduce its carbon emissions. Thus, carbon prices and carbon trading have become issues of global importance. In order to solve this environmental problem, the purpose of this paper is to combine mathematical programming, Theory of Constraints (TOC), and Activity-Based Costing (ABC) to formulate the green production decision model with carbon taxes and carbon right costs, in order to achieve the optimal product mix decision under various constraints. This study proposes three different scenario models with carbon taxes and carbon right used to evaluate the effect on profit of changes in carbon tax rates.

Achieve a low carbon supply chain through product mix

PurposeIn the era of climate change, industrial organizations are under increasing pressure from consumers and regulators to reduce greenhouse gas emissions. The purpose of this paper is to examine the effectiveness of product mix as a strategy to deliver the low carbon supply chain under the cap-and-trade policy.Design/methodology/approachThe authors incorporate the cap-and-trade policy into the green product mix decision models by using game-theoretic approach and compare these decisions in a decentralized model and a centralized model, respectively. The research explores potential behavioral changes under the cap-and-trade in the context of a two-echelon supply chain.FindingsThe analysis results show that the channel structure has significant impact on both economic and environmental performances. An integrated supply chain generates more profits. In contrast, a decentralized supply chain has lower carbon emissions. The cap-and-trade policy makes a different impact on the economic and environmental performances of the supply chain. Balancing the trade-offs is critical to ensure the long-term sustainability.Originality/valueThe research offers many interesting observations with respect to the effect of product mix strategy on operational decisions and the trade-offs between costs and carbon emissions under the cap-and-trade policy. The insights derived from the analysis not only help firms to make important operational and strategic decisions to reduce carbon emissions while maintaining their economic competitiveness, but also make meaningful contribution to governments’ policy making for carbon emissions control.

The impact of cost allocation errors on price and product-mix decisions

We use simulations to examine the impact of cost allocation errors on pricing and product-mix decisions. We compare the imperfect cost allocation of cost systems based on heuristics to the ideal cost allocation of a benchmark model. First, we find that more complex cost systems are associated with substantially lower profit errors. Second, we decompose the profit error and find that production quantity errors are larger than product portfolio errors indicating that reducing product portfolio errors is less critical in designing cost systems. We also document that overproduction errors are larger than underproduction errors and errors from keeping unprofitable products are larger than errors from dropping profitable products suggesting that cost systems tend to underestimate full costs. Third, we find that profit errors increase for more complex cost systems as resource sharing levels rise, which is an interesting counter intuitive result.

Solving product mix problem in multiple constraints environment using goal programming

The theory of constraints is an approach to production planning and control that emphasizes on the constraints to increase throughput by effectively managing constraint resources. One application in theory of constraints is product mix decision. Product mix influences the performance measures in multi-product manufacturing system. This paper presents an alternative approach by using of goal programming to determine the product mix of the manufacturing system. The objective of paper is to provide a methodology in order to make product mix decision. Key point of the proposed methodology is considering decision maker idea to determine the weights of objective functions that are throughput and bottleneck exploitation. Therefore the weights of the objective functions are determined by the information get from decision maker. Through an example, inefficiency of theory of constraints in multiple bottleneck problems has been showed. Comparison of theory of constraints, linear programming and other methods to product mix problem has also discussed to show the advantages of the proposed method.