Aligning supply chain portfolios with product portfolios

Langenberg, Kerstin U.; Seifert, Ralf W.; Tancrez, Jean‐Sébastien

doi:10.1016/j.ijpe.2011.08.032

Cited by 26 publications

(32 citation statements)

References 24 publications

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“…First of all, we observe that it is more costly to run a supply chain for an innovative product than for a functional product (in line with Fisher, 1997 andLangenberg et al, 2012). The main reason is the high degree of supply chain responsiveness required by the innovative product.…”

Section: Base Case For Both Product Typessupporting

confidence: 62%

“…As Fisher (1997) explains, demand uncertainty, holding costs and inventory costs are important factors to be considered when defining supply chain strategies. Langenberg et al (2012) and Seifert and Langenberg (2011) provide quantitative support for Fisher's qualitative framework. They present supply chain network design models that explicitly capture supply chain lead time and responsiveness decisions, and take into account demand uncertainty.…”

Section: Literature Reviewmentioning

confidence: 90%

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Carbon footprint and responsiveness trade-offs in supply chain network design

Martí

Tancrez

Seifert

2015

International Journal of Production Economics

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113

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a b s t r a c tConcern related to sustainability and greenhouse gases has grown among citizens as well as firms, which are increasingly committing to carbon emission reduction targets. However, firms' emissions come from direct and indirect sources, and from the different stages of their supply chain. Therefore, comprehensive supply chain approaches are essential to ensure the cost-effectiveness of carbon management strategies. These approaches should capture operational and environmental trade-offs arising from the interaction between different supply chain processes such as procurement, manufacturing, transport and inventory management. Considering all these processes, we propose a model for supply chain network design that takes demand uncertainty into account and includes decisions on supply chain responsiveness under different carbon policies: caps on supply chain carbon footprints, caps on market carbon footprints, and carbon taxes. Our model supports the analysis of the effect of different policies on costs and optimal network configuration and allows us to distinguish between different product types: functional or innovative products. With detailed numerical examples, we illustrate the type of analysis and managerial insights that can be derived with our model, which include the assessment of supply chains' potential for carbon abatement, the study of the effect of different carbon policies on supply chain costs and network design, the analysis of the impact of various product characteristics, the test of an alternative profit maximisation model, and the determination of the value of a supply chain carbon tax that should induce specific levels of carbon abatement.

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Section: Base Case For Both Product Typessupporting

confidence: 62%

Section: Literature Reviewmentioning

confidence: 90%

Carbon footprint and responsiveness trade-offs in supply chain network design

Martí

Tancrez

Seifert

2015

International Journal of Production Economics

Self Cite

113

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“…According to Orfi et al (2011) the product variety leads to product complexity with negative impacts on productivity, costs, new product development time, and customer satisfaction. Simultaneously offering functional products and new innovative products is also seen to complicate the demand supply chain (Langenberg et al, 2012). According to Gunasekaran et al (2004) a wide range of products decreases the performance of the operational supply chain, resulting in less value added per headcount, longer lead times, and decrease in on time deliveries.…”

Section: Introductionmentioning

confidence: 99%

Product portfolio management – Targets and key performance indicators for product portfolio renewal over life cycle

Tolonen

Shahmarichatghieh

Härkönen

et al. 2015

International Journal of Production Economics

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a b s t r a c tThe main purpose of this study is to widen the scope of product portfolio management (PPM) targets and key performance indicators (KPIs) to cover all phases of the product life cycle. Earlier research mainly covers PPM performance management within new product development (NPD) life cycle only. In addition, current challenges relating to PPM performance management over product life cycle are studied.The research method includes current state analysis based on both a thorough literature review and analysing ten case companies that represent hardware (HW), software (SW), services and solutions type businesses. The contribution is discussed and validated by a focus group consisting of all the case companies before making final conclusions.The principal results of this study include the potential framework for managing product portfolio renewal over the entire product life cycle based on strategic, tactical and operational performance measures. The PPM performance management, its business impact and connection to business processes and performance management dashboard are discussed.The role of PPM as a means of executive level dynamic performance management and decision making sets further questions for researchers' for systematic product portfolio definitions, governance models, processes and tools over product life cycle.

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“…However, other variables are potentially important for determining value of market mediation as well. Contract penalties and goodwill loss in case of late delivery, for instance, may also incentivize companies to invest in market mediation by increasing the cost of shortages (Langenberg, Seifert, & Tancrez, ).…”

Section: Categorizing Contingency Variablesmentioning

confidence: 99%

“…A failure to deliver as promised may at best result in a negative customer experience with no adverse financial effects. It is more likely, however, that a failure to deliver as promised will result in penalty payments, lost sales, and foregone contribution margins (Langenberg et al., ). A large‐scale supply chain disruption or recurring unreliability will damage customer relationships and eventually result in disappointed customers leaving for good (Hendricks & Singhal, ; Craighead, Blackhurst, Rungtusanatham, & Handfield, , Craighead et al., ; Habermann, Blackhurst, & Metcalf, ).…”

Section: Hypothesesmentioning

confidence: 99%

How to Find the Right Supply Chain Strategy? An Analysis of Contingency Variables

2019

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Contingency variables are characteristics of the business environment that influence the competitive priorities supply chains should pursue for maximizing profits. But which contingency variables should managers focus on when developing a supply chain strategy? On the one hand, if important variables are omitted, the selected strategy may fail to fulfill the needs of the business environment. On the other hand, considering irrelevant variables unnecessarily complicates the strategy formation process, hence preventing well‐suited strategies from being found. As a first step toward resolving this trade‐off, our study analyzes the effects hypothesized to be underlying a set of frequently cited contingency variables referred to as “DWV3” (product lifecycle Duration, delivery time Window, demand Variability, demand Volume, product Variety) as well as contribution margins. We test the hypotheses on archival data from a leading chemical manufacturer using multilevel regression. Our findings indicate that demand variability, the delivery time window, and contribution margins are important for strategy development because they indicate to what extent companies should invest in market mediation. Volume, variety, and lifecycle duration are less important for this purpose, but may instead be used for analyzing the causes of demand variability.

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Aligning supply chain portfolios with product portfolios

Cited by 26 publications

References 24 publications

Carbon footprint and responsiveness trade-offs in supply chain network design

Carbon footprint and responsiveness trade-offs in supply chain network design

Product portfolio management – Targets and key performance indicators for product portfolio renewal over life cycle

How to Find the Right Supply Chain Strategy? An Analysis of Contingency Variables

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