This research aims to determine and analyze the extent of the influence of community empowerment and sustainability-oriented innovation on sustainable performance through coworking spaces in the city of Bandung. To achieve the research objectives, a deductive approach is employed, intending to test a hypothesis to strengthen or reject existing hypotheses. Therefore, this research is also categorized as explanatory research. The research method used is the survey research method. The research sample is determined based on proportional stratified random sampling. This study focuses on business groups in coworking spaces in the 28 districts of Bandung City, with a total of 408 business operators. The sample selected consists of 208 business operators. Based on the research results, several conclusions are drawn, as follows: (1) Community empowerment has a significantly positive influence on sustainability performance, with a contribution of 84.5%; (2) Sustainability-oriented innovation has a significantly positive influence on sustainability performance, with a contribution of 69.2%; (3) Community empowerment has a significantly positive influence on Coworking Space, with a contribution of 93.6%; (4) Sustainability-oriented innovation has a significantly positive influence on Coworking Space, with a contribution of 36%; (5) Community empowerment has a significantly positive influence on sustainability-oriented innovation, with a contribution of 90.6%; (6) Coworking Space has a significantly positive influence on sustainability performance, with a contribution of 34%; (7) Community empowerment has a significantly positive influence on sustainability performance through Coworking Space, with a contribution of 20.7%; and (8) Sustainability oriented innovation has a significantly positive influence on sustainability performance through Coworking Space, with a contribution of 12.2%.

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.

What personal competences of successful project managers are determined by their former career as an elite athlete? To answer the question, comprehensive research is carried out, implemented as part of the EEIG-EU/P-Kr/06.12/23 project. The primary aim is to establish conclusively which particular personality traits, identified and analysed using the Big Five Inventory-2 and supplemented by structured interviews, directly contribute to the success of former elite athletes transitioning into roles as effective project managers. We found that successful project managers who were also elite athletes possess personality traits that can be identified as positive determinants of success in either sport or professional careers. Among these personality traits, we can include a low level of neuroticism and a high level of conscientiousness, then extraversion and agreeableness. This paper contributes to a nuanced understanding of how the realms of sports and management intersect and overlap. The presented paper can serve as a basis for further research in the field of personality psychology and management studies.

This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.

This study aims to examine whether banks are compliant with adopting sustainability regulations and guidelines, and how they disclose their sustainable finance activities in sustainability reporting by providing case of Indonesian banking. Previous research provided discussions on the role of governance in supporting many variables as quantitative studies, but failed to demonstrate on going practices of how banking industries implement sustainable finance governance. Hence, this study provides originality by analyzing the extend of disclosures in order to evaluate their commitments in responding to sustainability regulations and guidelines, through disclosures of economic, environment, social, and governance (EESG) information in annual and sustainability reports. The samples were undertaken by examining the contents of sustainability and annual reports published for the financial year 2016 to 30 June 2021, for the Indonesian banks listed in business category 4, business category 3, and international banks, with the total of 202 reports. The results indicate that the implementation of sustainable finance in EESG information increases annually with social performances are the highest information disclosed, while the governance and economic information received the lowest level of disclosure. Results of this study will benefit policymakers, banks, and related companies to understand sustainable finance governance, and reveal the importance the role of banking industries to support Sustainable Development Goals (SDGs). Providing the insights of the ongoing discussions are expected to suggest following actions for further policies to support the implementation of sustainable finance, in particular to establish sustainability governance as a foundation of commitments, beyond complying to regulations.

This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.