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Unlike many existing methods that are primarily focused on two-dimensional localization, this research paper extended the scope to three-dimensional localization. This enhancement is particularly significant for unmanned aerial vehicle (UAV) applications that demand precise altitude information, such as infrastructure inspection and aerial surveillance, thereby broadening the applicability of UAV-assisted wireless networks.

The paper introduced a novel method that employs recurrent neural networks (RNNs) for node localization in three-dimensional space within UAV-assisted wireless networks. It presented an optimization perspective to the node localization problem, aiming to balance localization accuracy with computational efficiency. By formulating the localization task as an optimization challenge, the study proposed strategies to minimize errors while ensuring manageable computational overhead, which are crucial for real-time deployment in dynamic UAV environments.

Simulation results demonstrated significant improvements, including a channel capacity of 99.95%, energy savings of 89.42%, reduced latency by 99.88% and notable data rates for UAV-based communication with an average localization error of 0.8462. Hence, the proposed model can be used to enhance the capacity of UAVs to work effectively in diverse environmental conditions, offering a reliable solution for maintaining connectivity during critical scenarios such as terrestrial environmental crises when traditional infrastructure is unavailable.

Conventional localization methods in wireless sensor networks (WSNs), such as received signal strength (RSS), often entail manual configuration and are beset by limitations in terms of capacity, scalability and efficiency. It is not considered for 3-D localization. In this paper, machine learning such as multi-layer perceptrons (MLP) and RNN are employed to facilitate the capture of intricate spatial relationships and patterns (3-D), resulting in enhanced localization precision and also improved in channel capacity, energy savings and reduced latency of UAVs for wireless communication.

The cyber-physical system (CPS) is a well proven technology for improving system performance, resilience, and interconnectivity. In emerging nations like India, the logistics industry lacks practices connecting logistical equipment with cyberspace. This paper aims to bridge this gap by identifying and evaluating the performance metrics of connectivity solutions. Its goal is to establish an appropriate infrastructure that enables seamless connectivity within the CPS-enabled logistics ecosystem.

A novel integrated decision method is employed to classify the optimal connectivity solution for CPS. It integrates Regret Theory (RT) and Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE-1) method in a Hesitant Fuzzy (HF) environment. This method considers the psychological traits of decision-makers and effectively incorporates their hesitancy for the classification.

The findings highlight security (c10) as the foremost critical performance metric, followed by cost (c6), scalability (c9), traceability (c2) and trustworthiness (c1) to build connective infrastructure for CPS. For extensive coverage scenarios, like freight transportation, cellular connectivity (a2) emerges as the most suitable connectivity solution.

This study provides a roadmap to logistics managers for selecting a suitable connectivity infrastructure to enhance seamless connectivity in logistics operations and processes. Technology providers can utilize the findings to develop the CPS infrastructure for effective freight logistics management.

This research introduces a novel decision-making tool for making choices related to advanced technology assessment. It holds significant value in facilitating well-informed decisions in the digital transformation era.

Talent management is conducted to maximize an organization's overall performance and efficiency which helps to serve as a competitive advantage. Human resource management is a concept which includes human-related activities, but talent management is a strategy which helps to get new talent, develop their skill sets and provide better employee engagement and experience to retain the top potential employees in an organization. Improvement in recruiting and retention of a workforce results from a well-executed talent acquisition approach. In the 21st century, employee retention has become a primary concern for the organizations specially with work from home and hybrid models.

The workforce for tomorrow is going to be very different from what it has been. Technology is transforming the way people work within organizations. The workplace is rapidly evolving in terms of people and processes and is going through a lot of technological changes. The terminologies such as automation, artificial intelligence, augmented reality and block chain technologies are slowly becoming part of the workplace and everyday activities of the organization.

The challenges are many and especially post-pandemic organizations are going through some major changes such as a mindset shift of employees to take up more remote working opportunities, building virtual teams, increase in the gig economy workers (contractual workers) and a diverse workforce which makes it even more challenging for the organization to manage and retain talent.

This chapter examines three common fintech use cases transforming the financial industry. First, the chapter introduces fintech's role in enhancing financial services and promoting financial inclusion, especially through digital platforms. Second, it investigates various fintech applications that support financial institution management by harnessing the power of artificial intelligence (AI) and machine learning (ML). Finally, the chapter explores fintech use cases related to the regulatory environment, including regulatory technology (regtech), blockchain technology, and cryptocurrencies. The insights presented in this chapter cater to researchers and practitioners keen on better understanding fintech's diverse applications in the ever-evolving financial industry landscape.

Social live streaming services (SLSS) have infused gamification into interface design and feature applications. Firms adopt gamification mechanisms to win customer loyalty in the live streaming and SLSS markets. Based on the mechanics-dynamics-aesthetics (MDA) framework and uses and gratifications 2.0 theory (UGT 2.0), this study aims to investigate the effects of game mechanics (mechanics) on enjoyment and user retention (aesthetics) through rewards and social interaction (dynamics) in the context of SLSS.

This study used an online survey via Google Forms, SurveyCake and social media platforms like Facebook, Instagram and Line to collect data from 232 SLSS users in Taiwan. Partial least squares structural equation modeling (PLS-SEM) was adopted to analyze the data.

The results validated the relationships between game mechanics and dynamic elements (rewards and social interaction) that triggered aesthetic elements (enjoyment feelings) among users. In addition, users experienced a sense of enjoyment that led to usage retention when using the gamified SLSS. Further, this study found enjoyment crucial for users to stay interactive with gamified services.

Driven by UGT 2.0, this study closed the gaps by integrating the MDA framework into the SLSS context and better understanding how game mechanics are connected to rewards and social interaction, leading to enjoyment and user retention when using SLSS. This study provides fresh insights into gamification-oriented SLSS practices. It offers significant theoretical and managerial implications and provides guidelines for SLSS platform operators on fostering user retention.

Through its advanced computational capabilities, cyber–physical systems (CPS) proffer solutions to some of the cultural challenges plaguing the effective delivery of facilities management (FM) mandates. This study aims to explore the drivers for the uptake of CPS for FM functions using a qualitative approach – the Delphi technique.

Using the Delphi technique, the study selected experts through a well-defined process entailing a pre-determined set of criteria. The experts gave their opinions in two iterations which were subjected to statistical analyses such as the measure of central tendency and interquartile deviation in ascertaining consensus among the experts and the Mann–Whitney U test in establishing if there is a difference in the opinions given by the experts.

The study’s findings show that six of the identified drivers of the uptake of CPS for FM were attributed to be of very high significance, while 12 were of high significance. Furthermore, it was revealed that there is no significant statistical difference in the opinions given by experts in professional practice and academia.

The study’s outcome provides the requisite insight into the propelling measures for the uptake of CPS for FM by organisations and, by extension, aiding digital transformation for effective FM delivery.

To the best of the authors’ knowledge, evidence from the literature suggests that no study has showcased the drivers of the incorporation of CPS for FM. Hence, this study fills this gap in knowledge by unravelling the significant propelling measures of the integration of CPS for FM functions.

This chapter focuses on how alternative data can change the nature of financial forecasting through improved short-term forecasting techniques and decreased informativeness from longer term sources. Increased use of social media data leads the charge in transforming this transition. Alternative data are data not from standard financial statements or formal reports. This chapter looks at alternative data from new sources (e.g., social media, Internet of Things [IoT], and digital footprints) and alternative data from new collection methods like web scraping for textual analysis, image analysis, and vocal analysis). It first discusses standard data in financial forecasting. Next, this chapter examines alternative data in financial forecasting. Finally, it discusses alternative data used in studying finance more broadly.

Based on imprinting theory and episodic future thinking, this paper aims to study how CEOs’ attributes and experiences inform innovation in tourism and hospitality businesses. It also explores ways to quantify innovation in this sector.

The authors quantitatively analysed innovation in tourism and hospitality using extensive data from companies’ annual reports. They further adopted multivariate regression to test how CEOs’ experience affects enterprise innovation.

Results demonstrate that CEOs’ academic education and rich work experience can promote corporate innovation. The authors also identified a mediating role of the tone of narrative disclosure in annual reports between CEOs’ academic education and corporate innovation. The imprinting effects of career experience and educational experience appear both independent and interactive.

CEOs are more inclined to engage in corporate innovation when influenced by the combined imprinting effects of strategic management training and work experience. Additionally, leaders should consider how communication styles indirectly influence innovation activities.

This paper introduces an integrated perspective that blends imprinting theory and episodic future thinking to bridge knowledge gaps regarding the interaction of CEOs’ past experiences. This work enhances understanding of how CEOs’ imprinted experiences, together with their capacity for envisioning future scenarios, can drive corporate innovation.

This paper takes the manufacturing cluster supply chain as the research object and explores the evaluation and enhancement strategy of manufacturing cluster supply chain synergy. The purpose of this study was to (1) analyze the mechanism of manufacturing cluster supply chain synergy; (2) construct manufacturing cluster supply chain synergy evaluation model; (3) algorithm realization of manufacturing cluster supply chain synergy evaluation and (4) propose manufacturing cluster-based supply chain synergy enhancement strategy.

Breaking through the limitations of traditional manufacturing cluster supply chain synergy evaluation, we take horizontal synergy and vertical synergy as coupled synergy subsystems, use the complex system synergy model to explore the horizontal synergy between core enterprises and cluster enterprises and the vertical synergy of supply chain enterprises and use the coupling coordination model to construct the coupled synergy evaluation model of manufacturing cluster supply chain, which is an innovation of the evaluation perspective of previous cluster supply chain synergy and also an enrichment and supplementation of the evaluation methodology. This is not only the innovation of the evaluation perspective but also the enrichment and supplementation of the evaluation method.

Using Python software to conduct empirical analysis on the evaluation model, the research shows that the horizontal and vertical synergies of the manufacturing cluster supply chain interact with each other and jointly affect the coupling synergy. On this basis, targeted strategies are proposed to enhance the synergy of the manufacturing cluster supply chain.

This study takes manufacturers, suppliers and sellers in the three-level supply chain as the research object and does not consider the synergistic evaluation between distributors and consumers in the supply chain, which can be further explored in this direction in the future.

Advanced manufacturing clusters, as the main force of manufacturing development, and the synergistic development of supply chain are one of the important driving forces for the high-quality development of China’s manufacturing industry. As a new type of network organization coupling industrial clusters and supply chains, cluster supply chain is conducive not only to improving the competitiveness of cluster supply chains but also to upgrading cluster supply chains through horizontal synergy within the cluster and vertical synergy in the supply chain.

Research can help accelerate the transformation and upgrading of clustered supply chains in the manufacturing industry, promote high-quality development of the manufacturing industry and accelerate the rise of the global value chain position of the manufacturing industry.

(1) Innovation of research perspective. Starting from two perspectives of horizontal synergy and vertical synergy, we take a core enterprise in the cluster supply chain as the starting point, horizontally explore the main enterprises of the cluster as the research object of horizontal synergy, vertically explore the upstream and downstream enterprises of the supply chain as the research object of vertical synergy and explore the coupling synergy of cluster supply chain as two subsystems, which provides new perspectives of evaluation of the degree of synergy and synergy evaluation. (2) Innovation of research content. Nine manufacturing clusters are selected as research samples, and through data collection and model analysis, it is verified that the evaluation model and implementation algorithm designed in this paper have strong practicability, which not only provides methodological reference for the evaluation of manufacturing cluster-type supply chain synergy but also reduces the loss caused by the instability of clusters and supply chains and then provides a theoretical basis for improving the overall performance of cluster-type supply chains.

The maritime industry, a linchpin of global trade, has embarked on a transformative journey catalysed by the relentless advance of digitalisation. There is a discernible gap in the literature concerning the specific consequences of digitalisation within the maritime sector. This research aims to examine the current body of literature on the influence of digitalisation in human resource development (HRD) on the competitive advantage of organisations and its potential within the maritime industry.

This research paper conducts a comprehensive bibliometric analysis.

The findings of this research explore the literature landscape encompassing digitalisation in HRD, its influence on HR operations, learning and development, performance management, employee experience and strategic alignment within maritime organisations.

This research provides valuable recommendations for maritime organisations and HRD practitioners seeking to leverage digitalisation to gain a competitive edge. Thus, the maritime industry can adopt digital HRD practices to streamline operations, improve performance and align HR strategies with broader organisational goals.