An integrated core competence evaluation framework for portfolio management in the oil industry

Drawing upon resource-based theory, this paper presents a core competence evaluation framework for managing the competence portfolio of an oil company. It introduces a network typology to illustrate how to form different types of strategic alliance relations with partnering firms to manage and grow the competence portfolio. A framework is tested using a case study approach involving face-to-face structured interviews. We identified purchasing, refining and sales and marketing as strong candidates to be the core competencies. However, despite the company's core business of refining oil, the core competencies were identified to be their research and development and performance management (PM) capabilities. We further provide a procedure to determine different kinds of physical, intellectual and cultural resources making a dominant impact on company's competence portfolio. In addition, we provide a comprehensive set of guidelines on how to develop core competence further by forging a partnership alliance choosing an appropriate network topology

An integrated core competence evaluation framework for portfolio management in the oil industry

The proponents of resource-based theory argue that efficient management of core competence portfolio provides sustainable competitive advantages. However, literature demonstrates little evidence regarding (i) how to identify core competence, specifically for a company operating in the oil sector, (ii) how to identify tangible and intangible resources related to the core competence of the company, and (iii) how to manage a company’s competence portfolio more efficiently by forging network alliances with collaborating firms. Drawing upon resource-based theory this paper presents a core competence evaluation framework for managing the competence portfolio of an oil company. The paper introduces a network typology to illustrate how to form different types of strategic alliance relations with partnering firms to manage and grow the competence portfolio. The framework is tested using a case study approach involving face-to-face structured interviews with twenty-five divisional managers of a large oil company in the Middle East. We identified purchasing, refining and sales and marketing as strong candidates to be the core competencies of the company. However, despite the company’s core business of refining oil, the core competencies were identified to be their research and development and performance management (PM) capabilities. We further provide a procedure to determine different kinds of physical, intellectual and cultural resources making a dominant impact on company’s competence portfolio. In addition, we provide a comprehensive set of guidelines on how to develop core competence further by forging a partnership alliance choosing an appropriate network topology. The paper makes many contributions to the field of strategic management and core competence evaluation in the oil sector. The guidelines provided can assist practitioners with devising appropriate network relationships with partnering companies in order to outsource, divest, protect and/or develop their core competence portfolio

A hybrid analytical network process and fuzzy goal programming for supplier selection: A case study of auto part maker

The aim of this research is to present a hybrid model to select auto part suppliers. The proposed method of this paper uses factor analysis to find the most influencing factors on part maker selection and the results are validated using different statistical tests such as Cronbach's Alpha and Kaiser-Meyer.The hybrid model uses analytical network process to rank different part maker suppliers and fuzzy goal programming to choose the appropriate alternative among various choices. The implementation of the proposed model of this paper is used for a case study of real-world problem and the results are discussed

Shifting the Paradigm: Agricultural Marketing in a Product Conscious Age

Australian agriculture needs a new business model. The traditional broad acre food and fibre industries (wool, meat, grains)are coming under increasing competitive pressure. Effective resource management is one side of the competitive response. Improving returns through innovative marketing is another. Value chain development and management is an increasing focus by innovative food and fibre businesses. These industries have been slow to adopt alternatives to the traditional auction and trading arrangements. What then are the critical considerations underpinning the development of a value chain approach? And how can value chain development and performance be monitored and improved

Partner selection in green supply chains using PSO – a practical approach

Partner selection is crucial to green supply chain management as the focal firm is responsible for the environmental performance of the whole supply chain. The construction of appropriate selection criteria is an essential, but often neglected pre-requisite in the partner selection process. This paper proposes a three-stage model that combines Dempster-Shafer belief acceptability theory and particle swarm optimization technique for the first time in this application. This enables optimization of both effectiveness, in its consideration of the inter-dependence of a broad range of quantitative and qualitative selection criteria, and efficiency in its use of scarce resources during the criteria construction process to be achieved simultaneously. This also enables both operational and strategic attributes can be selected at different levels of hierarchy criteria in different decision-making environments. The practical efficacy of the model is demonstrated by an application in Company ABC, a large Chinese electronic equipment and instrument manufacturer

Partner selection in agile supply chains: A fuzzy intelligent approach

Partner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision-making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from 84 representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organisational decision-makers in partner selection

Success factors for Taiwanese contractors collaborating with local Chinese contractors in construction projects

Regional trade cooperation has become an important component of construction industry due to the Free Trade Agreement. This segment of the market presents many challenges for construction firms. Establishing suitable international partnering relations is an effective strategy for adapting to the additional unpredictability of international markets. This research integrates the Balanced Scorecard system with Fuzzy Analytic Hierarchy Process for comprehensive and quantitative evaluation of the relevant bilateral cooperation. Commercial cooperation across the Taiwan Strait is selected as a case study for determining the evaluating methodology. After examining data from Chinese firms, 12 factors for partner selection are identified. The factors are compared with practical conditions of worldwide and local markets to establish their viability. The methodology provides a framework for evaluating potential partners when attempting to enter foreign markets. Additionally, it identifies critical factors for developing optimal market entrance strategies, contracts, and risk management; results can also be golcally (globally and locally) tailored to promote the efficiency of international cooperation

An analytical study of critical factors affecting contractor efficiency in construction projects in Indian scenario

Purpose: Recent studies show that lowest bidder technique is mainly used in developing countries such as India to award a contract. It has been demonstrated that the lowest bid is not always the accurate one and can lead to cost overruns and time extensions amongst other problems. The aim of this study was to investigate the critical factors impacting contractor’s efficiency in Indian construction projects. Research approach: A survey was sent to participants of construction projects awarded by the government with the lowest bidder technique in Uttar Pradesh, India. For further research, snowball sampling was used, and structured interviews were conducted amongst experienced managers and engineers of these projects on both client’s and contractor’s side. Findings: It was observed that, to a greater extent, the delays were caused due to contractor’s opportunistic behaviour. The main findings are that new bidding methodologies are to be tested as they can lead to the choice of a more accurate and realistic bidder. In addition, subjective evaluation components, such as schedule and workforce, should be reflected in contract award methods in addition to the cost criteria. Further studies should be performed on the choice of contract awarding methodology based on the project size and type. Originality value: The researcher’s focus was to analyze the influence of contracting methodologies and factors affecting contractor’s performance in lowest bid award project, where this is an area of least focus amongst researchers in the Indian subcontinent