Professional judgments in business valuation should be based on persuasive comparative data and conclusive empirical studies. However, these judgments are frequently made without these conditions, causing professional skepticism. An appraiser should explain in detail what was done to get the market value because valuation is the initial crucial step in the investment decision process. In socially responsible investment schemes, an appraiser has a fiduciary duty and a vital role in protecting the public from fraud and the risk of asset value destruction. Professional skepticism is essential to direct the appraiser’s judgment towards independent valuation for the public interest, assisting in evaluating the relevance and reliability of information, especially relating to social, environmental, and ethical issues. This paper studies the business valuation process from a behavioral finance perspective in the United States and Indonesia, aiming to tweak business valuation practices, identify biases, and mitigate them to ensure the market value does not shift far from fairness opinion. The case study explores experiences from the professional role-learning process. The results highlight the need for an appraisal protocol in business valuation, improvements in the discount for lack of marketability application, and these findings are pertinent to business appraisers and regulators. Recommendations include enhancing the clarity of professional judgments and the integration of recent empirical studies into practice.

This financial modelling case study describes the development of the 3-statement financial model for a large-scale transportation infrastructure business dealing with truck (and some rail) modalities. The financial modelling challenges in this area, especially for large-scale transport infrastructure operators, lie in automatically linking the operating activity volumes with the investment volumes. The aim of the paper is to address these challenges: The proposed model has an innovative retirement/reinvestment schedule that automates the estimation of the investment needs for the Business based on the designated age-cohort matrix analysis and controlling for the maximum service ceiling for trucks as well as the possibility of truck retirements due to the reduced scope of tracking operations in the future. The investment schedule thus automated has a few calibrating parameters that help match it to the current stock of trucks/rolling stock in the fleet, making it to be a flexible tool in financial modelling for diverse transport infrastructure enterprises employing truck, bus and/or rail fleets for the carriage of bulk cargo quantifiable by weight (or fare-paying passengers) on a network of set, but modifiable, routes.