Fitri Trapsilawati

According to an upstream oil and gas company’s report in Indonesia, over 80% of contractual sanctions issued stem from vendors failing to meet commitment obligations. Consequently, this study aims to provide vendor management strategy recommendations by analyzing variables significantly correlated with vendor commitment fulfillment in contracts. This paper presents an empirical investigation of variables influencing vendor commitment fulfillment in upstream oil and gas operations, including vendor development programs, technical capabilities, satisfaction metrics, and operator influence strategies. Research data were collected from 100 vendors representing diverse company classifications, business segments, and commodity specializations. Eight hypotheses were developed using prior industry studies and best practice references. These hypotheses were tested via Partial Least Squares-Structural Equation Modeling (PLS-SEM) methodology. The analysis confirms that vendor technical capabilities and satisfaction levels exhibit significant direct relationships with commitment fulfillment. Vendor development programs demonstrate no direct significant relationship; however, an indirect relationship emerges when technical capabilities act as a mediating variable, indicating that development initiatives substantially enhance fulfillment through capability improvement. The study further establishes that vendor development directly strengthens technical capabilities.

The complex tasks of air traffic control (ATC) and the various factors affecting its operation have shed light on the need to build a model to predict conflict detection and resolution (CDR) performance within a traffic situation. This study aimed at developing a fuzzy-hybrid framework for quantifying various aspects in ATC consisting of the software, hardware, environment, liveware and organisation (i.e. the SHELL model) to predict CDR performance. The proposed fuzzy-hybrid SHELL framework in this study was tested using metadata from 10 prior studies in ATC. The results showed a highly accurate prediction, as indicated by the RMSE and MAPE values of 0⋅09 and 5⋅36%, respectively, indicating a high consistency of 90⋅92% for predicting the CDR performance. This framework offers a promising approach for Air Navigation Service Providers (ANSPs) to maintain air traffic safety and improve ATC operations efficiency.

Small and medium-sized enterprises (SMEs) are contributors to economic growth. Many studies have mentioned a broad range of factors that influence the development of SMEs. However, studies examining SME growth between developed and developing countries have not been comprehensively investigated. The growth of SMEs relies on the entrepreneurial skills of the entrepreneur, who has the ability to manage business effectively, achieve profit, identify market opportunities, and enhance innovation by optimizing all available resources. The objective of this article was to synthesize the factors that influence the growth of small and medium-sized enterprises (SMEs) across developed and developing countries. This study particularly synthesized interrelationship factors depicted in a framework addressing resources and capabilities for SME growth. A systematic literature review (SLR) was employed to examine the research activities on this topic, referring to 108 articles from the Scopus and Web of Sciences databases. The articles synthesized individual studies to analyze the trend of SME growth research in developed and developing countries. Next, the factors of SME growth were identified into 6 (six) categories, including human capital resources, entrepreneurial perspectives on marketing, innovation, SMEs partnership, technology, and entrepreneur personality. The result represents that the factor extensively studied concerning SME growth is innovation capability, both in developed and developing countries. Differences exist in both critical factors and interrelationships among factors in developed and developing countries, particularly in the innovation capability, SME partnership and marketing capabilities.

The latest global air traffic shows a positive sign of a tremendous recovery in worldwide air traffic post-pandemic. This paper aims at providing a systematic literature review on air traffic conflict detection and resolution (CDR) in air traffic control (ATC) from ergonomics perspectives and developing a framework underlying the CDR processes to retort the bounce-back of air traffic density. A preferred reporting item for systematic reviews and meta-analyses (PRISMA) was adopted to conduct the review of prior publications in ATC CDR. Based on the 35 literatures reviewed, a framework of CDR is produced highlighting the key aspects of ATC as a sociotechnical system including humans, environment, interface/system, and task. The present study also sheds light on future research directions covering acceleration of ATC proficiency, design of ATC systems, analysis of global traffic patterns, ATC automation transparency, and task designs to enhance air traffic safety and efficiency. The take-away points from the growing body of literatures on ATC CDR are discussed further in this paper.

This study aimed to model group preference decision-making to implement Industry 4.0 on food and beverage small- and medium-sized enterprises (SMEs). An ant colony optimisation was adopted to model the decision-making process based on the travelling salesman problem. The model was demonstrated on three preferences of Industry 4.0, namely, ergonomic work methods, machineries and tools, and e-commerce and promotion. The Likert-scale Kansei words data were obtained from 120 SMEs’ manager in Indonesia. The data were then plotted to Cartesian coordinates with the x and y-axes showing the mode and average values, respectively, and were simulated in a sequence using ACO. The results indicated that machinery and tools were the most preferred to implement Industry 4.0. Adaptiveness was the most preferred attribute in making the first decision. The benchmarking demonstrated ACO performed better than genetic algorithm in modelling group preference. The group preference was also compared to trust level and the finding showed a high correlation between both constructs. The high trust in the group preferences is expected to contribute for the sustainability of Industry 4.0. The method enriches various existing theoretical approaches for group preference decision-making and applicable to assist the SME’s management for implementation of Industry 4.0.