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In order to make a thorough inquiry into the criterion of optimal product structure in the micro‐economic system (enterprise), this paper has proposed and demonstrated the benefit‐type linear programming model, and based on it, the concepts of enterprise's product structure, feasible structure and optimal structure have been discussed and the criterion of optimal structure has been revealed. In this paper, the methods of simplex iteration and sensitivity analysis are both used to approach necessarily the adjustment of product structure under the circumstances of varied or invaried environment inside and outside the system, and as a final, it has come to a conclusion that the variation of resource price vector P would not affect the optimal product structure in enterprise, but the variation of resource‐constrained vector b will cause negative effects both on optimal product structure in enterprise and on determination of criterion for optimal structure.

This paper deals with the organizing of interactive product development. Developing products in interaction between firms may provide benefits in terms of specialization, increased innovation, and possibilities to perform development activities in parallel. However, the differentiation of product development among a number of firms also implies that various dependencies need to be dealt with across firm boundaries. How dependencies may be dealt with across firms is related to how product development is organized. The purpose of the paper is to explore dependencies and how interactive product development may be organized with regard to these dependencies.

The analytical framework is based on the industrial network approach, and deals with the development of products in terms of adaptation and combination of heterogeneous resources. There are dependencies between resources, that is, they are embedded, implying that no resource can be developed in isolation. The characteristics of and dependencies related to four main categories of resources (products, production facilities, business units and business relationships) provide a basis for analyzing the organizing of interactive product development.

Three in-depth case studies are used to explore the organizing of interactive product development with regard to dependencies. The first two cases are based on the development of the electrical system and the seats for Volvo’s large car platform (P2), performed in interaction with Delphi and Lear respectively. The third case is based on the interaction between Scania and Dayco/DFC Tech for the development of various pipes and hoses for a new truck model.

The analysis is focused on what different dependencies the firms considered and dealt with, and how product development was organized with regard to these dependencies. It is concluded that there is a complex and dynamic pattern of dependencies that reaches far beyond the developed product as well as beyond individual business units. To deal with these dependencies, development may be organized in teams where several business units are represented. This enables interaction between different business units’ resource collections, which is important for resource adaptation as well as for innovation. The delimiting and relating functions of the team boundary are elaborated upon and it is argued that also teams may be regarded as actors. It is also concluded that a modular product structure may entail a modular organization with regard to the teams, though, interaction between business units and teams is needed. A strong connection between the technical structure and the organizational structure is identified and it is concluded that policies regarding the technical structure (e.g. concerning “carry-over”) cannot be separated from the management of the organizational structure (e.g. the supplier structure). The organizing of product development is in itself a complex and dynamic task that needs to be subject to interaction between business units.

The objective of this paper is to propose a consumer-behavior-based intelligence (CBBI) model to identify market structure so as to monitor product competition. Competitive intelligence extracted from Chinese e-business clickstream data is exploited to examine the relevance of consumers' heterogeneous behavioral feedback, namely, click, tag-into-favorite, time-of-browsing, add-into-cart, and remove-from-cart, to visualize the competitive product market structure and to predict product-level sales.

Our proposed CBBI model consists of visualization and prediction, which explore e-business clickstream data. We conduct the visualization and segmentation of market structure in the form of a perceptual map by employing K-means clustering algorithm and multidimensional scaling technique. Concurrently, we developed an updated Bayesian linear regression (BLR) to predict product-level sales by considering consumers' heterogeneous feedback. Our updated BLR specifically integrated the estimated knowledge of the previous periods to verify whether product sales are period-dependent due to the consumer memory effect in e-commerce, improving the conventional BLR of diffuse prior distribution setup in terms of mean absolute error (MAE) and root mean squared error (RMSE).

Considering the performance of consumers' heterogeneous actions, the present research visualized three different segments of the competitive market structure in a perceptual map, and its horizontal axis is shown as a signal of the ascending trend of product sales. The previous five-day period was ascertained to be the best size of a time window for the consumer memory effect on product sales prediction. This hypothesis is supported by the concept that product sales are period-dependent. The results of the proposed updated BLR indicate that consumer tag-into-favorite, add-into-cart, and remove-from-cart feedback have positive impacts on product-level sales while click and time-of-browsing have the opposite effect.

While the identified competitive product market structure elaborates consumer heterogeneous feedback toward alternative product choices, this paper contributes by extending those homogeneous consumer preferences-related marketing studies. The perceptual map's configuration in respect to period-dependent product sales facilitates the effective inclusion of consumer behavior application in product sales prediction research in e-commerce. This paper helps sellers and retailers better comprehend the impacts of heterogeneous feedback and the consumer memory effect on the degree of competition in the form of product sales. The research results also offer a managerial implication about shaping the competitive edge by conducting different product management strategies in e-commerce platforms.

The authors evaluate the preferences of retail investors with regard to the investment in structured financial products. The purpose of the paper is an analysis of the relative importance of key product attributes namely the issuing bank, the product structure, the associated costs and the disclosed risk.

The authors conduct a choice-based conjoint analysis, based on an online experiment. Participants judge their preferences for products which are presented by shortened key information documents according to the requirements of EU regulation.

Investors consider the costs and the product structure to be most important, whereas the issuer and information on risk are of less interest. Their preferences depend on their (self-evaluated) expertise: while inexperienced retail investors concentrate on costs, experienced investors pay more attention to the product structure.

The study is limited to a subsegment of the market, the discount certificates. For these products, issuing banks gain insight into the attractiveness of their products. Furthermore, the study carries implications for regulators: since investors emphasize the costs in their decisions, an unbiased disclosure of costs should be enforced.

While the recent literature has studied preferences for the investment in mutual funds, this is the first paper which directly analyzes the drivers of an investment in structured retail products.

It is necessary to implement green supply chains. But green development needs to be gradual and coexist with ordinary products in the market. This paper aims to study the green and ordinary product pricing and green decision-making under chain-to-chain competition.

This paper considers consumers' multiple preferences and takes two competitive supply chains with asymmetric channels as the research object. Through the construction of the game models involving different competitive situations, this paper studies the pricing, green decision-making and the supply chains' profits, and discusses the impact of consumer green preference, channel preference, green investment and competition on the decision-making and performance. Finally, this paper further studies the impact of the decision structure on the environmental and economic benefits of supply chains.

The results show that consumer green preference has an incentive effect on the green supply chain and also provides an opportunity for the regular supply chain to increase revenue. Specifically, consumers' preference for green online channels improves the product greenness, but its impact on the green retailer and regular supply chain depends on the green investment cost. Moreover, competition not only fosters product sustainability, but also improves supply chain performance. This paper also points out that the decentralization of the regular supply chain is conducive to the environmental attributes of the green product, while the environment-friendly structure of the green supply chain is different under different conditions. In addition, the profit of a supply chain under centralized decision is not always higher than that under decentralized decision.

The novelty of this paper is that it investigates the pricing of two heterogeneous alternative products and green decision-making for the green product under the competition between two supply chains with asymmetric channels, in which the green supply chain adopts dual channels and the regular supply chain adopts a single retail channel.

The Nature of Business Policy Business policy — or general management — is concerned with the following six major functions:

Supplier selection is a complex decision that involves not only the consideration of unit purchasing cost but also product life-cycle cost (LCC), which affects the company’s after-sale costs over the life cycles of their products. Product structure and its impact on the supplier selection evaluation process are rarely investigated in the literature. Therefore, product structure for a multi-criteria multi-product supplier selection problem with uncertainty is considered. In the model, we address product structure, the competitive supply environment, diverse criteria, and standard requirements. The objective is to choose suppliers that minimize LCC and maximize the reliability of the finished products.

Our model provides straightforward representation of interrelationships among multi-objectives and analysis of tradeoffs among conflicting objectives affected by product structure. We illustrate our model by using real life data from lubrication systems in the offshore reliability data (OREDA) handbook. Sensitivity analysis is provided for the case study in which various scenarios that describe product structure, the uncertainties in purchasing prices, reliabilities of purchased components, machine down-time due to poor quality components, suppliers’ capacity and delivery times. Different priority ranking among objectives is also tested to examine the impact of each objective on the overall objective.

Our computational results are based on real data and would provide useful guidelines for the management in OEM to choose right suppliers.

Product structure and its impact on the supplier selection evaluation process are rarely investigated in the literature. Therefore, product structure for a multi-criteria multi-product supplier selection problem with uncertainty is considered.

The purpose of this paper is to analyse current challenges and to articulate the preconditions for data-driven, fact-based product portfolio management (PPM) based on commercial and technical product structures, critical business processes, corporate business IT and company data assets. Here, data assets were classified from a PPM perspective in terms of (product/customer/supplier) master data, transaction data and Internet of Things data. The study also addresses the supporting role of corporate-level data governance.

The study combines a literature review and qualitative analysis of empirical data collected from eight international companies of varying size.

Companies’ current inability to analyse products effectively based on existing data is surprising. The present findings identify a number of preconditions for data-driven, fact-based PPM, including mutual understanding of company products (to establish a consistent commercial and technical product structure), product classification as strategic, supportive or non-strategic (to link commercial and technical product structures with product strategy) and a holistic, corporate-level data model for adjusting the company’s business IT (to support product portfolio visualisation).

The findings provide a logical and empirical basis for fact-based, product-level analysis of product profitability and analysis of the product portfolio over the product life cycle, supporting a data-driven approach to the optimisation of commercial and technical product structure, business IT systems and company product strategy. As a virtual representation of reality, the company data model facilitates product visualisation. The findings are of great practical value, as they demonstrate the significance of corporate-level data assets, data governance and business-critical data for managing a company’s products and portfolio.

The study contributes to the existing literature by specifying the preconditions for data-driven, fact-based PPM as a basis for product-level analysis and decision making, emphasising the role of company data assets and clarifying the links between business processes, information systems and data assets for PPM.

We undertake an empirical study of the well‐known product‐process matrix using data collected from 128 plants. Our analysis indicates that the relationship between product structure and process structure is significant, but not strong. Furthermore, less than half of the plants operate near the diagonal of the matrix. We found that the off‐diagonal plants are using innovative initiatives to overcome the lack of product structure and process structure match. As a result, we propose that a third dimension be added to the product‐process matrix that measures how aggressively plants are implementing these innovative initiatives, thereby explaining their off‐diagonal behavior.

Reports a new method for preparing a product structure analysis to improve the effectiveness of the master scheduling function for products that are manufactured on an assemble‐to‐order basis. This methodology for conducting product structure analysis uses relational database management software to identify common and unique material in a product structure. Highlights example results of the application of methodology.