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Despite the growing interest regarding companies' sustainability, its social dimension has mostly been neglected by academics and practitioners. Consequently, this study aims to address this issue by investigating if the adoption of human resource (HR) analytics can positively influence the impact of social sustainable operations practices (SSOP) on employees' motivation and engagement and the effect of these lasts on organizational retention.

Data were collected through online questionnaires addressed to 281 HR managers of heterogeneous companies from Europe and analyzed through a structural equation modeling (SEM) technique.

The findings confirmed the positive effect of SSOP on employees’ motivation and engagement, and of these last on employees’ retention. Furthermore, they confirmed that the usage of HR analytics positively moderates the relationship between SSOP and employees’ motivation and engagement.

This study contributes to both sustainable operations management and HR management literature streams. First, it adopts a multidisciplinary perspective which also considers evidence from HR management literature, allowing the authors to concentrate on the social dimension of sustainability. Second, it provided further insight regarding the adoption of a data-driven approach in relation to social sustainable operations management. Finally, it contributes to HR analytics-related literature by demonstrating its impact also on organizational aspects that are not directly controlled by the HR department.

In recent times, mobile banking has become the best alternative for transactions associated with payments like bills, fees, and peer-to-peer payments. Therefore, the pace of adoption is increasing day after other. However, the numbers of customers are not equal to the expectations as there are several challenges and threats hindering in the way of excellence and growth of mobile banking. Therefore, this chapter has been written purposively to address all the elements that are associated with the use of mobile banking with special emphasis on Pakistan and other developing sides of Asia. In fact, concern towards Asian sides is mandatory as the continent has the massive charm to attract users towards the use of mobile banking, but there is a need for proper policy and concern from stakeholders in order to give a push to the technology, which is fruitful for society, environment, as well as economy. The study includes an in-depth discussion on factors that need attention to make the study implicative and thorough for conducting further research in the field of Fin-Tech and mobile banking.

This study explores the potential of artificial intelligence (AI) in fostering sustainable entrepreneurship within the tourism industry. The rapid growth of the tourism sector has raised concerns regarding its environmental impact, social equity and economic sustainability. Sustainable entrepreneurship offers a promising approach to address these challenges by integrating environmental, social and economic considerations into business practices. AI technologies, with their ability to process vast amounts of data, analyse patterns and make predictions, have the potential to support sustainable entrepreneurship initiatives in the tourism industry. By analysing the current literature, this study provides insights into the effective utilisation of AI to promote sustainable entrepreneurship in the tourism industry, while acknowledging the need for responsible and ethical AI implementation. The findings contribute to the understanding of how AI can be harnessed as a tool for driving sustainable practices and innovation in the tourism sector, ultimately leading to a more sustainable and responsible tourism industry.

The purpose of this paper is to explore factors and their impacts influencing online grocery shopping intentions among customers in the post COVID-19 situation. Moreover, the study aims at evaluating the mediating roles of shopping habits during COVID-19 between perceived usefulness, perceived ease of use and post COVID-19 online grocery shopping intentions.

Based on a review of the literature and collection of 401 useable valid responses, the study was conducted through structured questionnaires applying personal interview technique. The subsequent analysis was conducted through partial least squares structural equation modeling (PLS-SEM) using Smart PLS 3.3.3.

The study findings revealed that perceived usefulness, perceived ease of use and shopping habits during COVID-19 have a significant influence on post COVID-19 online grocery shopping intentions. Also, the study has uncovered that perceived usefulness and perceived ease of use significantly influence shopping habits during COVID-19 among customers. Furthermore, the current study has revealed that hopping habit during COVID-19 significantly mediates the relationship between perceived usefulness, perceived ease of use and post COVID-19 online grocery shopping intentions.

The study findings have provided practical suggestions of developing and improving technological platforms to attract new customers for online grocery shopping. Further, the study suggests that online grocery retailers should apply adjusted pricing strategies using coupons and discount offers.

This paper investigates factors and its impacts on online grocery shopping intentions in post COVID-19 context. Therefore, the study uncovers the factors that add value to understanding customers' post COVID-19 online grocery shopping intentions by integrating perceived usefulness, perceived ease of use and shopping habits during COVID-19.

Automatic dependent surveillance-broadcast (ADS-B) is the foundational technology of the next generation air transportation system defined by Federal Aviation Authority and is one of the most precise ways for tracking aircraft position. ADS-B is intended to provide greater situational awareness to the pilots by displaying the traffic information like aircraft ID, altitude, speed and other critical parameters on the Cockpit Display of Traffic Information displays in the cockpit. Unfortunately, due to the initial proposed nature of ADS-B protocol, it is neither encrypted nor has any other innate security mechanisms, which makes it an easy target for malicious attacks. The system is vulnerable to various active and passive attacks like message ingestion, message deletion, eavesdropping, jamming, etc., which has become an area of concern for the aviation industry. The purpose of this study is to propose a method based on modified advanced encryption standard (AES) algorithm to secure the ADS=B messages and increase the integrity of ADS-B data transmissions.

Though there are various cryptographic and non-cryptographic methods proposed to secure ADS-B data transmissions, it is evident that most of these systems have limitations in terms of cost, implementation or feasibility. The new proposed method implements AES encryption techniques on the ADS-B data on the sender side and correlated decryption mechanism at the receiver end. The system is designed based on the flight schedule data available from any flight planning systems and implementing the AES algorithm on the ADS-B data from each aircraft in the flight schedule.

The suitable hardware was developed using Raspberry pi, ESP32 and Ra-02. Several runs were done to verify the original message, transmitted data and received data. During transmission, encryption algorithm was being developed, which has got very high secured transmission, and during the reception, the data was secured. Field test was conducted to validate the transmission and quality. Several trials were done to validate the transmission process. The authors have successfully shown that the ADS-B data can be encrypted using AES algorithm. The authors are successful in transmitting and receiving the ADS-B data packet using the discussed hardware and software methodology. One major advantage of using the proposed solution is that the information received is encrypted, and the receiver ADS-B system can decrypt the messages on the receiving end. This clearly proves that when the data is received by an unknown receiver, the messages cannot be decrypted, as the receiver is not capable of decrypting the AES-authenticated messages transmitted by the authenticated source. Also, AES encryption is highly unlikely to be decrypted if the encryption key and the associated decryption key are not known.

Implementation of the developed solution in actual onboard avionics systems is not within the scope of this research. Hence, assessing in the real-time distances is not covered.

The authors propose to extend this as a software solution to the onboard avionics systems by considering the required architectural changes. This solution can also bring in positive results for unmanned air vehicles in addition to the commercial aircrafts. Enhancement of security to the key operational and navigation data elements is going to be invaluable for future air traffic management and saving lives of people.

The proposed solution has been practically implemented by developing the hardware and software as part of this research. This has been clearly brought out in the paper. The implementation has been tested using the actual ADS-B data/messages received from using the ADS-B receiver. The solution works perfectly, and this brings immense value to the aircraft-to-aircraft and aircraft-to-ground communications, specifically while using ADS-B data for communicating the position information. With the proposed architecture and minor software updates to the onboard avionics, this solution can enhance safety of flights.

Blockchain, a groundbreaking technology that recently surfaced, is under thorough scrutiny due to its prospective utility across different sectors. This research aims to delve into and assess the cognitive elements that impact the integration of blockchain technology (BT) within library environments.

Utilizing the Stimulus–Organism–Response (SOR) theory, this research aims to facilitate the implementation of BT within academic institution libraries and provide valuable insights for managerial decision-making. A two-staged deep learning structural equation modelling artificial neural network (ANN) analysis was conducted on 583 computer experts affiliated with academic institutions across various countries to gather relevant information.

The research model can correspondingly expound 71% and 60% of the variance in trust and adoption intention of BT in libraries, where ANN results indicate that perceived possession is the primary predictor, with a technical capability factor that has a normalized significance of 84%. The study successfully identified the relationship of each variable of our conceptual model.

Unlike the SOR theory framework that uses a linear model and theoretically assumes that all relationships are significant, to the best of the authors’ knowledge, it is the first study to validate ANN and SEM in a library context successfully. The results of the two-step PLS–SEM and ANN technique demonstrate that the usage of ANN validates the PLS–SEM analysis. ANN can represent complicated linear and nonlinear connections with higher prediction accuracy than SEM approaches. Also, an importance-performance Map analysis of the PLS–SEM data offers a more detailed insight into each factor's significance and performance.

The growth of the internet, access to technology and rapid digital transformations have paved the way for developing attack surfaces for individuals and organizations. There is a dire need to provide cybersecurity awareness most effectively. Gamification-based platforms have evolved to make cybersecurity education more engaging and effective. This study explores the gamification platforms available for cybersecurity training and awareness, the extent to which they are used and their benefits and challenges.

PRISMA 2020 was used to conduct the systematic literature review.

The study comprehends the game design elements and their role in the effectiveness of cybersecurity training and awareness. The study unveils that traditional education methodologies are insignificant in cybersecurity awareness, and gamification-based platforms are more beneficial. The paper summarizes the implications of the findings and further postulates future research directions.

This work comprehends the various forms of gamification platforms and frameworks available for cybersecurity training and will motivate further development of gamification platforms. This paper will help academia, private and public organizations and game designers enhance their gamification-based cybersecurity education interventions.

The purpose of our research on blockchain technology is to unveil its immense potential, understand its applications and implications and identify opportunities to revolutionize existing systems and processes. This research aims to inspire the creation of new innovative solutions for industries. By harnessing blockchain technology, organizations can pinpoint key areas that could significantly benefit from its use, such as streamlining operations, providing secure and transparent digital solutions and fortifying data security.

This study presents a robust multi-criteria decision-making framework for assessing blockchain drivers in selected Indian industries. We initiated with an extensive literature review to identify potential drivers. We then sought the opinions of experts in the field to validate and refine our list. This meticulous process led us to identify 26 drivers, which we categorized into five main categories. Finally, we employed the Best-Worst Method to determine the relative importance of each criterion, ensuring a comprehensive and reliable assessment.

The authors have ranked the blockchain drivers based on their degree of importance using the Best-Worst Method. This study reveals the priority of BC implementation, with the retail industry identified as the most in need, followed by the Banking and Healthcare industries. Various critical factors are identified where blockchain technology could help reduce costs, increase efficiency and enable new innovative business models.

While this study acknowledges potential bias in driver assessment relying on literature and expert opinions, its findings carry significant practical implications. We have identified key areas where blockchain technology could be transformative by focusing on select industries. Future research should encompass other industries and real-world case studies for practical insights that could delve into the adoption challenges and benefits of blockchain technology in many other industries, thereby amplifying the relevance of our findings.

Blockchain is a groundbreaking, innovative technology with immense potential to revolutionize industries. Past research has explored the benefits and challenges of blockchain implementation in specific industries or sectors. This creates a gap in research regarding systematically classifying and ranking the importance of blockchain across different Indian industries. Our research seeks to address this gap by using advanced multi-criteria decision-making techniques. We aim to provide a comprehensive understanding of the significance of blockchain technology in critical Indian industries, offering valuable insights that can inform strategic decision-making and drive innovation in the country’s business landscape.

This research offered a systematic and comprehensive literature review in analysing current studies on employee ecological behaviour (EEB) strategies and settings to determine various emphasised workplace ecological behaviour areas and contribute a precise mapping for future research.

This systematic literature review method involved 106 peer-reviewed articles published in reputable academic journals (between 2000 and the first quarter of 2021). This study was confined to a review of empirical papers derived from digital databases encompassing the terms ‘Employee green behaviour’, ‘Green behaviour at workplace’, ‘Employee ecological behaviour’, ‘Employee Pro-environmental behaviour’ and ‘Pro-environmental behaviour at workplace’ in the titles.

This study identified relevant journal articles (classified as EEB at work) from the current body of knowledge. Notably, much emphasis was identified on EEB over the past two decades. Overall, most studies employing quantitative approaches in both developed and emerging nations. Notably, ecological behaviour application garnered the most significant attention from scholars among the four focus areas in the literature review: (i) EEB concepts, models, or reviews, (ii) EEB application, (iii) EEB determinants and (iv) EEB outcomes.

Significant literature gaps indicate this field to be a relatively novel phenomenon. Thus, rigorous research on the topic proves necessary to develop a holistic understanding of the subject area.

This study expands the current body of knowledge by providing the first comprehensive systematic review on EEB themes, methods, applications, determinants, contextual focus, outcomes and recommending future research agenda.

Based on the Natural resource-based view (NRBV), this study aims to analyze the association between the Sustainable Development Goals related to Gender Equality, Decent Work, Innovation, and Climatic Action in the Food Industry.

A quantitative study is adopted based on the 2019 World Bank Enterprise Survey microdata. The database includes 1,242 food enterprises from 16 European Union countries. We applied logistic regression with cluster robust standard errors.

Despite global efforts to promote decent work and gender equity, the anticipated results have not yet been achieved, suggesting varying performance in different contexts. Food firms, characterized by significant environmental impacts and seasonal tasks, employ diverse Human Resource Management (HRM) strategies based on whether they pursue innovation or environmental objectives. Grounded in the NRBV, our findings underscore the importance of investing in qualified workers and offering attractive wages to meet environmental goals, as well as providing stable contracts for female workers. The NRBV framework also highlights the crucial role of product and process innovations, whether green or not, in achieving climate action objectives.

European policies must be adapted to the human resources characteristics in the food industry, providing specific training on environmental and innovation issues and contributing to more work stability and gender equality.

Our study applies the NRBV to analyze how human resources and product/process innovations can boost environmental preservation in an industry characterized by strong environmental impacts, seasonal tasks, and financial constraints.