A PRACTICAL TEST OF A PROCESS MODEL FOR CUSTOMER RELATIONSHIP MANAGEMENT SYSTEM SELECTION WITH AN AUTOMOTIVE SUPPLIER

Selecting suitable customer relationship management systems (CRM) is a decision problem with economic, behavioural, technical and functional implications. It is important to methodically identify an appropriate solution with regard to the various aspects of the decision. In this paper, a practical test of the previously developed customer relationship management system selection (CRMSS) process model is conducted in a case study with an automotive safety goods supplier. The process model used was constructed based on a literature review and further refined by expert interviews and two international online surveys. To test the models applicability and align phases, tasks, roles and deliverables with practical experiences, qualitative interviews were conducted with the different stakeholders in the evaluation project. The CRMSS process model was then further refined according to the conclusions drawn from the presented case study. The first application of the process model suggests that it is considered as relevant for practice and can be understood and applied successfully for a CRM selection and evaluation. In the context of the case study the model was customised to meet the needs of the project

A decision support methodology to enhance the competitiveness of the Turkish automotive industry

This is the post-print (final draft post-refereeing) version of the article. Copyright @ 2013 Elsevier B.V. All rights reserved.Three levels of competitiveness affect the success of business enterprises in a globally competitive environment: the competitiveness of the company, the competitiveness of the industry in which the company operates and the competitiveness of the country where the business is located. This study analyses the competitiveness of the automotive industry in association with the national competitiveness perspective using a methodology based on Bayesian Causal Networks. First, we structure the competitiveness problem of the automotive industry through a synthesis of expert knowledge in the light of the World Economic Forum’s competitiveness indicators. Second, we model the relationships among the variables identified in the problem structuring stage and analyse these relationships using a Bayesian Causal Network. Third, we develop policy suggestions under various scenarios to enhance the national competitive advantages of the automotive industry. We present an analysis of the Turkish automotive industry as a case study. It is possible to generalise the policy suggestions developed for the case of Turkish automotive industry to the automotive industries in other developing countries where country and industry competitiveness levels are similar to those of Turkey

Absorptive capacity and relationship learning mechanisms as complementary drivers of green innovation performance

This paper aims to explore in depth how internal and external knowledge-based drivers actually affect the firms\u2019 green innovation performance. Subsequently, this study analyzes the relationships between absorptive capacity (internal knowledge-based driver), relationship learning (external knowledge-based driver) and green innovation performance. This study relies on a sample of 112 firms belonging to the Spanish automotive components manufacturing sector (ACMS) and uses partial least squares path modeling to test the hypotheses proposed. The empirical results show that both absorptive capacity and relationship learning exert a significant positive effect on the dependent variable and that relationship learning moderates the link between absorptive capacity and green innovation performance. This paper presents some limitations with respect to the particular sector (i.e. the ACMS) and geographical context (Spain). For this reason, researchers must be thoughtful while generalizing these results to distinct scenarios. Managers should devote more time and resources to reinforce their absorptive capacity as an important strategic tool to generate new knowledge and hence foster green innovation performance in manufacturing industries. The paper shows the importance of encouraging decision-makers to cultivate and rely on relationship learning mechanisms with their main stakeholders and to acquire the necessary information and knowledge that might be valuable in the maturity of green innovations. This study proposes that relationship learning plays a moderating role in the relationship between absorptive capacity and green innovation performance

'Smart' design: greening the Total Product System

About the book: Since the Rio summit in 1992, the paradigm of corporate environmental responsibility has gradually and consistently extended beyond complying with increasingly stringent environmental regulation and taking up the proactive initiatives of a few world-class companies. Research indicates that the business and financial performance of companies may depend directly on socially and environmentally responsible business practices. Many world-class companies now realize that customers and other stakeholders do not distinguish between a company and its suppliers. As a result, greening the supply chain is an innovative idea which is fast gaining attention in the industry. Greening the Supply Chain is a compilation of important chapters written by a diverse set of international authors which incorporates a broad variety of perspectives. Note: Smart car refers to Smart City coupe and Fortwo, and all terms are registered trademarks of MCC (micro compact car)

Supply chain decision making supported by an Open books policy

Based on a study of a buyer–seller relationship in the automotive industry, this article identifies 17 different decision-making processes where openly sharing cost data—a so-called open books policy—plays an important supporting role. These processes relate to supplier selection, various activities that occur prior to production, and the full-speed production stage of the exchange process. Overall, open books plays the greatest role in the pre-production stage, although it is found to support decision-making relating to supplier selection and decision-making during full-speed production to a greater extent than the literature recognizes

Contributions to the selection and implementation of standard software for CRM and electronic invoicing

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Inventory drivers in a pharmaceutical supply chain

In recent years, inventory reduction has been a key objective of pharmaceutical companies, especially within cost optimization initiatives. Pharmaceutical supply chains are characterized by volatile and unpredictable demands –especially in emergent markets-, high service levels, and complex, perishable finished-good portfolios, which makes keeping reasonable amounts of stock a true challenge. However, a one-way strategy towards zero-inventory is in reality inapplicable, due to the strategic nature and importance of the products being commercialised. Therefore, pharmaceutical supply chains are in need of new inventory strategies in order to remain competitive. Finished-goods inventory management in the pharmaceutical industry is closely related to the manufacturing systems and supply chain configurations that companies adopt. The factors considered in inventory management policies, however, do not always cover the full supply chain spectrum in which companies operate. This paper works under the pre-assumption that, in fact, there is a complex relationship between the inventory configurations that companies adopt and the factors behind them. The intention of this paper is to understand the factors driving high finished-goods inventory levels in pharmaceutical supply chains and assist supply chain managers in determining which of them can be influenced in order to reduce inventories to an optimal degree. Reasons for reducing inventory levels are found in high inventory holding and scrap related costs; in addition to lost sales for not being able to serve the customers with the adequate shelf life requirements. The thesis conducts a single case study research in a multi-national pharmaceutical company, which is used to examine typical inventory configurations and the factors affecting these configurations. This paper presents a framework that can assist supply chain managers in determining the most important inventory drivers in pharmaceutical supply chains. The findings in this study suggest that while external and downstream supply chain factors are recognized as being critical to pursue inventory optimization initiatives, pharmaceutical companies are oriented towards optimizing production processes and meeting regulatory requirements while still complying with high service levels, being internal factors the ones prevailing when making inventory management decisions. Furthermore, this paper investigates, through predictive modelling techniques, how various intrinsic and extrinsic factors influence the inventory configurations of the case study company. The study shows that inventory configurations are relatively unstable over time, especially in configurations that present high safety stock levels; and that production features and product characteristics are important explanatory factors behind high inventory levels. Regulatory requirements also play an important role in explaining the high strategic inventory levels that pharmaceutical companies hold

GResilient index to assess the greenness and resilience of the automotive supply chain

Purpose: The purpose of this paper is to suggest an Index entitled GResilient Index to assess the greenness and resilience of the automotive companies and corresponding supply chain. Design/methodology/approach: An integrated assessment model is proposed based on Green and Resilient practices. These practices are weighted according to their importance to the automotive supply chain competitiveness. The Delphi technique is used to obtain the weights for the focused supply chain paradigms and corresponding practices. The model is then tested using a case study approach in the automotive supply chain. Findings: The case study results confirmed the applicability of this Index in a real-world supply chain. The results show that the Resilient supply chain management paradigm is the one considered as the one that more contributes for the automotive supply chain competitiveness. Research limitations/implications: The proposed Index was developed in the automotive sector context therefore it could not be adjusted to a different one. Future research could consider other aggregation methods for the Index construction. Practical implications: Supply chain participants will be able to evaluate the performance of their companies or supply chain in terms of Green and Resilient paradigms. Also, the Index can be effectively employed for functional benchmarking among competing companies and supply chains.Green; resilient; supply chain management; index; automotive industry