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This study aimed to determine the impact of Business Intelligence (BI) applications on accounting department contributions to the development and quality assurance of university accounting education in Jordan. A questionnaire was given to accounting faculty members in 25 universities, and the results showed that BI applications had a significant effect on the development and quality assurance of university accounting education. Private universities had a greater impact than public universities. Recommendations of this study include improving awareness of BI applications, focusing on decision support systems in private universities and risk analysis in public universities, and promoting cooperation between public and private universities to achieve excellence in an increasingly competitive global environment.

Globalization, along with its technological developments, has brought important changes and developments in all sectors and led to innovation and modernization. In the tourism industry, the concept of smart destination, derived from the concept of smart city, has become widespread to meet the changing needs of tourists. In this context, smart technologies have started to be used in destinations, but more than technology in destinations is needed in terms of sustainability. To ensure sustainability in tourism, these smart technologies must also be eco-friendly. Smart destinations and eco-friendly practices are important for the sustainable development of the tourism industry. The use of technology in destinations can increase sustainability and efficiency, while using eco-friendly practices can protect and preserve the natural environment. In this study, first of all, smart destinations and the characteristics of smart destinations are discussed. Then, smart tourism and related eco-friendly practices are argued. Following this, information about the future of smart destinations is given, and assumptions are mentioned. Afterward, problems and solutions are discussed. Finally, the study has been completed with the conclusion part. The findings of the study revealed that the concept of green especially comes to the fore in smart destinations, that there are studies to prevent all kinds of pollution (air, noise, etc.), and applications such as smart parking systems, smart lighting systems, augmented reality (AR), and virtual reality (VR) are given importance.

This chapter aims to highlight the existing applications and future prospects of Artificial Intelligence (AI) in the tourist business. In addition, this chapter investigates the obstacles in using AI in the Indian tourist industry.

To achieve the study's aims, both primary and secondary data are used. Using secondary sources, desk research was conducted to investigate the existing uses and future prospects of AI application in the global tourism industry. In addition, qualitative interviews with 25 executives in the Indian tourist business were undertaken to study the obstacles to using AI in the Indian tourism industry.

The research found that the applications of AI in the worldwide tourist business are extensive. Nonetheless, corporations are actively using AI-based technology to improve the customer experience via chatbots, intelligent forecasting and smart, tailored travel experiences. The qualitative interviews found that the implementation of AI technology in the Indian tourist industry is hindered by budgetary restrictions, knowledge constraints and barriers relating to human resources.

The use of AI in the tourism business may significantly improve the client experience. As a consequence, the use of AI-based chatbots and intelligent travel aides is growing exponentially. The research examined the many uses of AI in the worldwide tourist industry as well as the obstacles associated with the deployment of AI in the Indian tourism industry.

Internet of things (IoT) involves the connection of various devices. IoT’s application ranges from wearables: Smart Home Application, Health Care, Smart Offices, Smart Cities, Agriculture, and Industrial Automation. While the number of connected devices grows by the day, so does the number of security risks and vulnerabilities that these devices face. Billions of the connected devices collect and transmit huge volumes of data making Data Security one of the most pressing technical concerns in IoT. Smart Office is one of the increasing IoT applications and Data Security has become today one of the most challenging areas in its application. It is important to identify data security threats. This chapter therefore presents a review of IoT Smart Office Data Security Threats based on existing research done.

This chapter considers how to ensure that both knowledge preservation and curation are well supported in the architecture and infrastructure of any organization. Support at the enterprise architecture is critical if the business goals of use, reuse, curation, and recuration in the business context are to be achieved. Enterprise architecture is explained – its vertical and horizontal approaches. Preservation is aligned with the information and data architecture. Curation is defined as a new element in the business architecture layer. The authors explain how this approach supports variations in practice across the organization.

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.

This study investigates the motivation among customers to be more loyal to online food delivery applications (OFDA) services even after the COVID-19 epidemic by using perceived service quality aspects in Sri Lanka. The data were gathered by physically distributing a self-administrated questionnaire to clients in Sri Lanka who continue to use OFDA services on platform to customer (P2C) service delivery platforms to buy food despite the COVID-19 outbreak. Multiple regression is employed to analyse 287 effective observations, and the data revealed the significant positive effect of interaction, environment, outcome, and food qualities on customer loyalty to OFDA services. In fact, there is no impact from the delivery quality on customer loyalty to OFDA services due to outsourced food delivery. The findings suggest regular improvements in attributes such as interaction, environment, outcome, and food qualities in this hyper-competitive business environment. Further, this study sets substantial facts for the interested parties to establish an exemplary delivery system and other technological advancements to have a sustainable competitive advantage and solid customer base in the long run.

Social enterprises (SEs), part of the third sector, are hybrid organizations combining the pursuit of social scopes with commercial business solutions. In seeking for social value, they pair for-profit and non-profit features, thereby compensating for shortcomings of both the public sector and the commercial market. Therefore, the performance management of such organizations assumes a crucial relevance. Among the available tools, the balanced scorecard (BSC) aims to capture performance multidimensionality, at the same time fostering legitimacy towards stakeholders.

In general terms, the BSC has the limit to follow a linear and static logic of construction and functioning. For this reason, scholars combine it with system dynamics (SD) to create dynamic balanced scorecards (DBSCs). However, literature seems to devote scarce attention to the adoption of such analytic tools in the third sector, particularly in SEs. This chapter wants to contribute to bridging this gap by proposing a tailored application in the context of a social cooperative, active in the clothing recycle and in the re-integration of disadvantaged social categories. By referring to previous literature about DBSC, two modelling strategies are identified: the BSC-driven and the SD-driven. The latter, based on inductive reasoning, is the one privileged for the study because of its wider flexibility. The modelling outputs consider different perspectives than the ones within traditional BSCs, contain elements of circular causality and show how financial and non-financial performances interplay and co-determine each other. Insights from the proposed model can be useful to support both decision-making and stakeholder engagement.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).