Market Penetration Research Articles

The Application of New Media Marketing in Luxury Brand Communication

In the evolving landscape of luxury brand communication, this paper explores the transformative role of new media marketing in the dissemination and perception of luxury brands. Drawing insights from recent studies on social media impact on luxury consumption, it delves into how platforms like Instagram, Facebook, and WeChat have reshaped consumer behavior, particularly among the affluent and aspirational demographics. The paper also investigates the alignment of advertising strategies with the United Nations Sustainable Development Goals (SDGs), particularly focusing on women's empowerment, showcasing how luxury brands can leverage social responsibility to enhance their image and appeal. Strategies adopted by luxury brands in the new media era are analyzed, emphasizing the effectiveness of content marketing, influencer partnerships, and digital storytelling. Case studies highlight the success of brands like Gucci and Chanel in engaging audiences through innovative campaigns that blend heritage with modernity. An understanding of the nuances in different cultural contexts is crucial, as demonstrated by the need for sensitivity towards post-feminist ideologies in crafting messages of empowerment. The paper concludes by offering recommendations for luxury brands looking to optimize their new media marketing efforts. It suggests a balanced approach that integrates online and offline experiences, fosters community engagement, and prioritizes ethical and sustainable practices. By doing so, luxury brands can not only increase their market penetration but also contribute positively to societal goals, thereby ensuring long-term brand loyalty and relevance in an increasingly digital and socially conscious world.

Electric Vehicle Adoption: Implications for Employment in South Africa’s Automotive Component Industry

The transition to electric vehicles (EVs) will require significant changes in the automotive industry, particularly concerning its labour force. This study evaluates the impact of EVs on employment within South Africa’s automotive component manufacturing sector. A system dynamics model was developed to assess the effect of EV market penetration on component manufacturing employment over time. Key drivers of employment in the conventional and the EV component industries were identified and incorporated into the model. The results indicate a negative impact of EV penetration on employment of 18.3% when considering 20.0% EV sales (EV20) in 2040. Scenario analyses highlighted the influence of individual components, battery localisation, and load shedding on labour. Tyre and wheel manufacturing was found to be the most labour impactful component in the conventional industry against electrical engines in the EV counterpart. Localising 25.0% of battery production could increase employment by 6.9% and 2.7% in the EV40 and EV20 Scenarios. Load shedding has a detrimental effect on the country’s economy, assumed to reduce employment by 30.0%. However, strategic industry and policy interventions can mitigate the adverse effects of this transition.

Robotic availability, not payor status, determines access to robotic emergency general surgery hernia repair in California and Florida.

Previous studies have demonstrated that access to robotic surgery is influenced by socioeconomic factors, including insurance status. The 2010 Affordable Care Act established an avenue for states to expand Medicaid coverage, which has increased access to surgical care for many conditions. We hypothesized that socioeconomic disparities in access to robotic repair of non-elective emergency general surgery (EGS) hernias are less prevalent in California, a Medicaid expansion state, compared to Florida, which has not adopted Medicaid expansion. The 2021 California and Florida State Inpatient Databases were used to identify all EGS admissions with an ICD-10 procedure code for ventral or inguinal hernia repair. Elective procedures and those with concurrent unrelated abdominal procedures were excluded. Patient demographics, comorbidity burden, payor status, and income quartile were abstracted. Aggregation of hospital data identified high-volume trauma, robotic, and EGS centers. There were 15,683 EGS hernia procedures of which 11% underwent robotic repair: 14% in Florida and 8% in California. On multivariable logistic regression, older age, male sex, lower income, and Medicare insurance were associated with reduced odds of robotic hernia repair in California, but not in Florida, despite an uninsured rate of 10%. The greatest predictor of robotic surgery in both states was treatment at a robotic surgery center. Overall, accounting for patient- and hospital-level factors, hernia surgeries in Florida were more likely to involve robotics (OR 1.61, CI 1.42-1.81, p < 0.001) compared to California. There were fewer disparities in access to EGS robotic hernia repairs in Florida than in California. This suggests that robotic surgery access for EGS hernia repairs is primarily determined by institutional adoption of robotic surgery, not income or payor status. Compared to California, Florida appears to have greater market penetration of robotic surgery, which has increased access to robotic EGS for all patients.

Electric Vehicle (EV) Market Penetration in Countries with Rising Motorization Rates

Electric Vehicle (EV) Market Penetration in Countries with Rising Motorization Rates

ФОРМУВАННЯ НА СУЧАСНОМУ ЕТАПІ РИНКУ ФІНАНСОВИХ ТЕХНОЛОГІЙ В СВІТОВІЙ ЕКОНОМІЦІ

The current stage of development of the world economy is characterized by the process of increasing the role of the financial sector, as well as the transition to a new phase of development - innovation. Globalization in financial innovations is critical in international innovative development in today's conditions. The rapid spread of financial innovations under the conditions of financial globalization has become the main driver of the formation of the world economic system, contributing to the deepening of financial globalization. The formation of the financial services market is uneven because various factors influence it, including the level of development of information and communication technologies, the stability of the financial sector, and others. These factors have been studied by researchers, but the development of specific segments of the fintech market has its peculiarities. Fintech is a complex system that unites the sectors of new technologies and financial services, startups, and the relevant infrastructure. The financial services sector is increasingly actively using new technologies and tools to perform its functions and implement fundamentally new solutions in which consumers of services are interested. New technologies inherently changed not only the historically formed landscape of providing financial services, giving it freshness and dynamics, but also changed the attitude to such a concept as "money", realizing the transition from cash to virtual money in a reasonably short period. The industry provides subjects of financial relations with a wide range of innovative technologies, among which robotics, biometrics, remote banking, P2P lending, and many others have become vital. The fintech industry is expected to grow due to increased market penetration rates for existing services and their international expansion. The transition from the traditional financial services system to a digital one provides excellent opportunities for large financial companies and FinTech startups to work with banks or financial organizations. As more critical financial infrastructure projects come into production, more players will be interested in implementing digital financial technologies.

Real-Time Freeway Crash Detection Framework using Connected Vehicle Waypoint Data

Accurate and timely detection of traffic accidents is crucial for transportation agencies seeking swift responses and effective traffic management, particularly on freeways where crash severity and traffic flow disruptions are amplified. While several methods have been developed using cameras or infrastructure-mounted sensors, these approaches may face challenges in geographical scalability. To address this issue, a novel approach has been developed that leverages real-time connected vehicle trajectories at a market penetration rate of 4%–9%. The method involves extracting five key features from individual journeys that sense the speed and acceleration fluctuations. The results demonstrate promising outcomes, achieving an overall accuracy of 63.5% with 4.1% false detections and 33.4% non-detections. This accuracy surpasses the speed-alone model using the same data by 24%. Furthermore, higher traffic volumes lead to even greater accuracy, exceeding 80% at level of service D and 90% at level of service E. The developed algorithm also exhibits precision in crash detection, with a mean latency of only 2.5 min after the actual incidents. The entire processing time may additionally add up to 1 min. The robustness of the model is tested for a single day on one of the interstates, providing promising results. This study highlights the potential of connected vehicle data in enhancing crash prediction methods and underlines its value for the safety and efficiency of future transportation systems.

Evolution of Paytm's Business Model

This case study explores the evolution of Paytm's business model, highlighting its transformation from a mobile recharge platform to a multifaceted digital services powerhouse. Initially launched in 2014 by One97 Communications as a prepaid mobile recharge and bill payment platform, Paytm rapidly diversified its offerings to include e-commerce, financial services, and digital payments, capitalizing on India's burgeoning digital economy. The study examines key phases in Paytm's business model evolution, including its expansion into the financial sector with services such as Paytm Wallet, Paytm Payments Bank, and investment products.The analysis focuses on strategic decisions that fueled Paytm's growth, such as its aggressive market penetration strategies, partnerships with major retailers and financial institutions, and its adaptation to regulatory changes. It also highlights how Paytm leveraged technology and data analytics to enhance customer experience and streamline operations, contributing to its market dominance.Furthermore, the case study addresses the challenges faced by Paytm, including intense competition, regulatory hurdles, and the need for continuous innovation to maintain its competitive edge. By examining these aspects, the study provides insights into how Paytm's adaptive business model has enabled it to remain a leading player in India's digital ecosystem.The findings underscore the importance of flexibility and diversification in sustaining growth in the rapidly evolving digital services sector. This case study offers valuable lessons for other businesses seeking to navigate the dynamic landscape of digital transformation and innovation.

Indonesian SMES and Global Market Penetration: The Effects of Human Capital Investment, Government Role, and Technological Progress

MSMEs play a significant role in supporting the country's economy as they account for 60.5% of GDP. MSMEs confront a number of difficulties related to financing, supply, and market demand that need to be given more consideration in order to support their entry into the global market. The purpose of this study is to examine how government involvement, technology advancement, human capital investment, and entrepreneurial orientation affect MSMEs (micro, small, and medium-sized firms) in Indonesia and their internationalization strategies. This study uses a quantitative approach with data collection techniques using a Likert scale questionnaire. Then descriptive analysis and Partial Least Squares (PLS) are used to analyze the data. The study's findings show that technical change significantly affects MSMEs' internationalization strategies; in contrast, entrepreneurial orientation, investments in human capital, and the role of the government are not as significant in this regard. However, this research offers stakeholders improved guidance for bolstering MSMEs' success and expansion in global markets, as well as for widening the gap in the global MSME market to promote Indonesia's sustainable economic growth.

Strategi Pemasaran untuk Meningkatkan Penjualan Mahalona Kopi Karawang

The implication for Mahalona Kopi is that it needs to design more competitive marketing strategies and offer products or services to potential markets. This research aims to formulate a marketing strategy for Mahalona Kopi and take advantage of opportunities and overcome challenges so that the coffee shop business can continue to operate and generate profits. The data processing method used in this research is descriptive qualitative method, with the analysis process using SWOT analysis. Data sources include primary data and secondary data, obtained through direct observation and in-depth interviews related to opportunities and challenges in the coffee shop business. The matrix results show that Mahalona Kopi is in cell IV (Grow and Build). The appropriate strategy for this cell position at Mahalona Kopi is an intensive strategy, such as market penetration, product development, and market development.

Market Penetration Strategy by Increasing Firm Competitiveness

To achieve successful market penetration, businesses must navigate complexities related to culture, legal frameworks, economic conditions, and competition. Businesses must decide whether to standardize their marketing strategies across different markets or adapt them to suit unique market characteristics. Competition is the ability to perform better, and faster. In facing competition, companies need to determine the right strategy, because in general companies are trying to survive, grow and develop. The purpose of the Market Penetration Strategy research by Increasing Company Competitiveness can include several aspects, namely, Assessing the company's strengths and weaknesses. Conducting market analysis to understand existing opportunities and challenges, including consumer preferences and behavior, and market trends and Developping an effective Market Penetration Strategy to increase market penetration, such as products, improving customer service, or competitive pricing strategies. This study uses a descriptive qualitative method to find out how PT. AJS Bumiputera markets its products, using market penetration to increase competitiveness, or to find out what the biggest challenges are in its market penetration strategy. This study uses a qualitative method as one of the methodologies in research that does not yet have a standard definition and is generally agreed upon for use. From the results of the study it is known that PT. Bumiputera Sharia Life Insurance, using market penetration through digital platforms such as social media, company websites, and online advertising campaigns to reach a wider audience. Organizing events, seminars, or workshops, related to finance or health. Providing education about the benefits of insurance products to the public, conducting direct promotions through telemarketing, or face-to-face marketing to introduce products directly.

Predicted Expenditure for Prescription Drugs for Multiple Sclerosis in the Italian Market Between 2023 and 2028: Results of the Oracle Project.

Multiple sclerosis (MS) is a chronic neurodegenerative disease that leads to impaired cognitive function and accumulation of disability, with significant socioeconomic burden. Serious unmet need in the context of managing MS has given rise to ongoing research efforts, leading to the launch of new drugs planned for the near future, and subsequent concerns about the sustainability of healthcare systems. This study assessed the changes in the Italian MS market and their impact on the expenditures of the Italian National Healthcare Service between 2023 and 2028. A horizon-scanning model was developed to estimate annual expenditure from 2023 to 2028. Annual expenditure for MS was calculated by combining the number of patients treated with each product (clinical inputs) and the yearly costs of therapy (economic inputs). Baseline inputs (2020-2022) were collected from IQVIA® real-world data, while input estimation for the 5-year forecast was integrated with analog analyses and the insights of clinicians and former payers. The number of equivalent patients treated in 2028 in Italy was estimated at around 67,000, with an increase of 10% versus 2022. In terms of treatment pattern evolution, first-line treatments are expected to reduce their shares from 47% in 2022 to 27% in 2028, and Bruton tyrosine kinase inhibitors are expected to reach 23% of patient shares. Overall, expenditure for MS is estimated to decrease from €721 million in 2022 to €551 million in 2028, mainly due to losses of exclusivity and renegotiation of drug prices. Despite the increase in the number of patients treated for MS and the launch of new molecules that will reach high market penetration, the model confirmed sustainability for the Italian National Healthcare Service.

Understanding the zero-emission vehicle market spatial diffusion and its determinants from 2019 to 2022 using spatial econometric models

Due to the rapid rise in the acceptance of zero-emission vehicles (ZEVs), much research has been conducted on the market evolution of alternative fuel technology. The research reported in this paper builds on prior studies by incorporating several new directions. Firstly, the spatial distribution of ZEV purchases in California is explored, then seven models (two nonspatial models and five spatially explicit models) are developed to predict regional ZEV sales. The predictions are based on fundamental and widely accessible characteristics such as infrastructure and demographic statistics. Next, a spatial econometric model known as the “spatial error model” is chosen to distribute ZEV sales from their original postal code (ZIP) level to the more often utilized US census tract level. This allows for carrying out a comprehensive analysis that includes studying the correlation of ZEV sales with local incentives and disadvantaged communities. Results reveal that ZEV sales in California increased significantly between 2019 and 2022, as spatial autocorrelation decreased. Vulnerable groups were less likely to have access to ZEVs, particularly during the initial stage of the ZEV market penetration in 2019. As expected, regions with considerable ZEV sales tended to also experience substantial purchase rebates and lower disadvantaged population, especially in 2019.

Study on mixed traffic characteristics around highway on-ramp bottleneck using a microscopic simulation model

In the early mixed traffic environment, connected and automated vehicles (CAVs) tend to follow simple control rules for the sake of traffic safety and stability. Comprehensive analysis of overall mixed traffic performance and vehicle to vehicle interactions around highway on-ramp bottleneck is a basis for further traffic management and control. And yet CAVs in existing researches are mainly in the form of cooperative vehicular platoon, and mixed traffic scenarios within simulation software are not applicable for in-depth investigation. The purpose of this paper is to develop a microscopic simulation model to study in detail lane-based mixed traffic performance around the highway on-ramp. This model firstly considers vehicle characteristics of individual human vehicles (HVs) and CAVs by combining different microscopic traffic models. After the hypothetical on-ramp bottleneck structure is constructed, various simulation scenarios are developed under varying traffic volumes and changing market penetration rates (MPRs) of CAVs. Simulation results show that mixed traffic flow is improved in terms of congestion patterns and traffic capacity. For oscillating and nearly homogeneous congested traffic, congestion degrees are greatly reduced when CAV MPR above 30 % and 50 % respectively. Mixed traffic capacity is increased by 19.3 % when a smaller desired time gap set for CAVs, while it shows no significant change in a larger value. In the HV-HV interactions, traffic conflicts are slightly influenced by CAVs. Comparatively, conflict situations in HV-CAV interactions get worse, the proportion of time to collision (TTC) greater than 2 s monotonically declining with the rise in CAV MPR. It is concluded that traffic characteristics overall show a good momentum when MPR of CAV and the desired time gap of CAVs in mixed traffic are appropriate.

The economic impact of social media marketing: A study of consumer goods in emerging markets

The economic impact of social media marketing on consumer goods in emerging markets has become increasingly significant, driven by rapid digital adoption and the growing influence of online platforms. This study explores how social media marketing strategies employed by consumer goods companies contribute to economic growth in these regions. By leveraging data from various emerging markets, the research examines the role of social media in enhancing brand visibility, consumer engagement, and market penetration. The study highlights the ability of social media to reach vast audiences at relatively low costs, enabling companies to build brand awareness and foster consumer loyalty in markets where traditional advertising channels may be less effective or accessible. Through targeted advertising, influencer partnerships, and interactive campaigns, social media marketing has proven instrumental in driving sales and expanding market share for consumer goods companies. This, in turn, has stimulated local economies by increasing consumer spending, creating jobs, and encouraging competition. Furthermore, the study discusses the multiplier effect of social media marketing on economic development, particularly in how it helps local businesses integrate into the global economy. By providing a platform for smaller companies to compete with established brands, social media has democratized access to markets and facilitated the growth of entrepreneurial ventures in emerging economies. However, the study also acknowledges the challenges and limitations of social media marketing in these contexts, such as digital divides, varying levels of internet penetration, and the need for culturally sensitive content. The findings underscore the importance of adapting social media strategies to the specific characteristics of emerging markets to maximize their economic impact. In conclusion, social media marketing has become a powerful tool for driving economic growth in emerging markets by enhancing brand presence, increasing consumer demand, and fostering competitive business environments. As digital ecosystems continue to evolve, the role of social media in shaping economic landscapes in these regions is expected to expand further, offering significant opportunities for consumer goods companies and local economies alike.

The Role Mechanism of Social Preferences and Price Advantage in the Market Economy

In today's market economy environment, social preferences and price advantage, as two core driving forces, directly influence market operation and development trajectories. As consumer demand becomes increasingly diversified, social preferences intuitively reflect deep-seated cultural identity and value orientations, even guiding market trends. Price advantage, as the cornerstone of market competition, also impacts corporate production and development. These two elements intertwine: social preferences infuse emotional and cultural content into pricing strategies, while price advantage becomes an effective means to satisfy social preferences and achieve market penetration. A deep understanding and skillful application of these mechanisms are crucial for companies to navigate the complex and ever-changing market environment and achieve sustainable development.

Thermal Cameras and Their Safety Implications for Pedestrian Protection: A Mixed Empirical and Simulation-Based Characterization

Multiple sensing technologies exist for advanced driver support and driving automation systems. Car manufacturers combine different solutions to increase the robustness and operational capabilities of driving automation technology perception systems. One sensing method that did not achieve high market penetration with respect to other solutions is the thermal camera. Thermal cameras can operate in low-light and high-contrast conditions as they do not need external sources of illumination. Instead, they are sensitive to the infrared radiation emitted by any surface above 0 K. Thus, thermal cameras can be a suitable candidate to compensate for the weaknesses of visible cameras. To establish the potential benefit of thermal cameras for pedestrian protection, this paper reports on an experiment using state-of-the-art thermal imaging sensors. The authors’ scientific effort includes a characterization of the infrared sensor capability to identify pedestrians when coupled with a detection algorithm and provides a simulation-based investigation of the potential safety benefits of thermal camera adoption. The analysis additionally includes a heuristic characterization of the detection capabilities of a passenger car equipped with visible cameras to provide a baseline comparison. Ultimately, the thermal sensors return noteworthy detection capability that could lead to a potentially significant improvement in road safety on rural roads provided that the sensor has sufficient resolution.

A CAV-Lead speed advice approach considering local spatiotemporal traffic state near bottlenecks

Bottlenecks of the freeway generated especially by traffic accidents or temporary work zones contribute to significant reductions in system throughput and hinder the efficient traffic operations. It is imperative to take proactive measures to improve traffic state. With the rapid advancements in intelligent transportation, connected and autonomous vehicles (CAVs) have attracted much attention by its speculated capabilities in improving traffic safety and well-organized operational coordination. Therefore, reasonably utilizing the advantages of CAVs is possible to reduce the impact induced by bottlenecks. In this research, we propose a novel algorithm called CAV-Lead to obtain the CAV’s regulated speed under mixed CAVs and human-driven vehicles (HVs) environment to improve the overall utilization of the freeway capacity near bottlenecks. Firstly, we illustrate the basic principle of the CAV-Lead algorithm that takes both microscopic and macroscopic traffic characteristics into account. Then, based on the local spatiotemporal traffic state, the CAV-Lead algorithm is proposed to determine each CAV’s speed under mixed flow. Furthermore, a real-time simulation control framework considering the random behavior of HVs is presented. Moreover, several simulation evaluations including comparisons with basic scenarios and similar research are conducted under various CAV market penetration rates (MPRs). The results demonstrate that the CAV-Lead could improve the traffic performance, especially for the high traffic demand with certain MPRs.

PENGEMBANGAN STRATEGI BISNIS PADA HOTEL XYZ DENGAN ANALISIS MATRIX IFE DAN EFE

The increases of tourist visits in Bali can influence the development of the hotel industry. The significant increase in the number of tourists has caused demand for accommodation services, especially hotels, which has an impact on increasing hotel competition. This research aims to identify and design a business strategy at hotel XYZ through several stages such as IFAS (Internal Factors Analysis Summary) and EFAS (External Factors Analysis Summary) analysis. This research uses a qualitative descriptive method with data collection methods through interviews. Based on the EFAS and IFAS values, the company is in quadrant V with a hold and maintain business strategy. The results of this research provide strategies that can be implemented by XYZ Hotel, namely market penetration strategies and product development strategies.

A cooperative perception based adaptive signal control under early deployment of connected and automated vehicles

Connected vehicle-based adaptive traffic signal control requires certain market penetration rates (MPRs) to be effective, usually exceeding 10%. Cooperative perception based on connected and automated vehicles (CAVs) can effectively improve overall data collection efficiency and reduce required MPR. However, the distribution of observed vehicles under cooperative perception is highly skewed and imbalanced, especially under very low CAV MPRs (e.g., 1%). To address this challenge, this paper proposes a novel deep reinforcement learning-based adaptive traffic signal control (RL-TSC) method that integrates a traffic flow model, known as the cell transmission model (CTM), denoted as CAVLight. Traffic states estimated from the CTM are integrated with the data collected from the cooperative perception environment to update the states in the CAVLight model. The design of reward function aims for reducing total vehicle delays and stabilizing agent behaviors. Extensive numerical experiments under a real-world intersection with varying traffic demand levels and CAV MPRs are conducted to compare the performance of CAVLight and other benchmark algorithms, including a fixed-time controller, an actuated controller, the max pressure model, and an optimization-based adaptive TSC. Results demonstrate the superiority of CAVLight in performance and generalizability over benchmarks, especially under 1% CAV MPR scenario with high traffic demands. The influence of CTM integration on CAVLight is further explored through RL agent policy visualization and sensitivity analysis in CTM parameters and CAV perception capabilities (i.e., detection range and detection accuracy).

PACC: A platoon-based adaptive cruise control strategy based on leader-following information topology to mitigate traffic oscillations under CAV environment

Traffic oscillations, often induced by repetitive acceleration and deceleration maneuvers in vehicles’ car-following behaviors, can cause many negative impacts on the traffic flow. With the development of connected and automated vehicle (CAV) technologies recently, scholars have made numerous effects on mitigating the propagation of traffic oscillations through a variety of advanced CAV control strategies, especially those related to the CAV platoon control. Different from the previous works, this paper proposed a platoon-based adaptive cruise control (PACC) strategy for CAV platoon to mitigate the traffic oscillations. The strategy is designed based on the novel and unique leader-following (LF) information topology. Built on the classical proportional-derivative (PD) controller that is implemented in the adaptive cruise control (ACC) strategy of autonomous vehicles (AVs), the PACC strategy is exquisitely designed to ensure the string stability of entire CAV platoon and the critically damped condition of each following CAV in the platoon. Credit to the rapid response of following CAV to the vibration of leading CAV’s dynamic status under LF information topology and the thorough consideration of string stability and damping characteristics in the PD controller design, the PACC strategy enables the CAV platoon to mitigate the traffic oscillations more efficiently than the existing cooperative adaptive cruise control (CACC) and ACC strategies. The numerical experiment for the mixed traffic flow on a single-lane ring road indicates that, when the CAV platoon adopts the PACC strategy, the performance of traffic flow in terms of operational efficiency, driving safety, passenger’s comfort, and fuel economy is substantially enhanced, compared with CACC and ACC strategies. In addition, the performance of PACC strategy gradually improves with the increase of market penetration rate (MPR) of CAVs and length of CAV platoon. Overall, the proposed PACC strategy is a promising solution to the mitigation of traffic oscillation under the CAV environment.