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This paper aims to study the bibliometric analysis of resource orchestration research in management and businessareas.

The research method is based on a three-step protocol of dataset setting, dataset refining and analyzing the data. First, the 202 published articles in the resource orchestration field were collected from the Web of Science database. Second, the document information was refined. Finally, we used the bibliometric analysis toolbox to investigate the documents. Also, bibliometric analysis in this research has been conducted using VOSviewer and SPSS software.

The findings of this research examined the evolution of the resource orchestration theory. Also, this paper has identified five major themes in this field: resource orchestration for entrepreneurship and innovation, orchestrating supply chain, orchestrating information technology resources, orchestrating intangible resources and the role of resource orchestration in small firm performance. Finally, emerging trends in the resource orchestration area include sustainable development, innovation and information technology.

This paper is the first to use bibliometric analysis to examine resource orchestration theory. Accordingly, this research contributes to the resource orchestration area through the theoretical evolution, underlying streams of research and emerging themes in research topics and methodologies.

The purpose of this study is to address why managers enter the excessive market. A comparison of the facts and perceptions of entrants relative to success in the market shows that many entrants are confident about the viability of their businesses and enter the market. Accordingly, the authors simulate market entry decisions to detect behavioral biases.

The authors adapted the entry decisions simulation method, which is supported by the theoretical foundations of signal detection theory (SDT) and signaling theory. The simulation model is implemented on the Anaconda platform and written in Python 3.

The results of this study suggest that overestimation relates to excess market entry. Also, the proportion of excess entry under difficult conditions is always higher than under easy conditions.

This research helps managers and firms think about their and their competitors' abilities and evaluate them before entering the market. Policymakers and practitioners can also design programs such as experiential learning to help entrants assess their skills.

So far, no research has investigated the role of overconfidence under different market conditions. Accordingly, this study contributes to the current market entry literature by disentangling the debate between absolute and relative confidence and by considering the role of task difficulty.