scholarly journals Using P2P sharing activity to improve business decision making: proof of concept for estimating product life-cycle

2005 ◽  
Vol 4 (1) ◽  
pp. 14-20 ◽  
Author(s):  
Sudip Bhattacharjee ◽  
Ram Gopal ◽  
Kaveepan Lertwachara ◽  
James R. Marsden
Keyword(s):  
Decision Making ◽  
Life Cycle ◽  
Product Life Cycle ◽  
Proof Of Concept ◽  
Business Decision ◽  
Product Life

scholarly journals Analysis of the behaviour of the clients assisted and sales variables in the different phases of the product life cycle

2018 ◽  
Vol 27 (3) ◽  
pp. 266-284 ◽  
Author(s):  
Aida Galiano ◽  
Vicente Rodríguez ◽  
Manuela Saco
Keyword(s):  
Life Cycle ◽  
Product Life Cycle ◽  
Business Management ◽  
Bass Model ◽  
Business Decision ◽  
Product Life ◽  
Content Type ◽  
Nonlinear Regression Models ◽  
Sales And Marketing ◽  
Practical Implications

Purpose The Bass model was created to analyse the product life cycle (PLC) in order to help sales and marketing departments in their business decision making. The purpose of this paper is to analyse the diferences between the clients assisted and sales variables, to discover which of the two variables is the more useful for the estimation of the PLC phases through the Bass model, thus aiding the managers of company sales and marketing departments. Design/methodology/approach In this research, the authors analysed the 223,577 clients assisted by a nationwide network of car dealerships, who acquired 36,819 vehicles, during a 24-month period. In the analysis, the Bass model was applied to define the PLC phases; and nonlinear regression models were used to carry out the estimations. Findings The results show that more consistent estimates of the PLC phases are obtained from the clients assisted variable. This work has theoretical and practical implications that can help business management. Research limitations/implications The most remarkable thing about this research is that we have shown that the functionality of the clients assisted variable is greater than the sales variable for the Bass model and, therefore, for PLC estimation. Practical implications The results of this research are very useful, since they allow marketing decision makers to obtain more consistent estimations of the PLC phases using the Bass model and the clients assisted variable. This is based on the fact that the use of this variable helps to detect if there is any deficiency in the design of the marketing strategy when the client does not make the purchase. Social implications The data on clients assisted are as easily available to companies as sales data. However, the use of this variable improves PLC analysis and this allows an improvement in company forecasting. Thus, making the clients assisted variable a tool to strategically plan investments in innovation and marketing would reduce uncertainty in business management. Originality/value The purpose of this paper is to analyse the diferences between the clients assisted and sales variables, to discover which of the two variables is the more useful for the estimation of the PLC phases through the Bass model, thus aiding the managers of company sales and marketing departments.

scholarly journals Understanding the Stages of the Product Life Cycle

2021 ◽  
Author(s):  
Chinonso Kenneth Udokporo
Keyword(s):  
Decision Making ◽  
Life Cycle ◽  
Technological Innovation ◽  
Product Life Cycle ◽  
Corporate Strategy ◽  
Strategy Development ◽  
Product Life ◽  
Technology Deployment ◽  
Biological Studies ◽  
Support Decision Making

Originally formulated in the context of biological studies, the Life cycle (LC) concept was and now has become widely adopted as a framework for the interpretation and evaluation of phenomena that are subject to, and bound by the inevitability of change. The application of the LC concept to the development of industrial products is an important element in the administration of technological innovation. On this basis, therefore, it is referred to as the product life cycle (PLC). The concept of the PLC is used to support decision making in the management of product development. It may also be used in corporate strategy development, as well as the planning of activities and can be adapted to focus on technology deployment.

A Sustainability and Mass Customization Assessment Framework

2012 ◽  
Author(s):  
Khaled Medini ◽  
Catherine Da Cunha ◽  
Alain Bernard
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Life Cycle ◽  
Mass Customization ◽  
Product Life Cycle ◽  
Current Paper ◽  
Decision Making Process ◽  
Assessment Framework ◽  
Product Life ◽  
Sustainability Performance

The paper presents a framework for the assessment of mass customization and sustainability performance of enterprises and supply chains. The assessment includes the product, process, enterprise and supply chain levels while considering the product life cycle phases. This two perspectives approach ensures a quite complete assessment and provides guidance to designers and managers during the decision making process. The framework construction and use methods are depicted in the current paper.

A method for Estimating the Degree of Uncertainty With Respect to Life Cycle Assessment During Design

2010 ◽  
Vol 132 (9) ◽  
Author(s):  
Srinivas Kota ◽  
Amaresh Chakrabarti
Keyword(s):  
Decision Making ◽  
Life Cycle Assessment ◽  
Life Cycle ◽  
Environmental Impact ◽  
Product Life Cycle ◽  
Uncertainty Estimation ◽  
Decision Making Process ◽  
Product Life ◽  
Individual Product ◽  
Total Impact

Life cycle assessment (LCA) is used to estimate a product’s environmental impact. Using LCA during the earlier stages of design may produce erroneous results since information available on the product’s lifecycle is typically incomplete at these stages. The resulting uncertainty must be accounted for in the decision-making process. This paper proposes a method for estimating the environmental impact of a product’s life cycle and the associated degree of uncertainty of that impact using information generated during the design process. Total impact is estimated based on aggregation of individual product life cycle processes impacts. Uncertainty estimation is based on assessing the mismatch between the information required and the information available about the product life cycle in each uncertainty category, as well as their integration. The method is evaluated using pre-defined scenarios with varying uncertainty.

scholarly journals Closed Product Life Cycle as a Basis of the Circular Economy

2021 ◽  
Vol 5 (4) ◽  
pp. 36-50
Author(s):  
Maria Vetrova ◽  
Dinara Ivanova
Keyword(s):  
Decision Making ◽  
Life Cycle ◽  
Supply Chains ◽  
Circular Economy ◽  
Product Life Cycle ◽  
Digital Technologies ◽  
Economic Feasibility ◽  
Decision Support Model ◽  
Product Life ◽  
The Impact

Objective – The circular economy aims to preserve the value of products and materials within a closed supply chain. The existing models and decision-making methods for managing the end of the product life cycle are mostly focused on the economic aspects. While the circular economy is aimed at combining environmental, economic and social goals. This article aims to develop a model for enterprise decision-making on the disposal of used products, taking into account socio-environmental and economic factors. Methodology/Technique – The article analyzes the impact of digital technologies on the formation of closed supply chains and the development of a circular economy. At the same time, special attention is focused on the model of a closed product life cycle, as a fundamental element in the formation of a circular economy at the micro and nano levels, as well as the importance of using digital technologies at all stages of the product life cycle. Findings –The methods of product management at the end of the life cycle studied in the article have made it possible to form a simulation decision support model regarding the method of product disposal, taking into account environmental and economic feasibility. Novelty – This study identified the main trends in the development of closed supply chains under the influence of digital technologies in the context of a circular economy. Type of Paper: Review JEL Classification: F42, F43 Keywords: Circular Economy; Digital Technology; Decision-making Model; Closed-loop Supply Chains Reference to this paper should be made as follows: Vetrova, M; Ivanova, D. (2021). Closed Product Life Cycle as a Basis of the Circular Economy, Journal of Business and Economics Review, 5(4) 36–50. https://doi.org/10.35609/jber.2021.5.4(4)

scholarly journals Opportunities and challenges for the inclusion of patient preferences in the medical product life cycle: a systematic review

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Rosanne Janssens ◽  
Isabelle Huys ◽  
Eline van Overbeeke ◽  
Chiara Whichello ◽  
Sarah Harding ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Life Cycle ◽  
Patient Preferences ◽  
Product Life Cycle ◽  
Grey Literature ◽  
Medical Product ◽  
Preference Heterogeneity ◽  
Product Life ◽  
Benefit Risk Assessment

Abstract Background The inclusion of patient preferences (PP) in the medical product life cycle is a topic of growing interest to stakeholders such as academics, Health Technology Assessment (HTA) bodies, reimbursement agencies, industry, patients, physicians and regulators. This review aimed to understand the potential roles, reasons for using PP and the expectations, concerns and requirements associated with PP in industry processes, regulatory benefit-risk assessment (BRA) and marketing authorization (MA), and HTA and reimbursement decision-making. Methods A systematic review of peer-reviewed and grey literature published between January 2011 and March 2018 was performed. Consulted databases were EconLit, Embase, Guidelines International Network, PsycINFO and PubMed. A two-step strategy was used to select literature. Literature was analyzed using NVivo (QSR international). Results From 1015 initially identified documents, 72 were included. Most were written from an academic perspective (61%) and focused on PP in BRA/MA and/or HTA/reimbursement (73%). Using PP to improve understanding of patients’ valuations of treatment outcomes, patients’ benefit-risk trade-offs and preference heterogeneity were roles identified in all three decision-making contexts. Reasons for using PP relate to the unique insights and position of patients and the positive effect of including PP on the quality of the decision-making process. Concerns shared across decision-making contexts included methodological questions concerning the validity, reliability and cognitive burden of preference methods. In order to use PP, general, operational and quality requirements were identified, including recognition of the importance of PP and ensuring patient understanding in PP studies. Conclusions Despite the array of opportunities and added value of using PP throughout the different steps of the MPLC identified in this review, their inclusion in decision-making is hampered by methodological challenges and lack of specific guidance on how to tackle these challenges when undertaking PP studies. To support the development of such guidance, more best practice PP studies and PP studies investigating the methodological issues identified in this review are critically needed.

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