Product Portfolio Management Research Articles

How loud is consumer voice in product deletion decisions? Retail analytic insights

This study examines the role of online consumer reviews in product deletion decisions. Building upon product portfolio management theory and the signaling theory, we integrate consumer voice, represented by online consumer review behavior into organizational voice—strategic product deletion decision-making. We empirically evaluated the relationship between online consumer reviews and organizational product deletion decisions using text mining and logistic regression models. The results indicate consumer online review characteristics are significant factors for product deletion decisions. Findings suggest that products with lower review attribute ratings, or those with textual review content less pertinent to the core performance attributes, are more likely to be deleted. The linguistic retail analytic characteristics of online reviews also provide insights for product deletion decisions. Products with reviews having higher subjectivity, shorter length, and lower readability are more likely to be deleted. Pre-purchase consumer voice—the perceived helpfulness or unhelpfulness of online reviews also impacts product deletion decisions. A general conclusion is that online reviews can provide important retail analytics for smarter retail operations planning at the strategic and tactical levels when it comes to product planning and portfolio management through product deletion.

Application of data mining technique for customer purchase behavior via Extended RFM model with focus on BCG matrix from a data set of online retailing

This study explores the integration of data mining, customer relationship management (CRM), and strategic management to enhance the understanding of customer behavior and drive revenue growth. The main goal is the use of application of data mining techniques in customer analytics, focusing on the Extended RFM (Recency, Frequency, Monetary Value and count day) model within the context of online retailing. The Extended RFM model enhances traditional RFM analysis by incorporating customer demographics and psychographics to segment customers more effectively based on their purchasing patterns. The study further investigates the integration of the BCG (Boston Consulting Group) matrix with the Extended RFM model to provide a strategic view of customer purchase behavior in product portfolio management. By analyzing online retail customer data, this research identifies distinct customer segments and their preferences, which can inform targeted marketing strategies and personalized customer experiences. The integration of the BCG matrix allows for a nuanced understanding of which segments are inclined to purchase from different categories such as “stars” or “cash cows,” enabling businesses to align marketing efforts with customer tendencies. The findings suggest that leveraging the Extended RFM model in conjunction with the BCG matrix can lead to increased customer satisfaction, loyalty, and informed decision-making for product development and resource allocation, thereby driving growth in the competitive online retail sector. The findings are expected to contribute to the field of Infrastructure Finance by providing actionable insights for firms to refine their strategic policies in CRM.

Disruptive Factors in Product Portfolio Management: An Exploratory Study in B2B Manufacturing for Sustainable Transition

Business-to-business (B2B) manufacturing companies are increasingly confronted with transformative trends such as sustainability, digitalization, and servitization. These trends are changing how product portfolios are developed, and how value contributions are assessed, and therefore have disruptive potential. Dealing with these disruptive factors in Product Portfolio Management (PPM) is a largely unexplored topic. This study presents an empirical-qualitative exploration that contributes significantly to the field. The aim is to clarify the extent to which disruptive factors influence the evaluation and shaping of the product portfolio in B2B manufacturing companies. The Gioia method was used to evaluate 21 semi-structured interviews with experts from leading B2B manufacturing companies. Eight overarching challenges in PPM resulting from disruptive factors were identified. Based on the eight overarching challenges and their associated causal relationships, two aggregated dimensions of action were derived: (1) increasing speed and flexibility by using generative artificial intelligence (AI) in a defined PPM process and (2) adjusting the product portfolio evaluation to consider various strategic drivers. These two dimensions of action call for future research to overcome the disruptive factors in PPM.

The Effect of Macro-indicators, Profit Sharing on Mudharabah Deposits: Evidence from Indonesia

This research seeks to ascertain how interest rates, GDP, and profit-sharing relate to mudharabah savings in Islamic commercial banks. This study employs a quantitative research design and measures its findings using a panel data regression approach. Sharia commercial banks that registered with the Financial Services Authority (OJK) between 2016 and 2020 make up the research population. There were 180 observations in total in this study because the sample was chosen using the purposive sampling method and included a total of nine Sharia commercial banks. This study employed secondary data, specifically quarterly financial reports. The study's findings demonstrate that mudharabah deposits benefit from interest rates. Mudharabah benefits from the amount of profit sharing. deposits. Mudharabah deposits are positively impacted by the GDP. It is well recognized that the amount of mudharabah savings is influenced by GDP, a measure of people's income. The managerial ramifications of how GDP, profit-sharing, and interest rates affect mudharabah deposits can be very significant in a financial context. Interest rates, income uncertainty, and risk management minutes. Profit sharing, compliance with Sharia principles, and product development and portfolio management.

Strategies to Improve Portfolio Management of New Products

Overview: This article presents the findings of an Innovation Research Interchange (IRI) study on practices and outcomes in new product (NP) portfolio management. Given the substantial investments in R&D and the consequential impact on the business’s future, effective portfolio management decisions play a pivotal role in achieving business success. Portfolio decisions influence R&D productivity, the success rates of new products, and several other performance metrics related to NPD.

Commercial and Technical Productization for Design Reuse in Engineer-to-Order Business

In the engineer-to-order (ETO) business, companies provide customer value by customizing the products according to the customers’ needs in a project-like manner. As a result, the number of individual product designs tends to proliferate, causing challenges in company operations, and product portfolio and product lifecycle management. In addition, if the company's product offering is not well productized, using the ETO model may further lead to poor understanding of the offering, deficient reuse of previous designs, and challenges in sales and making offers. A qualitative multiple case study was conducted to analyze the productization challenges of four ETO companies. On the basis of the challenges and the previous literature, a generic model for commercial and technical productization in ETO business was constructed and further tested in the companies. The model utilizes the logic of commercial and technical product structures. The product structure logic is linked to four different scales of product development processes to address different types of customer requests based on the complexity of the modification that the request necessitates. The model may support clarifying the product offerings of ETO companies to improve their design reuse, sales, and making offers. Further, the ETO order-related decision-making can be linked to product portfolio management targets and company strategy.

Curating the elegance of Chikankari: a case of Ada

Learning outcomes Upon completion of the case study, the students will be able to conceptualize the importance of brand differentiation; suggest the implications of brand differentiation in the context of the traditional Chikan art form; examine the aspect of a brand’s product portfolio management; and critically analyse the competitive advantages of the brand using the VRIO framework. Case overview/synopsis The Chikankari art form gained worldwide recognition. In fact, it also received a geographical indication (GI) tag which is important for international branding. The case is centred around an entrepreneur, Mr. Vinod Punjabi, who redefined the essence of the existing Chikan art form by value addition in terms of intricate designs, patterns and exclusivity. He founded the brand Ada in 2015 aimed at preserving the traditional art form while curating elegance and exclusivity in its product portfolio. The case outlined Punjabi’s journey. The protagonist carefully analysed the open and unorganized Chikankari market and adopted the strategy of brand differentiation to stand apart from the competitors. Punjabi’s daughter, the chief operations officer of Ada, described the aspects. The journey was arduous, but over the years, Ada emerged as a successful name in the Chikankari market. The brand’s intent of becoming synonymous with Chikankari was successful owing to its authentic and exclusive hand-crafted products in the competitive environment of machine-made replicas. Furthermore, the brand also consistently worked on the aesthetic appearance of its store to attract a wide range of customers. Punjabi ensured that the brand was an amalgamation of all the essential elements for its survival in the long run. Complexity academic level The case is aimed for students pursuing bachelor’s and master’s degrees in business administration/diploma in management, marketing and entrepreneurship. Furthermore, it will assist the management trainees in gaining valuable insights. Supplementary materials Teaching notes are available for educators only. Subject code CSS 8: Marketing.

UNCERTAINTY MANAGEMENT IN PRODUCT DEVELOPMENT PORTFOLIOS: THE IMPACT OF GLOBAL SUSTAINABILITY AGENDAS

AbstractIncreased focus on sustainability significantly impacts product development portfolio management in organizations. This paper focuses on the significant unaccommodated uncertainty caused by the green transition for current mid- and long-term portfolio management processes. These uncertainties arise in areas such as the regulatory environment, market demands, and technical capabilities. This paper makes four contributions: First, current product portfolio management literature is mostly employing deterministic practices. Uncertainties are incompletely addressed, and current methods fail to address the deep uncertainties of the green transition. Second, building a literature-based conceptual framework of the sources of uncertainty in 6 areas: Business Models, Technology, Regulation and Legislation, Finance and Insurance, Market and Consumer, and Organizational Context. Third, preliminary empirical evidence supports the usefulness of our model for product development portfolio management. Fourth, concluding with a suggested empirical research agenda to develop a deeper understanding of challenges towards method and theory development to support the green transition on the portfolio management level.

Ramp-up planning for alternative product portfolios in a multi-product-multi-stage production system

The importance of production ramp-ups has increased owing to dynamic changes in endogenous and exogenous business environments. There is consequently a need to develop approaches for product portfolio and capacity management for the production ramp-up when multiple candidate products are considered to be launched. In this paper, we develop an optimisation model for the ramp-up planning of multiple candidate products that share common resources. We consider the product launch schedule with the problem of capacity planning to realise a profitable production system when demand increases after a product is introduced in the market. We suggest four different types of ramp-up strategies for managing multiple candidate products according to the available capacity. Numerical analyses show that a sophisticated ramp-up strategy aligned with the company’s capacity management supports realising a profitable production ramp-up. We expect that the model developed in this paper supports decision-making related to successful ramp-up production.

Concrete manufacturing with a low CO2 footprint

The object of the research is the current state of the climate action strategy for cement and concrete production, including possible levers for reducing CO2 emissions. It has been determined that the main source of carbon dioxide emissions per tonne of Portland cement, and subsequently per cubic metre of concrete, is the decarbonization of calcium carbonate, the main raw material component of Portland cement clinker. It also involves the combustion of fossil fuels, which are necessary for the decarbonization and firing of raw materials. Therefore, Portland cement with a reduced content of Portland cement clinker is considered as a solution for concrete manufacturing with a low CO2 footprint. Additionally, the potential of Ukraine in the development of a sustainable Portland cement clinker production approach based on using alternative fuels and alternative raw materials, which will positively affect the total amount of CO2 per ton of clinker, was evaluated. Improved quality performance of cement has been identified as a key direction in product portfolio management to promote cements with a lower clinker factor by increasing the content of active mineral additives. It is shown that the production of concrete with increased strength and durability requirements based on cements saturated with active mineral additives is an important task. Since active mineral additives have different origins, not all of them available for use in cement production exhibit hydraulic properties inherent in Portland cement clinker. Was investigated that «Complex Performance Testing System» (CPTS) as the main test method for evaluating the quality parameters of Portland cement with a reduced clinker factor in accordance with specific applications. This customer-oriented approach opens up the possibility of producing low-CO2 concrete. It has been shown that using the CPTS method, a reduction in the total amount of cement per cubic meter of concrete can be achieved, given the specified parameters of the concrete mix, which has a direct impact on the total amount of CO2/m3.

Decentralised or centralised management of data and products: influence on revenue-generating processes

Products, services, product data, information systems, and business processes are very closely related issues. The products must be in control, and the product data and product portfolio suit the business to ensure process performance. Customers' demanding complex solutions necessitate considerations over decentralised or centralised management of data and products. Decisions on product and data management affect vital processes. Thematic analysis is applied to company product data management (PDM) and product portfolio management (PPM) practices to reflect the centralisation vs. decentralisation perspective and identify preconditions for centralisation. It appears that the volume of standard products, pressures to comply with regulations and standards, and product and process maturity influence whether a company benefits more from centralisation or decentralisation. Value is provided by revealing challenges of decentralised PDM and PPM, and by clarifying preconditions for centralisation. The findings indicate the order of priority for centralisation in terms of aligning processes and harmonising data.

Prototyping a data-driven customer segmentation utilizing machine usage data for product portfolio management

For companies to have well-fitting product portfolios, product portfolio management requires profound knowledge of its customers. Data-driven decision processes like customer segmentation offer more objectivity than established qualitative assessments. In contrast to existing research, which focuses on customer segmentation based on buying behavior, this paper prototypes a usage-behavior-based customer segmentation for a machine tool manufacturer for sheet metal processing, utilizing machine usage data. Additionally, self-service reports of the customer segmentation are generated. The design choices regarding the data selection, pre-processing, and clustering algorithm selection are verified based on the segmentation results and real-world applicability of the generated reports.

Multivariate Profile Monitoring Method

Several authors refer to product portfolio management as an essential process because it may be used as a corporate management tool. However, the product portfolio management methods which are often adopted have limitations that prevent its use in practice, mainly due to the high dimensionality of selecting an optimal portfolio. Moreover, the large amount of available data is a relevant issue for practical applications. Thus, the contribution of this article is to propose a method for the product life cycle to monitor time-series behaviour patterns. The goal is to identify changes that may indicate that the product portfolio needs to be revised. The proposed method uses a multivariate regression model to relate financial variables associated with the products portfolio, the performance of products against competition, and even macroeconomic data. The objective is, through profile monitoring, to identify the specific time for the product portfolio review decision-making. We adopted three tools to develop a method – principal component analysis, multivariate regression model, and profile monitoring with Hotelling T 2 Control chart. A Monte Carlo simulation validated the approach. The results showed false alarm rate and average time to signal to be similar to previous studies. Finally, the application of the model is illustrated in a real case, using data provided by a company’s portfolio of agricultural equipment.

RETRACTED: Selecting and balancing market portfolio using artificial intelligence and fuzzy multiobjective decision-making model

Most enterprises focus on product portfolio management (PPM) and exclude market portfolio management, and individual markets are selected solely based on financial performance which may not be appropriate because other factors may dictate the outcome of the market selection. This study proposes a market portfolio model that considers market share, market growth, market competition, market risk, and market cost to maximize overall profit. A three-stage approach is proposed to identify potential product markets using an AI algorithm. A set of the most promising market is then determined based on the results of Stage 1 using a fuzzy multi-objective mathematical programming model by concurrently maximizing the total market share and market growth, and minimizing the market competition and market risk. A single-objective mathematical programming model is then used to determine a market portfolio to maximize the total profit using the results for Stage 2. The single-objective model is tested using two sets of threshold constraints. The balance of the market portfolio is discussed and the results are compared. The novelty of the article: (1) the first study involves a product market portfolio, (2) the decision of market selection is scientific (using AI instead of personal judgment), holistic (factors include market share, growth, competition, risk, cost, and profit) and optimized (using mathematical optimization), and (3) the market portfolio maximizes total profit. (4) the proposed method produces a portfolio with a higher profit than the TOPSIS method.

Industrial operation model for the construction industry

For decades, the construction industry has been searching for avenues to improve productivity. One potential direction for improvement is industrialisation, which involves repetitive and modular products and standardised processes to achieve economies of scale. This article describes an industrial operation model (IOM) based on the literature and uses empirical studies to find the emerging elements of the IOM in the construction industry. We employed qualitative and inductive approaches to build the general IOM framework. We determined the main challenges for the IOM through semi-structured interviews with 11 companies. The current state of the analysed IOM elements was perceived as inconstant and generally weak. In any case, we were able to describe several challenges in the main areas of the IOM. In this study, six preconditions for the IOM were defined as critical: defined target markets and products, effective product portfolio management, product and process data availability, efficient operative business processes, systematic continuous improvement, and governance and owners of the main IOM elements. The IOM framework and the proposed preconditions can be used as bases for future productivity development in the construction industry.

AI Predicted Product Portfolio for Profit Maximization

ABSTRACT Enterprises analyze opportunities and threats in the external environment, measure internal strengths and weaknesses, and formulate strategic objectives to stay ahead of their opponents. Product portfolio management (PPM) is a dynamic process by which an enterprise chooses which products to develop, sell, maintain, and remove to achieve strategic objectives, maximize profit, and balance markets for different capabilities. Most product portfolios involve new products only and exclude existing products. This study proposes a product/market portfolio model that considers both old/new products and old/new markets to maximize overall PPM profit, determine which old products should stay in existing markets, which new markets should be considered, or which markets should be abandoned, and develop new products for old markets or to introduce new products to some new markets. This study uses machine learning and deep learning algorithms to establish prediction models to screen the planned products and markets with a high success rate. Mathematical programming is then used to determine which old products should be sold in which old and new markets and which new products should be launched in which new and old markets to maximize profit. A sensitivity analysis is used to determine the effect of changes in the resource and the risk threshold on profit and product/market selection.

Using Machine Learning for Product Portfolio Management: A Methodical Approach to Predict Values of Product Attributes for Multi-Variant Product Portfolios

AbstractTo satisfy customer needs in the best way, companies offer them an almost infinite number of product variants. Although, an identical product was not built before, the values of its attributes must be determined during the product configuration process. This paper introduces a methodical approach to predict the values of product attributes based on customer feature configurations using machine learning. Machine learning reduces the effort compared to rule-based expert systems and is both, more accurate and faster. The approach was validated by predicting vehicle weights using industrial data.

모바일 앱 포트폴리오 전략이 모바일 개발자의 성과에 미치는 영향

What mobile app development strategy should the developer consider to survive and grow in hypercompetitive mobile application market? Mobile app market is one of the most rapidly growing segment in software market. Although mobile app market is a promising area, this positive perspective is not consistently applicable to app developers. In extremely competitive mobile app market, application developers would need to carefully consider and formulate app development strategies for success. To define the strategies, product portfolio management composing with app development speed, diversification speed, and switch speed is introduced. Quantitative analysis validating the statistical relationship between portfolio strategies and app developer’s financial performance is conducted. For this analysis, data from app developers with worldwide cumulative revenue estimate of over $100,000 were collected. As a result of data analysis, positive relationship between app development speed and developer’s financial performance was supported whereas diversification speed and switch speed had negative relationship with revenue. Theoretically, this research differs from the previous mobile app related studies. While previous studies used app ranking or user ratings as proxy for app performance, this study uses estimated sales volume as dependent variable which reflects more accurate and empirical performance.

Advantages For Portfolio Management Through Cost Scaling Equations for Offshore Wind Turbine Components

This paper presents the key concerns of offshore wind turbine Original Equipment Manufacturers’ (OEMs) Product Portfolio Management (PPM) functions for the predicted turbine growth. In addition, it provides possible improvements within the portfolio decision process through available cost forecast equations for turbines’ main components.

Productization as a link to combining product portfolio management and product family development

In R&D many disciplines focus on different aspects of managing the product life cycle. Generally, the focus can be divided into technical aspects and business aspects. Combining these two views, and research areas can be beneficial in the context of productization. Productization links to the concept of product structure and relates to modelling of the offering according to a consistent product structure, commercially and technically. The goal of this research is to identify how a business-specific product structure can be formed and should be managed to maximize the value of the offering. This study uses a literature review for defining the current state of product portfolio management (PPM) and product family development (PFD) concepts with linkages to productization. As a result, this study presents similarities and differences between PPM and PFD through the productization lens. A suggestion of combining the best practices of both approaches is demonstrated through an illustrative case study. Also, proposals for future research are presented. The main contribution involves indicating that effective PPM requires a business-specific physical product structure and partitioning logic. The benefits of PPM can only be truly captured through applicable product structure. Therefore, PFD is recommended to be used in designing product portfolio related technical aspects. PPM is applied for management purposes with the support of a defined product structure.