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Investigating The Relationship Between Pricing Strategies And International Customer Acquisition In The Early Stage Of SaaS: The Role Of Hybrid Pricing
Get PDFModern cloud infrastructures make it possible for SaaS businesses to provide their services to clients all over the world. As a result, it is easy for a SaaS company to operate on a worldwide scale in an early stage. Innovative SaaS services are more difficult to price than regular products. Poor pricing may lead to a misleading impression of the product, while a well-thought-out price plan can assist a business in achieving its immediate and long-term revenue objectives while also satisfying its customers. The goal of this study is to investigate which pricing strategy helps SaaS organizations attract more customers. Correlation, Random Forest Regression, and Pairwise Multiple Linear regression were applied. The correlation heatmap shows that the sales volume is highly and positively associated with hybrid pricing. This indicates that the implementation of the hybrid pricing technique is associated with more sales volume. The majority of SaaS companies in the study sample used freemium, high-low, and hybrid. The skimming and the penetration pricing techniques were the least employed pricing tactics in SaaS. The regression model with hybrid pricing has also shown a high explanatory performance. With an overall score of 91.89 percent, the findings of this empirical study showed a sufficient degree of accuracy. According to the random forest results, among other techniques, hybrid pricing is the most significant pricing technique in increasing sales volume in SaaS. This study recommends that the SaaS business should employ a hybrid pricing approach in order to attract more consumers, enhance the entire experience they deliver, and therefore increase SaaS sales revenues
Predictive Analytics in Cloud Computing: An ARIMA Model Study on Performance Metrics
Get PDFPredictive analytics is a key aspect of cloud computing as it helps organizations to anticipate future events and take proactive measures to prevent issues before they occur. In this research, the goal was to perform an ARIMA (AutoRegressive Integrated Moving Average) model to predict cloud performance using various performance metrics. The study utilized ten different performance metrics, such as Response Time, Resource Utilization, Availability, Error Rate, Memory Usage, CPU Utilization, Disk I/O, Network Bandwidth and others to model cloud performance. The aim was to investigate the potential of ARIMA models to predict cloud performance by analyzing the impact of these different performance metrics on the model\u27s accuracy. The study also used four performance criteria, namely LogL (Log Likelihood), AIC (Akaike Information Criterion), BIC (Bayesian Information Criterion), and HQ (Hannan-Quinn Criterion) to evaluate the performance of the ARIMA models. The results of the study showed that the ARIMA model (2,0) and (0,2) had the lowest AIC and BIC values among all the models considered. This indicated that these models were the most suitable for predicting cloud performance, as they had the lowest information loss compared to the other models. The results of the study provided evidence that ARIMA models can effectively predict cloud performance. This research highlights the importance of predictive analytics in cloud computing and the potential for ARIMA models to predict cloud performance. The findings have implications for organizations that rely on cloud computing. However, more research is needed in this area, as the study was limited to only ten performance metrics, and more extensive research is needed to validate the findings and to determine the best approach to predict cloud performance
The Impact of Remote Work on Firm’s Profitability: Optimizing Virtual Employee Productivity and Operational Costs
Get PDFRemote working offers a series of benefits not only to the employees individually but importantly to the companies as a whole. This research discusses how altering business strategy to accommodate remote working may boost the profitability of a firm. More specifically, we proposed the RW (Remote -Work) led growth hypothesis. We derived this hypothesis from two perspectives: the VEP (Virtual employee productivity) and VOC (Cost-cutting through the virtual office). We argued that employee productivity increases through factors such as work-life balance and employee engagement. Additionally, a firm can reduce operational expenses by adopting a work-from-home model. Although working remotely can increase the profitability of a firm, certain hidden expenses must be evaluated. This research also discusses these challenges that may cause the degrowth of a firm. We recommend that firms should resolve these issues to make a robust growth strategy that can achieve growth in the remote working model. The remote work trend is a recent phenomenon and there is not enough empirically workable dataset from different firms. Some post-pandemic surveys suggest that companies enjoyed profits to some extent but these surveys lack rigorous empirical models
Virtual Employee Monitoring: A Review on Tools, Opportunities, Challenges, and Decision Factors
Get PDFThere has been a significant reduction in human-to-human contact since the beginning of the COVID-19 epidemic. Many workplaces have taken the initiative to allow staff to work from home. However, monitoring workers and determining whether or not they are executing the tasks assigned to them has proven to be a significant difficulty for all firms and organizations that facilitate Work From Home. Individual workers\u27 hours of work, presence, and active, idle, and break periods are being automatically tracked. To increase accountability, the program may take computer screen captures at random or at predetermined intervals and check the remote team\u27s online activity and analytics in real-time to see how they are spending their time and where they might improve. This research discusses the 4 popular mentoring tools, namely, Virtual time tracking (VTT), Random screen capture (RSC), Tracking of Websites and Apps, and Face Identification/biometrics. We also examined the opportunities these tools offer and the challenges they pose.
Finally, we briefly outlined various decision factors before implanting remote employee monitoring. We argue that a firm must first assess the local legal framework before employing staff monitoring and should assess if their industry is conducive to monitoring. Finally, Employee monitoring will be effective only if the necessary information technology infrastructure is in place
Equitable Healthcare Access During the Pandemic: The Impact of Digital Divide and Other SocioDemographic and Systemic Factors
Get PDFAccess to healthcare is a fundamental right for all individuals, and it has become more crucial than ever during the ongoing COVID-19 pandemic. Unfortunately, many people have faced barriers to accessing healthcare services due to the digital divide. The COVID-19 pandemic has brought into sharp focus the urgent need for access to healthcare services. The impact of the pandemic on healthcare access has been a matter of concern for policymakers, healthcare providers, and the public alike. This study aimed to empirically examine the determinants of healthcare access during the pandemic, with a specific focus on the impact of the digital divide. The sample size consisted of 312 individuals, and the study applied a multivariable regression model with HAC estimator to analyze the data. Healthcare access was the dependent variable, while the independent variables included Digital divide, Demographic factors, Sociocultural factors, and Systemic factors. The findings revealed that demographic factors, sociocultural factors, and systemic factors significantly impacted healthcare access during the pandemic. However, the most significant finding was the impact of the digital divide on healthcare access. This finding underscores the critical need to address the digital divide to ensure equitable healthcare access during the pandemic and beyond. This study highlights the urgent need for policymakers and healthcare providers to focus on addressing the digital divide to ensure equitable access to healthcare services. By doing so, it will be possible to ensure that vulnerable populations are not left behind during this critical time. The findings of our study have important implications for healthcare policy and practice and can guide future research in this area. This study provides valuable insights into the determinants of healthcare access during the pandemic, which can inform efforts to improve healthcare delivery and promote health equity
Innovations in Electric Vehicle Technology: A Review of Emerging Trends and Their Potential Impacts on Transportation and Society
Get PDFThe adoption of electric vehicles (EVs) has gained significant momentum in recent years, driven by the need to reduce greenhouse gas emissions, improve air quality, and achieve sustainable transportation. This study presents a comprehensive review of emerging trends in EV technology and their potential impacts on transportation and society. The study explores various areas of innovation in the field of EVs, including battery technology, wireless charging, vehicle-to-grid (V2G) communication, lightweight materials, autonomous driving, vehicle-to-everything (V2X) communication, circular economy approaches, advanced charging infrastructure, energy storage, and social and behavioral innovations. This study reveals that battery technology advancements are driving the adoption of EVs. Lithium-ion batteries have improved energy density, charging speed, and lifespan. Alternative battery technologies, like solid-state and lithium-sulfur batteries, show promise for even higher energy density, faster charging, and increased safety. Wireless charging technology is emerging, with high-power and high-efficiency systems potentially addressing concerns about charging infrastructure and range anxiety. V2G communication allows EVs to serve as mobile energy storage units, contributing to grid stability, load balancing, and renewable energy integration. Lightweight materials, like advanced composites and lightweight metals, can significantly reduce the weight of EVs, improving energy efficiency and overall performance. Autonomous driving technologies have the potential to improve safety, reduce congestion, and optimize energy use. V2X communication enables a wide range of applications, like intelligent traffic management and enhanced safety features. Circular economy approaches, including designing EVs with recyclability and reusability in mind, using recycled materials in manufacturing, and developing end-of-life recycling and repurposing strategies, can minimize the environmental impact of EVs and contribute to their sustainability
An Extensive Exploration of Techniques for Resource and Cost Management in Contemporary Cloud Computing Environments
Get PDFResource and cost optimization techniques in cloud computing environments target minimizing expenditure while ensuring efficient resource utilization. This study categorizes these techniques into three primary groups: Cloud and VM-focused strategies, Workflow techniques, and Resource Utilization and Efficiency techniques. Cloud and VM-focused strategies predominantly concentrate on the allocation, scheduling, and optimization of resources within cloud environments, particularly virtual machines. These strategies aim at a balance between cost reduction and adhering to specified deadlines, while ensuring scalability and adaptability to different cloud models. However, they may introduce complexities due to their dynamic nature and continuous optimization requirements. Workflow techniques emphasize the optimal execution of tasks in distributed systems. They address inconsistencies in Quality of Service (QoS) and seek to enhance the reservation process and task scheduling. By employing models, such as Integer Linear Programming, these techniques offer precision. But they might be computationally demanding, especially for extensive problems. Techniques focusing on Resource Utilization and Efficiency attempts to maximize the use of available resources in an energy-efficient and cost-effective manner. Considering factors like current energy levels and application requirements, these models aim to optimize performance without overshooting budgets. However, a continuous monitoring mechanism might be necessary, which can introduce additional complexities
Recommendations for implementing VR and AR in Education, Art, and Museums
Get PDFArtificial intelligence technologies are becoming more common, and schools, museums, and art exhibitions will need to alter their old methods of working and thinking processes to fully realize their potential. In an increasingly digital environment, incorporating VR and AR technology as well as wearable gadgets into various areas may help to increase participation. The strategic role and usage of VR and AR in influencing tourist experience at art galleries and museums, as well as its potential to improve education, needs to be explored in VR and AR in Education, Art, and Museums. This research provides some recommendations for museum supervisors, tour designers, academic software developers because it covers a wide range of topics such as digital training, digital heritage, and gaming
The Determinants of AI Adoption in Healthcare: Evidence from Voting and Stacking Classifiers
Get PDFArtificial intelligence (AI) has emerged as a disruptive force in the healthcare industry, driving new breakthroughs that promise to enhance treatment outcomes while simultaneously lowering costs. Artificial intelligence in healthcare has demonstrated promise to help doctors and patients at each step of the healthcare system, from an accurate diagnosis to urgent monitoring of patients and self-management of long-term illness. Despite physician and administrative interest, the use of these technologies in healthcare institutions remains limited. We hypothesized that risks such as black box issue, error rate, and legal risks halt the adoption. Similarly, technical combability in healthcare centers stemming from cloud adoption, the presence of IT skills in healthcare, and digitalized healthcare records significantly explain the AI adoption in healthcare. To test our hypotheses, we applied Ensemble Voting Classifier and Stacking Classifier algorithms. The ensemble voting classifier outperforms the stacking classifier in terms of accuracy. Our findings indicate that majority of healthcare institutions with limited technological compatibility and high perceived risks have no plans to use artificial intelligence at this time. The majority of healthcare institutions with moderate risk perceptions and moderate technical combability are indecisive about integrating artificial intelligence. Healthcare facilities with good technological combability and low (AI) perceived risks are either uncertain or eager to use artificial intelligence approaches. Both classifiers yielded almost identical results, demonstrating the validity of our empirical findings
Establishing Efficient IT Operations Management through Efficient Monitoring, Process Optimization, and Effective IT Policies
Get PDFEvery organization is becoming increasingly reliant on IT that is available, dependable, secure, and high-performing. The ability of an IT team to run its operations efficiently is directly and completely contingent on its ability to deliver resilient IT. The IT team must be able to identify, prioritize, execute, and manage the processes that drive operational tasks and activities in particular. IT teams may reach such goals more efficiently and consistently with the help of effective IT Operation Management processes and solutions. This research attempts how efficiency can be attained. More specifically, we focus on three broad components of efficient IT Operation management: 1) efficient monitoring 2) process optimization 3) and effective IT policies. IT infrastructure monitoring enables the detection of security threats and the resolution of operational issues before they cause harm to clients. We find that there are three significant practices to achieve efficient monitoring. They are: Organizing and Prioritizing Alerts, Providing Processed Data in a Dashboard, and Selecting a Trustworthy Vendor Partner. We also find that there are four challenges in IT infrastructure monitoring: It is sometimes necessary to take a proactive approach; after all, that\u27s what monitoring is all about. Here are some of the most typical monitoring difficulties that businesses, in general, and IT departments, in particular, face: Being beyond monitoring capacity, the ineffectiveness of outdated monitoring applications, increasing prices, and data capacity. IT process optimization technique identifies the most appropriate ways of satisfying an organization\u27s technological and informational needs on a proactive (and non-responsive) basis, with the main goal of supporting it in the long-term development of value. This research also explains discusses forming efficient IT policies such as policies for IT emergency intervention and disaster recovery, Security policies for IT infrastructure. Efficient IT policies provide information technology transparency for individuals in a business. IT policies assist to counter risks and manage risk while assuring that operations are efficient, effective, and consistent