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The purpose of this paper is to present a new approach in viewing the control of safety at crude oil exploration platforms.

The approach utilized in this work is the fusion of artificial neural network and fuzzy logic. The approach is adopted in view of the better presentation of solutions to the safety control problem that neuro‐fuzzy exhibits. It is better than the individual application of either artificial neural network or fuzz logic to the problem at hand. The model captures uncertainties and imprecision that are prevalent in the quantification or data gathering stage of safety control measurement.

It was demonstrated that the application of neuro‐fuzzy is feasible. The results seem applicable to similar settings with similar system characteristics.

Since more confidence is obtained with the use of this more effective tool, there is improvement in decision making based on reliance on the model. Thus, the improved quality of decision made would positively affect lives of workers at the oil platforms or the materials or equipment used for exploration purposes.

The work is original in that it is the first time the neuro‐fuzzy methodology would be applied to offshore oil platform safety control.

This paper aims at developing a methodology capable of controlling accidents and failures in oil and gas production activities.

Fuzzy analysis that is based on fuzzy linguistics, rule matrix, rule structures, and system operating rules is utilised. Fuzzy methodology is applied to develop a safety control model for the prevention of accidents and failures in oil and gas production activity offshore platforms.

The model is demonstrated with a case study, thereby suggesting the feasibility of the applied approach in practical cases.

Primarily, the study aims to guarantee safety. Also uncertainties and imprecision that commonly characterize safety measurement systems are tracked. The time‐consuming activity in measurement and the requirement of lots of specific information about the process is avoided.

The results from the study provide valuable baseline information for future research investigating how safety of oil platforms is affected by some factors.

Over the past several decades, the need for safety on offshore oil platforms has attracted significant attention from all its stakeholders. This paper seeks to present a mathematical model that could be used to control unsafe conditions on oil platforms.

The model is based on the intuitive notion of safety underlying practices on an offshore platform. The theory of control system combines the human/operator factor gain, maintenance function effectiveness, the component safety quality assurance system, and the safety measurement system in a holistic manner to attain a controlled status of the oil platform.

It is observed that these components relate in a mutually interlinked system that guarantees maximum safety control if all the components are holistically managed.

Practically, the control of an offshore oil platform guarantees the lives and properties of those who utilize the oil platform.

The work is perhaps the first to advance a model of safety on oil platforms with the use of control systems. The work would be of value to safety managers, employees of oil companies and researchers interested in the control of accidents on oil platforms.

This paper aims to explore business relationship framework between two companies. In this research, relationship marketing and transaction cost were used as frameworks to analyze business relationship of two different kinds of companies in Indonesia, oil company and hypermarket. Gronroos (1994) defines relationship marketing is establishing, maintaining and enhancing relationships with customers and other partners, at a profit, so that the objectives of the parties involved are met. This is achieved by a mutual exchange and fulfillment of promises. This definition is a key to analyze the relationship of retailer and their supplier. In contrast, Williamson (1980) argued that relationship in business organization is based on their economic interest, and this approach is known as transaction cost approach. In this kind of relationship, business organizations consider cost and benefit of business relationship.

The design of this study is triangulation. Two approaches were used to answer the research questions. A survey involving 204 respondents was conducted. These are companies in Indonesia oil and gas and retail industries. The types of power of those companies were analyzed using descriptive statistic and paired t test. Also, case study was conducted to gain depth information of two companies, with a large number of business partners among the respondents. The design of case study is holistic case study.

The result shows that, in the oil company, the relationship between a company and their supplier is tied on a strict contract. In fact, the relationship of supplier and company in a fuel company based on transaction cost theory. In the retail company, the relationship of supplier and retailer based on trust, commitment and satisfaction. Those three construct are the foundation of relationship marketing. Companies in those two industries tend to use non-coercive power to influence their business partners.

This study analyzes type of business relationship in industries in emerging markets. It also discusses type of influence strategy used by companies to control their business partners to gain mutual benefit.

Despite efforts to improve safety management practices in industrial companies, major accidents seem to be inevitable. Many accidents still occur because companies are unable to learn from past occurrences due to ineffective incident and accident learning processes. This study proposes a learning-based framework for industrial accidents investigation and contributes to accident prevention research.

The proposed learning process includes the analysis of the industrial accident using the Event Tree Analysis (ETA) method, capitalisation of causative factors using the Swiss Cheese Model (SCM), and finally modelling the relationships among the accident causative factors and analysing their causality using the Fuzzy Cognitive Mapping (FCM) technique and running learning scenarios.

The proposed learning process was applied to an industrial accident, and the results showed that human unsafe behaviours and unsafe supervision were the principal causative factors of the blowout accident.

The proposed learning-based framework provides a structured approach for oil and gas companies to systematically analyse and learn from past accidents, enhancing their prevention strategies. Theoretically, the framework bridges the gap between theory and practice by demonstrating how established accident analysis methods can be combined and applied in a real-world industrial context.

The proposed learning process combines accident analysis and investigation techniques with simulations for an in-depth and robust learning-based framework for accident prevention.