High-value Activities Research Articles

Open Brain AI and language assessment.

Neurolinguistic assessments play a vital role in neurological examinations, revealing a wide range of language and communication impairments associated with developmental disorders and acquired neurological conditions. Yet, a thorough neurolinguistic assessment is time-consuming and laborious and takes valuable resources from other tasks. To empower clinicians, healthcare providers, and researchers, we have developed Open Brain AI (OBAI). The aim of this computational platform is twofold. First, it aims to provide advanced AI tools to facilitate spoken and written language analysis, automate the analysis process, and reduce the workload associated with time-consuming tasks. The platform currently incorporates multilingual tools for English, Danish, Dutch, Finnish, French, German, Greek, Italian, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, and Swedish. The tools involve models for (i) audio transcription, (ii) automatic translation, (iii) grammar error correction, (iv) transcription to the International Phonetic Alphabet, (v) readability scoring, (vi) phonology, morphology, syntax, semantic measures (e.g., counts and proportions), and lexical measures. Second, it aims to support clinicians in conducting their research and automating everyday tasks with "OBAI Companion," an AI language assistant that facilitates language processing, such as structuring, summarizing, and editing texts. OBAI also provides tools for automating spelling and phonology scoring. This paper reviews OBAI's underlying architectures and applications and shows how OBAI can help professionals focus on higher-value activities, such as therapeutic interventions.

Robotic Process Automation in Banking for Better Customer Experience

Robotic Process Automation (RPA) has emerged as a transformative technology in the banking sector, offering opportunities to streamline operations, reduce costs, and enhance customer experiences. This explores the impact of RPA implementation on customer experience within the banking industry. By automating repetitive, rule-based tasks such as account maintenance, loan processing, and customer inquiries, banks can significantly improve operational efficiency and accuracy while freeing up human resources to focus on higher-value activities. Furthermore, we discuss the challenges and considerations associated with RPA adoption in banking, including data security, regulatory compliance, and employee upskilling. Ultimately, this underscores the pivotal role of RPA in reshaping the banking landscape, driving innovation, and delivering superior customer experiences in an increasingly digital world.

Design and Development of Automated Control of Restaurant Robot

This paper presents a novel voice-controlled restaurant robot system designed to revolutionize the dining experience by seamlessly integrating advanced robotics and natural language processing technologies. The proposed system aims to enhance customer service, operational efficiency, and overall dining satisfaction by providing a user-friendly and interactive platform. .The restaurant robot is equipped with a comprehensive set of capabilities, including, voice recognition and manipulation. By leveraging voice control, users can interact with the robot using natural language commands, enabling seamless communication and intuitive control. This allows customers to effortlessly place orders The system's is comprises a mobile robotic platform, bluetooth modules, a cloud-based natural language processing, The voice control functionality is implemented through a sophisticated speech recognition system, enabling the robot to accurately understand and interpret user commands. .In addition to customer-facing interactions, the restaurant robot also assists restaurant staff in various tasks. Deliver food and beverages to tables, handle payment transactions, and perform routine cleaning tasks. By automating these processes, the system improves operational efficiency, reduces labor costs, and allows human staff to focus on highervalue activities such as customer engagement and culinary expertise. .To evaluate the performance and usability of the voice-controlled restaurant robot, a series of experiments were conducted in a real-world restaurant environment. The results demonstrated the system's high recognition accuracy, robustness in noisy environments, and its ability to effectively handle a wide range of user requests. .The proposed voice-controlled restaurant robot presents a promising solution for transforming the dining experience. It combines the convenience of voice control with advanced robotics, enabling seamless and interactive interactions between customers, staff, and the robotic platform. The system's ability to enhance customer service, operational efficiency, and overall dining satisfaction positions it as a significant advancement in the hospitality industry.

A Study to Know the Role of AI and Sustainability in Agriculture

Artificial intelligence (AI) has become an increasingly important tool in agriculture, providing farmers with innovative solutions to improve productivity, efficiency, and sustainability. Using AI-powered tools such as drones, sensors, and machine learning algorithms, farmers can gather and analyze data about soil health, crop growth, and weather patterns to make informed decisions and optimize their operations. AI has the potential to transform agriculture by enabling more precise and targeted applications of fertilizers, pesticides, and other inputs, reducing waste, and increasing yields. It also has the potential to reduce the environmental impact of agriculture by minimizing the use of harmful chemicals and promoting sustainable farming practices. Additionally, AI can assist in the automation of tedious and repetitive tasks, freeing up farmers to focus on more strategic decision-making and higher-value activities. This can also help to address labor shortages in the agriculture sector, particularly in countries with aging populations or where traditional agriculture work is seen as less desirable. Overall, the use of AI in agriculture has the potential to revolutionize the industry, making it more efficient, sustainable, and profitable while also ensuring that we can continue to feed a growing global population in a responsible and sustainable manner. Keyword: Artificial Intelligence, AI in Agriculture, AI and Agriculture, Sustainable Farming, AI application in Agriculture

The Impact of Artificial Intelligence on the Accounting Profession: A Concept Paper

This study examined the impact of artificial intelligence (AI) on the accounting profession. It systematically investigated the effects of AI technologies on the accounting field, redefining the roles and responsibilities of accountants. Through literature review, this study sheds light on AI influence on the accounting profession. The results of this study indicate that the impact of AI on accounting profession can be divided into three themes: (i) automation of routine tasks, (ii) enhanced data analysis, and (iii) value-adding of the professional roles. The automation of routine tasks includes data entry, validation, and transaction processing, while enhanced data analysis includes predictive analytics and decision support. AI also has impacted in terms of value-adding of the professional roles, which comprise of increasing scalability and cost savings and focus on higher value activities. The findings of this study suggest that the accounting profession is evolving in response to AI technology, and accountants should embrace these changes to harness the full potential of AI in their work.

Upgrading through global, regional or national value chains? Firm-level evidence from the East African textiles & apparel sector

This paper introduces the concept of value chain directionality to investigate how orientation to different value chains has implications for productive learning and industrial outcomes. We develop and test this concept building on a purposefully designed firm-level survey focused on the textile and apparel value chain in East Africa. Tanzanian and Kenyan textiles and apparel firms lie on a spectrum in terms of their engagement with national, regional and global value chains (NVCs, RVCs and GVCs), with outcomes varying with value chain directionality. GVC firms focus on a narrow range of lower-value functions (mostly garment assembly) while RVC and NVC firms perform a wider range of functions including vertical integration to textile manufacture and higher-value activities such as design and branding, but cases of functional upgrading were rare in all groups. GVC firms were closer to the technological frontier, but RVC and NVC firms were similarly engaged in process upgrading. GVC firms tended to have more complex products than RVC and NVC firms, and only GVC firms had recently engaged in product upgrading. Crucially, results in the area of end market upgrading confirmed the hypothesis that RVCs have the potential to serve as ‘learning grounds’, or ‘stepping stones’ to more demanding but potentially lucrative global markets. In other outcomes, GVCs appear to offer greater prospects for rapid employment generation but RVCs and NVCs tend to favour backward integration by incorporating more locally sourced inputs.

THE IMPACT OF AI ON INTERNAL AUDITING: TRANSFORMING PRACTICES AND ENSURING COMPLIANCE

Artificial Intelligence (AI) is revolutionizing internal auditing by transforming traditional practices and enhancing compliance mechanisms. This abstract explores the multifaceted impact of AI on internal auditing, highlighting key advancements in efficiency, accuracy, risk management, and regulatory adherence. AI technologies, particularly machine learning and advanced data analytics, are enhancing the capabilities of internal auditors to analyze large volumes of data swiftly and with greater precision. Traditional internal auditing methods, often constrained by manual processes and sampling techniques, are being supplanted by AI-driven approaches that offer comprehensive analysis and real-time insights. This shift enables auditors to identify anomalies, fraud, and operational inefficiencies more effectively, thereby improving the overall accuracy and reliability of audit outcomes. One of the significant benefits of AI in internal auditing is its ability to automate routine and repetitive tasks. By leveraging AI, auditors can focus on higher-value activities, such as strategic risk assessment and decision-making, thus enhancing the overall productivity of the audit function. Furthermore, AI-driven tools can continuously monitor financial transactions and operational processes, providing real-time alerts and insights that help in early detection of potential issues and proactive risk management. AI also plays a crucial role in ensuring compliance with regulatory standards. By integrating AI systems with compliance frameworks, organizations can automate the tracking and reporting of compliance-related activities. This not only reduces the risk of human error but also ensures that organizations stay updated with evolving regulatory requirements. AI’s ability to process and analyze regulatory texts enables organizations to swiftly adapt to new compliance mandates, thereby mitigating the risk of non-compliance penalties. However, the integration of AI into internal auditing is not without challenges. Ensuring data quality and integrity is paramount, as AI systems rely on accurate data inputs to function effectively. Additionally, the "black box" nature of some AI algorithms can pose transparency issues, making it difficult for auditors to explain how specific conclusions were reached. Addressing algorithmic biases and maintaining auditor expertise in AI technologies are also critical considerations. In conclusion, AI is significantly transforming internal auditing practices by enhancing efficiency, accuracy, and compliance. While the benefits are substantial, careful management of data quality, transparency, and algorithmic biases is essential to fully realize the potential of AI in internal auditing. Keywords: Impact, Ai, Internal Auditing, Transforming Practices, Ensuring Compliance.

Structural Change and Economic Growth in Visegrad and South Caucasian Countries

This paper investigates the effect of the change in the economic structure on economic growth in Visegrad and South Caucasia. The Shift Share Analysis (SSA) method measures the direct effects of structural change on productivity growth. Fully Modified OLS (FMOLS) regressions evaluate the indirect effect of the advanced sectors on economic growth. SSA finds that within sector productivity is the main driver of economic growth in both regions and the manufacturing sector is the engine of within sector productivity growth in Visegrad countries. Expansion of the modern business services sector produced a positive reallocation effect in all countries but the lack of growth dynamism in the productivity of this sector undermined the positive reallocation effect in Hungary and Slovakia. The FMOLS regressions show that manufacturing export has a positive effect on economic growth while business service production does not. The general structure of Visegrad economies is similar to advanced countries and they can achieve further development by upgrading their production within advanced sectors while South Caucasian countries can develop their economies by expanding the high-value sectors and channeling the excess labor in low-value sectors to relatively higher value activities. Both strategies require investment in human capital and upgrading their domestic capacity.

Artificial Intelligence (AI): Revolutionizing Digital Marketing

Artificial intelligence (AI)-enabled digital marketing is revolutionizing the way organizations create content for campaigns, generate leads, reduce customer acquisition costs, manage customer experiences, market themselves to prospective employees, and convert their reachable consumer base via social media. Real-world examples of organizations who are using AI in digital marketing abound. For example, Red Balloon and Harley Davidson used AI to automate their digital advertising campaigns. However, we are early in the process of both the practical application of AI by firms broadly and by their marketing functions in particular. One could argue that we are even earlier in the research process of conceptualizing, theorizing, and researching the use and impact of AI. Importantly, as with most technologies of significant potential, the application of AI in marketing engenders not just practical considerations but ethical questions as well. The ability of AI to automate activities, that in the past people did, also raises the issue of whether marketing professionals will embrace AI as a means to free them from more mundane tasks to spend time on higher value activities, or will they view AI as a threat to their employment? Given the nascent nature of research on AI at this point, the full capabilities and limitations of AI in marketing are unknown. This special edition takes an important step in illuminating both what we know and what we yet need to research.

Editorial and News

Editorial and News

Waste Not: Can Household Biogas Deliver Sustainable Development?

Household biogas systems are a renewable energy technology with the potential to provide sustainable development benefits by reducing pressure on forest stocks and by shifting household time allocation towards higher value activities or long-term investments in human capital. We estimate the environmental and socioeconomic impacts of biogas expansion in Nepal using an instrumental variables approach that exploits conditional variation in access to biogas installation companies. We confirm prior evidence that biogas use significantly reduces collected fuelwood, estimating changes of approximately 800–2000 kg per year per household. We find new evidence that biogas saves time in fuelwood collection (23–47%), and results in reallocation of time away from home production and wage labor towards agricultural labor and education. We find that biogas reduced forest cover loss in the Hill region and when combined with other forest protection policies. Together the results suggest that biogas can contribute modestly to sustainable development, particularly in combination with complimentary opportunities or policies.

Domestic Demand-driven Growth: Analytical Perspectives and Statistics Needed

Given the imbalances in global demand and sluggish growth in the advanced economies, which had absorbed the bulk of world exports before the onset of the 2008/09 global financial crisis (GFC), the shift from export-led growth (ELG) strategies to domestic demand-driven growth (DDDG) strategies appears inevitable for export-oriented economies. In dissecting Malaysia's growth performance into various demand components and sources, it was found that DDDG in Malaysia had helped to offset the weak export demand it had faced over the last decade and, importantly, during the post-GFC years. Using input-output tables to assess the changes in output structure arising from substituting current export demand with domestic demand, the analysis showed that the country's high export orientation in a large number of industries precludes its ability to fully offset any sharp decline in exports. The implication is that DDDG can only effect a partial decoupling from external demand and that given the differences in the composition of export and domestic demand, there will be sectoral differences in the impact on industrial capacity, employment and income arising from the ELG-DDDG shift. In cross-country comparisons, Malaysia's 'apparent' under-consumption and low private investment levels, in concert with its narrowing but still positive savings-investment gap, lend further support to the feasibility and desirability of promoting DDDG to support economic growth. Importantly, DDDG is sustainable only if it maximizes economic efficiency and utilization of resources, skills, human capital, and physical and social infrastructures subject to structural, credit and other constraints. On the consumption side of DDDG, a higher level of spending by the middle and upper income groups will need to be elicited while the income of the low income groups will need to be boosted. Private investment, regardless of domestic or foreign sources or DDDG versus ELG orientation, will be one of the key drivers of DDDG, given the excess savings in the private sector as well as the capacity expansion and productivity growth associated with gross fixed capital formation. Some evidence of lower productivity growth in domestic-oriented industries compared to export-oriented ones reiterates the need for policy measures to boost productivity as part of the DDDG thrusts. Based on a suggested DDDG framework, whereby the fundamental sources of economic growth emanate from output and structural shifts to higher value activities, productivity increases and institutional quality improvements, the statistical needs are examined for each of the four suggested strategic DDDG thrusts. The paper reiterates that DDDG should not be viewed as a substitute for export-led growth (ELG) strategies. Rather, by harnessing the complementarities of the two paradigms, Malaysia can capture the growth opportunities arising from an upswing in external demand while mitigating the adverse effects on output and employment due to volatile export markets by strengthening the resilience of domestic demand.

A ‘China-Plus-One' strategy: The best of both worlds?

This paper offers a conceptual analysis of the widely discussed idea of a China-Plus-One strategy which refers to the practice of international businesses active in China coupling their investments with a second facility, generally in another Asian economy. The key finding is that a China-Plus-One strategy appears to be beneficial to both firms that seek to pursue it for reasons of risk diversification, cost reduction or avoidance of overreliance on China, for China in that it frees up resources which can be applied to other higher value activities, and for Plus-One host economies which gain the benefits of inward investment. The contribution of the article is in integrating a fragmented business literature, providing a coherent academic framework, in isolating direct and indirect impacts, in identifying the costs of a China-Plus-One strategy, and in integrating company examples. Testable propositions regarding the characteristics of firms more likely to pursue a China-Plus-One strategy are also developed.