Nour El-Hoda Khalifeh, Rudy Youssef, Farah Fadel, Roy Khalil, Elie Shammas, Naseem Daher, Imad H. Elhajj, Thomas Irrenhauser, Michael N. Niedermeier and Christian Poss
The purpose of this paper is to detail the design and prototyping of a smart automation solution for de-strapping plastic bonding straps on shipping pallets, which are loaded with…
Abstract
Purpose
The purpose of this paper is to detail the design and prototyping of a smart automation solution for de-strapping plastic bonding straps on shipping pallets, which are loaded with multiple containers secured by a top-cover as they move on a conveyor belt.
Design/methodology/approach
The adopted design methodology to have the system perform its function entails using the least number of sensors and actuators to arrive at an economic solution from a system design viewpoint. Two prototypes of the robotic structure are designed and built, one in a research laboratory and another in an industrial plant, to perform localized cutting and grabbing of the plastic straps, with the help of a custom-designed passive localizing structure. The proposed structure is engineered to locate the plastic straps using one degree of freedom (DOF) only. An additional strap removal mechanism is designed to collect the straps and prevent them from interfering with the conveyor.
Findings
The functionality of the system is validated by performing full-process tests on the developed prototypes in a laboratory setting and under real-life operating conditions at BMW Group facilities. Testing showed that the proposed localization system meets the specified requirements and can be generalized and adapted to other industrial processes with similar requirements.
Practical implications
The proposed automated system for de-strapping pallets can be deployed in assembly or manufacturing facilities that receive parts in standard shipping pallets that are used worldwide.
Originality/value
To the best of the authors’ knowledge, this is the first mechanically smart system that is used for the automated removal of straps from shipping pallets used in assembly facilities. The two main novelties of the proposed design are the robustness of the strap localization without the need for computer vision and a large number of DOF, and the critical placement and choice of the cutting and gripping tools to minimize the number of needed actuators.
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Khaled Jamal Alrabea, Mohammad Alsaffar, Meshari Abdulhameed Alsafran, Ahmad Alsaber, Shihanah Almutairi, Farah Al-Saeed and Anwaar Mohammad Alkandari
By addressing the dearth of literature on the subject of cybersecurity risks and artificial intelligence (AI), this study aims to close a research gap by concentrating on the…
Abstract
Purpose
By addressing the dearth of literature on the subject of cybersecurity risks and artificial intelligence (AI), this study aims to close a research gap by concentrating on the ever-changing environment of online social networks (OSNs) and technology. The main goals are to classify cyberattacks into categories like malware, phishing/spam and network intrusion detection; to identify efficient algorithms for preventing cyber threats; to review relevant literature from 2019 to 2020; and to use machine learning algorithms to detect suspicious behavior related to malware. The study offers a novel framework that suggests particular machine learning algorithms for every kind of cyber threat, hence improving cybersecurity knowledge and reaction capacities. This makes the research useful for examining the impact of cybersecurity on smart cities.
Design/methodology/approach
Thirty papers have been examined on AI and machine learning algorithms, including K-nearest-neighbor (KNN), convolutional neural networks (CNN) and Random Forest (RF), that were published in 2019 and 2020. Using analytical software (NVivo), a qualitative approach is used to retrieve pertinent data from the chosen research. The researchers divide cyberattacks into three groups: network intrusion detection, phishing/spam and malware.
Findings
The study’s conclusions center on how AI and machine learning algorithms linked to cybersecurity are reviewed in the literature, how cyberattacks are classified and how an inventive framework for identifying and reducing risks is proposed. This makes the research useful for researching the implications of cybersecurity for smart cities.
Practical implications
The practical implications of this research are noteworthy, particularly in the realms of technology, AI, machine learning and innovation. The utilization of the NVivo technique enhances decision-making in uncertain situations, making the study’s results more reliable. The findings showcase the applicability of tools in analyzing malicious cyberattacks to address issues related to social media attacks, emphasizing their practical utility. The study’s relevance is further highlighted by a real-world example, where a Kuwaiti public sector fell victim to a malware attack, underlining the importance of cybersecurity measures aligned with the New Kuwait 2035 strategic development plan. The innovative framework presented in the research guides the selection of algorithms for detecting specific malicious attacks, offering practical insights for securing information technology (IT) infrastructure in Kuwait.
Social implications
The rapid digitization in Kuwait, accelerated by the COVID-19 pandemic, underscores the pivotal role of technology in government services. Ma’murov et al. (2023) emphasize the significance of digitization, particularly in accessing and verifying COVID-19 information. The call for a dedicated digital library for preserving pandemic-related material aligns with the evolving digital landscape. Cybersecurity emerges as a critical concern in Kuwait and the Gulf Cooperation Council (GCC), necessitating transnational cooperation (Nasser Alshabib and Tiago Martins, 2022). In the local context, the inefficiency of information security systems and low awareness among government employees pose cybersecurity challenges (Abdulkareem et al., 2014). Social media’s role during the pandemic highlights its significance, yet the need for cybersecurity in this domain remains underexplored (Ma’murov et al., 2023; Safi et al., 2023).
Originality/value
The unique aspect of the paper is its in-depth investigation of the relationship between cybersecurity and AI in OSNs. It uses a special application of machine learning methods, including CNN, RF and KNN, to identify suspicious behavior patterns linked to malware. The detailed analysis of 30 research papers released between 2019 and 2020, which informs the choice of suitable algorithms for diverse cyber threats, further emphasizes the study’s uniqueness. The novel framework that has been suggested categorizes assaults and suggests certain machine learning techniques for identification, offering a useful instrument to improve comprehension and reactions to a variety of cybersecurity issues.
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Zeyu Li, Mazlina Mustapha, Ahmad Fahmi Sheikh Hassan and Saidatunur Fauzi Saidin
This study examines the impact of corporate governance on succession planning and organizational performance. Drawing on agency theory, the main purpose of this study is to…
Abstract
Purpose
This study examines the impact of corporate governance on succession planning and organizational performance. Drawing on agency theory, the main purpose of this study is to identify the effect of corporate governance on succession planning by measuring the different characteristics of the board of directors.
Design/methodology/approach
This multi-quantitative research used primary and archival data. A total of 281 valid questionnaires were collected from Chinese listed family firms to gauge succession planning. Relevant archival data were obtained to measure board characteristics and organizational performance. All hypotheses were examined through structural equation modeling.
Findings
The outcomes indicate that corporate governance positively influences succession planning and, in turn, boosts superior organizational performance, which uncovers the mediating effect of succession planning on the relationship between corporate governance and organizational performance. Our findings reveal that board independence and education facilitate the development of succession planning, which is crucial in the family business’s life cycle.
Originality/value
The results of this study contribute to management succession, strategic management and leadership research by demonstrating how corporate governance fosters organizational performance through succession planning, thereby expanding the application scenarios of agency theory in family firms. Additionally, the article also enriches our understanding of how family businesses apply sound governance structures to promote organizational strategic decision-making during the succession process.
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Mahfooz Alam, Shakeb Akhtar and Mamdouh Abdulaziz Saleh Al-Faryan
This paper aims to investigate the role of corporate governance on the bank profitability of Indian banks vis-à-vis South Asian Association for Regional Cooperation (SAARC…
Abstract
Purpose
This paper aims to investigate the role of corporate governance on the bank profitability of Indian banks vis-à-vis South Asian Association for Regional Cooperation (SAARC) nations.
Design/methodology/approach
For the Corporate Governance Index, the authors examined board accountability, transparency and disclosure and audit committee, while Tobin’s Q, return on equity and return on assets are used to measure the bank’s profitability. The study used a two-stage analysis based on balanced panel data for robust findings. Sample of this study consists of 60 commercial banks from India and 60 banks from SAARC nations for the period of 2009–2021. This study used panel regression and a generalized method of moment approach using the CAMELS framework on banking industry-specific variables to determine their respective impacts.
Findings
The findings of this study suggest that board accountability is positive and significantly affects the profitability of banks as indicated by return on assets, return on equity and Tobin’s Q. In contrast, the audit committee has a positive and insignificant impact on return on assets, return on equity and Tobin’s Q, while transparency and disclosure have a negative and significant impact on these metrics. Furthermore, the country dummy result shows a significant positive impact on all the bank performance parameters, implying that Indian banks have the highest degree of convergence with corporate governance as compared to other SAARC nations.
Research limitations/implications
This study provides insight to the regulators, policymakers and financial institutions to evaluate the role of corporate governance in emerging economies. However, the findings of the study should be interpreted with caution, as the results are sensitive to the disparity between India and other SAARC nations' government policies, climatic circumstances and cultural or religious traditions.
Originality/value
To the best of the authors’ knowledge, this is the first attempt to gauge the performance of Indian banks vis-à-vis SAARC nations using the CAMELS framework approach. Further, findings of this study suggest some novel evidence tying corporate governance quality with the profitability of banks among SAARC nations.