Smallholder cocoa producers often experience low productivity levels, partly due to their weak collaborative advantage (CA). CA enables businesses to optimize outcomes through effective collaboration within value chains. This paper aims at examining the effect of CA pillars (trust building, resource investment, and decision synchronization) on the productivity. This paper uses primary data of 406 samples from smallholder cocoa producers in Indonesia. The data is analyzed by using CDM (Crepon Duguet Mairesse) model that divides the CA process into three stages: effort, output, and productivity. In the first stage, our model shows that having motivation to collaborate positively affects collaborative effort expenditure to develop a CA. In the second stage, the study finds that the three pillars of CA have to some degree contributes to achieving a better access to finance, superior cocoa seeds, and cocoa processing technology for smallholder cocoa producers. In the third stage, acquiring the outputs of CA leads to productivity improvement. The findings underscore the significance of intangible factors in shaping robust Collaborative Advantage (CA) and influencing productivity. This enriches CA theory, which has traditionally focused primarily on tangible factors.

The rapid advancement of artificial intelligence (AI) technology is profoundly transforming the information ecosystem, reshaping the ways in which information is produced, distributed, and consumed. This study explores the impact of AI on the information environment, examining the challenges and opportunities for sustainable development in the age of AI. The research is motivated by the need to address the growing concerns about the reliability and sustainability of the information ecosystem in the face of AI-driven changes. Through a comprehensive analysis of the current AI landscape, including a review of existing literature and case studies, the study diagnoses the social implications of AI-driven changes in information ecosystems. The findings reveal a complex interplay between technological innovation and social responsibility, highlighting the need for collaborative governance strategies to navigate the tensions between the benefits and risks of AI. The study contributes to the growing discourse on AI governance by proposing a multi-stakeholder framework that emphasizes the importance of inclusive participation, transparency, and accountability in shaping the future of information. The research offers actionable insights for policymakers, industry leaders, and civil society organizations seeking to foster a trustworthy and inclusive information environment in the era of AI, while harnessing the potential of AI-driven innovations for sustainable development.

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.

Objectives: This research aimed to empirically examine the transformative impacts of Artificial Intelligence (AI) adoption on financial reporting quality in Jordanian banking, with internal controls as a hypothesized mediation mechanism. Methodology: Quantitative survey data was collected from 130 bank personnel. Multi-item reflective measures assessed AI adoption, internal controls, and financial reporting quality—structural equation modelling analysis relationships between constructs. Findings: The research tested four hypotheses grounded in agency and contingency theories. Confirmatory factor analysis demonstrated sound measurement models. Structural equation modelling revealed that AI adoption significantly transformed financial reporting quality. The mediating effect of internal controls on the AI-quality relationship was supported. Specifically, the path from AI adoption to quality was significant, indicating a positive impact. Despite internal controls strongly predicting quality, its mediating effect significantly shaped the degree of transformation driven by AI adoption. The indirect effect of AI on quality through internal controls was also significant. Findings imply a growing diffusion of AI applications in core financial reporting systems. Practical implications: Increasing AI applications focus on holistically transforming systems, reflecting committing adoption. Jordanian banks selectively leverage controls to moderate AI-induced transformations. Originality/value: This study provides essential real-world insights into how AI is adopted and impacts the Jordanian banking sector, a key player in a fast-evolving developing economy. By examining the role of internal controls, it deepens our understanding of how AI works in practice and offers practical advice for integrating technology effectively and improving information quality. Its mixed methods, unique context, and focus on AI’s impact on organizations significantly enrich academic literature. Recommendations: Banks should invest in integrated AI architectures, strategically strengthen critical controls to steer transformations, and incrementally translate AI innovations into core processes.

This study aims to empirically analyze the impact of budget allocation by the Korea Institute of Science and Technology Information (KISTI) on national research competitiveness, thereby reassessing the value of investing in research infrastructure within a knowledge-based society. In the 21st century, research and development (R&D) have emerged as a pivotal element of national competitiveness, underlining the increasing importance of investments aimed at constructing and enhancing research infrastructure. However, empirical studies examining the causal relationship between research infrastructure investment and national research competitiveness are still notably scarce. Accordingly, this research endeavors to systematically delineate the effect of research infrastructure investment, with a focus on KISTI’s budget allocation, on enhancing national R&D outcomes. To achieve this, the structural relationship between KISTI’s budget, national R&D budget, and various academic and industrial performance indicators was analyzed using multiple regression and simple regression analysis. In particular, by demonstrating the mechanism through which the budget management of research support organizations like KISTI contributes to strengthening national research competitiveness, this study aims to shed new light on the strategic value of research infrastructure investment in a knowledge-based society. Furthermore, these findings are expected to provide valuable evidence for the formulation of national R&D policies in Korea and the strategic planning of budget operations for research support organizations. Through strategic investment of limited budgets, this could enhance the efficiency of national R&D investments and contribute to strengthening the capacity for scientific and technological innovation required in a knowledge-based society.

The main objective of this study is to identify the impact of trust on the construction of corporate value in commerce and services microbusinesses. This work is based on identifying the challenges faced by SMEs (Small and Medium-sized Enterprises), which are conditioned by the type of business and the regulatory and incentive variables that exist in the territory, affecting their permanence and stability in the market and their financial and commercial development. A local study is carried out in Bogotá, Colombia, through a descriptive research project, using a quantitative analysis method (SPSS) to process data obtained from local microbusinesses. As a result, it was observed that trust has a discrete impact on the creation of corporate value, which is created from the use of ICT (Information and Communication Technology). This leads to the recognition that it is necessary to strengthen horizontal networks with suppliers, clients, and similar businesses, as well as vertical networks with entities and public associations, to generate lasting and strong links that increase the competitiveness of these business units in the face of exogenous risks shaped by the social, economic, and cultural characteristics of the territory, which are increasingly conditioned to the use of communication technology.