The intercorrelations among risk factors and trust dimensions in S-commerce: An empirical investigation from the user experience

With the increase in social media users, businesses are trying to benefit from the popularity and reachability of such platforms by introducing a new channel for promoting and selling their products. This study surveyed 267 social commerce consumers in the UAE to understand the impact of the perceived risks on users\u27 trust, which is known to impact customers\u27 purchase intention. Structural equation modeling and factor analysis were applied. The results highlighted the importance of security risks as statistically significant influencers of the users\u27 trust. On the other hand, financial and time risks were insignificant. The study has both practical and theoretical implications discussed in the paper

Modelling innovative business clusters

Science and Technology Parks (STPs) are often used as tools to foster regional development. They encourage innovation amongst the constituent firms, including by networking and knowledge spillover between the inhabitants and other actors. The high failure rate of STPs led us to evaluate a case study using panel data analysis as well as simulate how STP architecture can best cope with a changing innovation environment. Data from the Ratsit database was obtained for firms in industry sector 62X (IT and related industry) in Linköping, Sweden and then divided into those on-cluster or off-cluster. Inhabitancy conferred protection for on-cluster firms against externalities. Longitudinal studies showed that micro-firms entering the STP exodus point was seen around 15-17 years when firms, grown to around 150 employees, either plateau out in growth or depart the locality. Size and age influence corporate turnover, as does the ability to innovate, but whereas size and age have a quadratic (non-linear) impact on financial growth, innovation capabilities have a positive linear impact. Employment is mainly correlated to age, previous years’ innovation and shareholder investment. Innovation output is correlated to networking measured as social expenditure, which in turn exhibits a positive influence on innovation capabilities. From the point of view of the host cluster, we simulated three organizational topologies for STPs; firstly, in the star model all are connected to the cluster initiative (CI), secondly the strongly connected model, when all are connected to each other, and finally the randomly connected model, where the network follows no centralised topology. Analyses used adjacency matrixes and Monte-Carlo simulation, trading transaction (networking) costs against knowledge benefit. Results show that star topology is the most efficient form from the cost perspective. Later, when the cost of knowledge transformation is lowered, then the strongly connected model becomes the most efficient topology. iii | P a g e Then, Agency-based Monte-Carlo simulations were then applied to clusters organisation to understand the impact of managers quality on innovation distribution using both poor and good innovation. Results show that it is very beneficial to have a central Cluster Initiative (CI) controlling the decision-making process in the early stages of STP development. However, with early maturity and commitment to a high-growth trajectory, high quality of decision–making is required amongst managers and decisions are best taken by the CI with the input of individual on-cluster firms. The scenario where CI is supported by good-quality decisions from on-cluster firms – an ambidextrous situation – is superior when good innovations abound and the STP has acquired a degree of maturity

The Good, The Bad, and The Ugly About Insta Shopping: A Qualitative Study

Instagram, as many social media platforms, has been increasingly used by users to shop for goods and products from business or other individuals. Recently, studies have shed lights on acceptance and usage of Insta shopping from users’ perspectives by following popular technology models, such as technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT). However, more rich and in-depth insights about using Instagram for commercial purposes within a certain context are yet to be discovered. Therefore, this study aims at discovering experiences and interactions with Insta shopping, the factors and the drivers that impact users’ acceptance of Insta shopping, the weight of each factor (degree of consensus among participants), and their direction (positive, negative, or both). The study followed a qualitative approach, by creating four homogeneous focus groups (six participants each) of IT students in United Arab Emirates (UAE) universities. The data analysis approach considered is an axial coding technique as part of the grounded theory, which includes open coding, axial coding, and selective coding stages. The results revealed that the time factor, trust in Insta shops (and its drivers such as reviews, word of mouth, trading license, and others), distrust (and its drivers such as fake comments and reviews, extremely low prices, and others), and the associated risks (financial for losing money, security because of online payments, and some privacy issues) can impact users’ behaviors toward Insta shopping. Also, the study classified participants’ viewpoints and experiences’ themes into advantages, disadvantages, and issues that are associated with Insta shopping. The study indicated theoretical and practical implications and suggests future research directions

Conceptualising the Role of the UAE Innovation Strategy in University-Industry knowledge Diffusion Process

Universities are considered one of the primary sources of knowledge and an essential component of the triple helix theory. They fuel the industries with the required expertise and pool of resources to operate efficiently. Moreover, entrepreneurial universities successfully contributed to regional development and employment growth by supporting entrepreneurial activities and incubation programmes. Thus, university-industry collaboration is vital for enhancing knowledge-based industries\u27 knowledge diffusion as well as the regional innovation atmospheres. On the other hand, countries and regional authorities strive to stimulate their regional development by encouraging innovation and entrepreneurship activities. For example, the UAE announced its 2015 innovation strategy that focused on seven industries: education, technology, renewable energy, transportation, education, health, water, and space. The strategy stressed the role of universities R & R&D, first-class research, and promoting incubation services as one of the country\u27s main innovation enablers. Thus, universities, scholars and industry should concentrate on the identified sectors to achieve the strategic innovation goals. This work aims to conceptualise and test the relationship and collaboration between industry and universities in the UAE and the impact of the innovation strategy on this relationship. Therefore, we critically analyse literature on the university-industry relationship and connect it with the UAE innovation strategy that resulted in a conceptual university-industry relationship model where the innovation strategy and UAE government act as a moderator of this relationship. The initial results show that the conceptual model includes research and curriculum collaboration. Research collaboration includes joint research, research fund, commercialisation of the research output, while curriculum collaboration includes the programmes and courses updates and joint training programmes. The developed model is still in its early stage of development and requires further updates based on interviews with the HEIs researchers and the survey results

Efforts and Suggestions for Improving Cybersecurity Education

In this growing technology epoch, one of the main concerns is about the cyber threats. To tackle this issue, highly skilled and motivated cybersecurity professionals are needed, who can prevent, detect, respond, or even mitigate the effect of such threats. However, the world faces workforce shortage of qualified cybersecurity professionals and practitioners. To solve this dilemma several cybersecurity educational programs have arisen. Before it was just a couple of courses in a computer science graduate program. Now a day’s different cybersecurity courses are introduced at the high school level, undergraduate computer science and information systems programs, even in the government level. Due to some peculiar nature of cybersecurity, educational institutions face many issues when designing a cybersecurity curriculum or cybersecurity activities

The Impact of Personal Lifestyle and Personal Innovativeness on Insta Shopping Purchase Intention

Social commerce (s-commerce) is an evolving concept that has become an inspirational area of research due to the continued development and breakthroughs of social interactions and social media platforms. This study examines the moderating effect of perceived risks and overall trust on the intention to buy. Moreover, it tests the impact of consumers’ lifestyles and personal innovativeness on perceived risks and trust. We surveyed 267 active social commerce users and analyzed the responses using SmartPLS3.0 by applying structural equation modeling. The results show a significant impact of consumers’ lifestyles, personal innovativeness, and trust on behavioral intention. However, consumers’ perceived risks do not influence users’ decisions to use Insta shopping

Motivation and Hurdles for the Student Adoption of Metaverse-based Classroom: A Qualitative Study

Metaverse is an emerging technology that combines the virtual world and the real world, resulting in an immersive user experience. It has many applications. In this study, we inves-tigated the users\u27 perception of the Metaverse-based classroom in the UAE by qualitatively surveying 84 higher education students. After coding the users\u27 responses, we generated a world cloud and analyzed the user responses. A little more than a third of the surveyed users do not believe that they will benefit from using Metaverse in higher education, and they would not like to use it. Users are mainly concerned about their health conditions, security, and privacy of their information, and the students\u27 movement may result in students losing focus (distraction). On the other hand, the learner will be motivated by the interactive nature of the Metaverse-based classroom and the education\u27s location and time flexibility. Different practical and theoretical implications have been identified and discussed in this paper

DroidDetectMW: A Hybrid Intelligent Model for Android Malware Detection

Malicious apps specifically aimed at the Android platform have increased in tandem with the proliferation of mobile devices. Malware is now so carefully written that it is difficult to detect. Due to the exponential growth in malware, manual methods of malware are increasingly ineffective. Although prior writers have proposed numerous high-quality approaches, static and dynamic assessments inherently necessitate intricate procedures. The obfuscation methods used by modern malware are incredibly complex and clever. As a result, it cannot be detected using only static malware analysis. As a result, this work presents a hybrid analysis approach, partially tailored for multiple-feature data, for identifying Android malware and classifying malware families to improve Android malware detection and classification. This paper offers a hybrid method that combines static and dynamic malware analysis to give a full view of the threat. Three distinct phases make up the framework proposed in this research. Normalization and feature extraction procedures are used in the first phase of pre-processing. Both static and dynamic features undergo feature selection in the second phase. Two feature selection strategies are proposed to choose the best subset of features to use for both static and dynamic features. The third phase involves applying a newly proposed detection model to classify android apps; this model uses a neural network optimized with an improved version of HHO. Application of binary and multi-class classification is used, with binary classification for benign and malware apps and multi-class classification for detecting malware categories and families. By utilizing the features gleaned from static and dynamic malware analysis, several machine-learning methods are used for malware classification. According to the results of the experiments, the hybrid approach improves the accuracy of detection and classification of Android malware compared to the scenario when considering static and dynamic information separately

A systematic analysis on the readiness of Blockchain integration in IoT forensics

Internet of Things (IoT) devices are massively utilized in our daily lives which is exposing them to a wide range of attacks. The heterogeneity of evidence produced by IoT devices is complicating the process of evidence collection and processing. Consequently, it is imperative to maintain admissible evidence collection, preservation, and analysis to be presented in a court of law. The currently used digital forensic tools and methodologies are lagging behind the IoT\u27s heterogeneity and distributive nature. The decentralized, distributed, and transparent nature of Blockchain has encouraged lots of research on utilizing Blockchain to store, process, and investigate digital evidence in IoT forensics across various jurisdictions. Therefore, this research work analyzes proposed frameworks in the literature to review their deployment of Blockchain technology to resolve the various presented challenges in IoT Forensics. It presents a systematic review to investigate the readiness of blockchain integration in IoT forensics. Many factors have been addressed to consider when integrating the Blockchain technology into IoT forensics such as data integrity, distributed storage, authentication, transparency, and security where the literature provides an adequate proof on the crucial need to consider them as essential IoT forensic readiness factors. The research findings highlight challenges and open research opportunities of blockchain utilization to facilitate sound and efficient IoT forensics