Entry Barriers Research Articles

On excessive entry in Bayes‐Cournot oligopoly

AbstractIn a Cournot industry where firms are privately informed about their marginal costs, raising entry barriers (i.e., imposing strictly positive, but not too large, entry costs) increases expected output, entrants' profits, total welfare, and might benefit consumers. Under Bayes‐Cournot competition, firms react to the expectation (conditional on entry) of rivals' costs rather than to their actual costs. This creates scope for entry by relatively inefficient types. Entry costs that prevent these high‐cost types from entering increase inframarginal (lower‐cost) types' and rivals' expected output. As a result, they increase profits and, unless they reduce output variability too much, also consumer surplus.

The Role of Fintech in Increasing Retail Participation in the Indian Stock Market

The rapid growth of financial technology (fintech) has brought substantial changes to retail investor activity in the Indian stock market. This study examines how fintech developments have boosted retail participation from 2017 to 2024, primarily through mobile trading platforms, robo-advisors, and digital payment solutions. Using a quantitative research method with secondary data, the study tracks the year-over-year increase in retail shareholders, noting a significant rise particularly after 2021. The findings point to factors such as the Digital India initiative, growing adoption of fintech, and evolving market conditions as key drivers that have reduced entry barriers for retail investors. The analysis establishes a connection between the advancement of fintech and improved access to the stock market, underlining fintech's significant contribution to democratizing investment opportunities. Nonetheless, ongoing issues like regulatory challenges and financial literacy gaps remain, highlighting the need for continued efforts to maximize fintech's potential in fostering sustainable growth in retail investment.

Indie economics: social purpose, lay expertise and the unusual rise of modern monetary theory

ABSTRACT We argue that the IPE literature on economic expertise has been characterised by ‘methodological elitism’ that makes it ill equipped to account for the influence of heterodox and grassroots forms of expertise. To remedy this, we posit a theoretical framework that emphasises the tensions between two forms of professional legitimacy. One is internal legitimacy and it is rooted in appeals to scientific objectivity, political neutrality and high professional barriers of entry. However, internal legitimacy may clash with external legitimacy, which is a function of a clear articulation of social purpose. Taking the surprising rise of Modern Monetary Theory as a case study, the paper makes two claims. First, its ideas did not coalesce into a distinctive heterodox brand of economics through traditional mechanisms like academic peer-review and citation networks, but through intense online activity. Second, the messaging that spurred MMT consistently combined constitutive claims with explicit declarations of social purpose. The result was an open project with a broad normative appeal, which successfully enrolled a large group of passionate followers and co-creators. To date, IPE scholars have been blind to such alternative forms of knowledge production.

Bank Entry Barriers and Firms’ Risk-Taking

Bank Entry Barriers and Firms’ Risk-Taking

A Comparative Analysis of Ethnic Networks and Internationalization of Latin American Agri-SMEs: The Case of Argentina, Brazil, and Chile

This paper investigates the key drivers influencing the internationalization of agricultural small and medium-sized enterprises (agri-SMEs) in Latin America, with a particular emphasis on the role of social and ethnic networks. Focusing on Argentina, Brazil, and Chile—three of the region’s largest agricultural economies—this study examines how familial and cultural connections between descendants of European immigrants and European entrepreneurs facilitate the global expansion of agri-SMEs. Using a cross-sectional quantitative analysis, data from agri-SME managers reveal the importance of these networks in reducing market entry barriers by providing insider knowledge of foreign markets, regulatory conditions, and potential business partnerships. The findings demonstrate that ethnic networks significantly reduce market entry barriers, providing Latin American agri-SMEs access to essential insider knowledge on foreign markets and local regulations, thereby facilitating internationalization. Additionally, agri-SMEs that leverage these networks are better positioned to meet growing global demands for sustainable, traceable food products, gaining a competitive advantage in international markets. The strength and frequency of interactions within ethnic networks are positively correlated with the degree of internationalization, highlighting the importance of social capital in overcoming operational challenges. This paper contributes to the literature by highlighting the underexplored role of ethnic networks in shaping the international marketing strategies of agricultural firms and their capacity to adapt to evolving consumer behaviors. The study offers practical insights for supporting the global integration of agri-SMEs in Latin America, addressing both operational challenges and the increasing need for sustainable food production practices.

Single cell transcriptional analysis of human adenoids identifies molecular features of airway microfold cells.

The nasal, oropharyngeal, and bronchial mucosa are primary contact points for airborne pathogens like Mycobacterium tuberculosis (Mtb), SARS-CoV-2, and influenza virus. While mucosal surfaces can function as both entry points and barriers to infection, mucosa-associated lymphoid tissues (MALT) facilitate early immune responses to mucosal antigens. MALT contains a variety of specialized epithelial cells, including a rare cell type called a microfold cell (M cell) that functions to transport apical antigens to basolateral antigen-presenting cells, a crucial step in the initiation of mucosal immunity. M cells have been extensively characterized in the gastrointestinal (GI) tract in murine and human models. However, the precise development and functions of human airway M cells is unknown. Here, using single-nucleus RNA sequencing (snRNA-seq), we generated an atlas of cells from the human adenoid and identified 16 unique cell types representing basal, club, hillock, and hematopoietic lineages, defined their developmental trajectories, and determined cell-cell relationships. Using trajectory analysis, we found that human airway M cells develop from progenitor club cells and express a gene signature distinct from intestinal M cells. Surprisingly, we also identified a heretofore unknown epithelial cell type demonstrating a robust interferon-stimulated gene signature. Our analysis of human adenoid cells enhances our understanding of mucosal immune responses and the role of M cells in airway immunity. This work also provides a resource for understanding early interactions of pathogens with airway mucosa and a platform for development of mucosal vaccines.

Automatic animal monitoring systems based on AutoML technologies

In contemporary agricultural contexts, the sector is experiencing active processes of automation, underscoring the need for effective tools to develop such automated systems. The utilization of automation tools enhances the efficiency of numerous processes, including those in the domain of animal monitoring. This article examines the application of the AutoML approach as a means for automating the process of generating deep learning models employed in automatic monitoring systems. The VGG19 architecture has been chosen as a testbed for demonstrating the capabilities of the developed technologies. This well-established architecture for deep learning models is designed for object recognition in images.The present study implements a technology for automated structural-parametric synthesis of VGG19 models and the optimization of their hyperparameters. Such an approach allows for the automated creation of models tailored to specific applied problems, even for users lacking specialized knowledge in deep learning.The system delineated in this work is developed on the AutoGenNet software platform, which embodies the No-Code development concept. This concept conceals complex aspects of model creation and training processes from users, significantly lowering the entry barrier for newcomers. Additionally, the AutoGenNet platform incorporates a mechanism for the automatic generation of software wrappers, facilitating efficient interaction with trained models.All aforementioned aspects have contributed to the effective implementation of the AutoML approach for automating the generation and training processes of the VGG19 model. Consequently, the processes associated with solving automatic monitoring tasks reliant on deep learning models have been significantly simplified and expedited.The developed system has been tested on the task of recognizing individual cows. Test results indicated that the system possesses a high degree of scalability and can be adapted for the automated generation of other object recognition models, thereby opening avenues for addressing a diverse array of applied challenges related to the monitoring of various animal species.

Corporate risk disclosure in response to heightened entry threat: Evidence from a quasi-natural experiment in China

Using the deregulation of market entry barriers in China as a quasi-natural experiment, this study examines how increased entry threats affect incumbent firms' risk disclosure. We find that firms respond by increasing their market-related risk disclosures. This effect is stronger among firms facing higher economic uncertainty, lower financial constraints, greater product market competition, and higher information transparency. Mechanism analysis shows that increased risk disclosure weakens the link between deregulation of market entry barriers and new firm entry, suggesting that such disclosures can effectively deter potential competitors. Moreover, while market reactions to market risk disclosures are neutral, they are negative for operational and financial risk disclosures. Our findings suggest that firms strategically disclose market risks to mitigate entry threats, thus enhancing their resilience and adaptability in dynamic markets.

Stepping forward with ease: Government debt governance as a catalyst for entrepreneurship

This study evaluates the causal effect of government debt on entrepreneurship. Exploiting New Budget Law reform in China that regulates the scale of local government debt, we find that government debt reduction bolsters entrepreneurial ventures by optimizing land utilization and enhancing access to start-up loans. Consistently, the entrepreneurial effect is more pronounced in unregulated industries and downstream sectors. Furthermore, we demonstrate that government debt reduction also contributes to entrepreneurship quality. It induces smaller entrants with higher survival rates post-reform, resulting in more incumbent enterprises exiting. Our results underscore the benefits of encouraging government debt governance experimentation in lowering entry barriers.

Cultural Norms and the Gendered Impact of Entrepreneurship Policy in Mexico

This article explores how policies that reduce barriers to entrepreneurship impact underrepresented groups differently depending on local norms and cultural beliefs. While prior studies suggest that underrepresented groups should benefit more than other groups do from policies lowering entry barriers, the empirical evidence is mixed. We argue that the absence of normative and cognitive support can undermine the effectiveness of these policies for underrepresented groups. To explore this, we leveraged the staggered rollout of a policy that reduced entry barriers to entrepreneurship in Mexico. The results show that while the policy increased the number of businesses founded by men, it had a small and statistically insignificant impact for women, thus exacerbating the gender gap in entrepreneurship. Further analyses suggest that while women were not more likely to become involved in entrepreneurship as founders, they did become engaged in alternative roles within new ventures, often leaving other forms of employment to enter unpaid work in businesses founded by men in their household. The effects of the policy on the gender gap in entrepreneurship and unpaid work were more pronounced in areas with a strong patriarchy logic and among married individuals. This research highlights the need to consider context in the design of policies intended to encourage entrepreneurship.

Doubling Indian Agri Export through Natural Farming Management, Horticulture & African Markets

Aims: We explore the scope of escalating agriculture export in doubling farmers income and rational use of the growing Indian agriculture surplus and consequent glut, farmer distress. Study Design: The study is exploratory type and was conducted by literature survey and discussion with farmers, experts and industry. Methodology: The study was conducted by field visits to exporting, farmer exporters and experts during 2017 to 2022 by visiting farmers in Amaravati and Palghar districts, exporters in Mumbai city and experts at Pune city. Their data were triangulated with the literature from reputed agri-research institutions. Results: Doubling agri export can help to doubling farmer’s income (DFI) as export price is premium and profitability higher, besides increasing foreign exchange. Fruits & vegetables (F&V) is the largest agri-export segment globally but meagre 9th rank among Indian agri-export basket. Focussing on larger or costly market segment such as fruits & vegetables having higher productivity & surplus, rather than the cereals can help. Recent natural farming mission can aid in it and safeguard consumer and farmer’s health such as from the cancer. Indian F&V production more than doubled in the past 2 decades to exceed grains production, due to their health benefits. Maximum residue level (MRL) is the export benchmark so promoting low/ no pesticide techniques under the recent Indian natural farming (NF) mission can help to triple Indian agri-exports to $ 100 billion by 2030 from $35 billion in 2023, through horticulture, dairy and tea, cocoa that are in demand and valued. African markets can be tapped as it imports majority of its food and has less entry barriers. Policy may focus on fruits like Banana and premium for NF produce. Conclusion: Focusing on fruits & vegetables (F&V), dairy, lipids & adopting the low/ no “pesticide residue” standard etc. can boost Indian agri-exports.

Agent-based digital traffic model generation for regions facing data scarcity using aggregated cellphone data: a case study for Brussels

ABSTRACT The adoption of agent-based models (ABMs) in transport research has highlighted their potential in digitally simulating travel behaviour from a bottom-up perspective. However, generating ABMs remains a complex multi-step process, often suffering from the lack of model representation or reliance on proprietary data, thereby limiting ABMs' transferability, especially in regions facing data scarcity. This research presents a systematic ABM generation algorithm for Brussels, Belgium, that generates high-quality ABMs more representative of real-life travel patterns, including incorporating external travel demand and allowing multiple destinations for the same activity types in activity chaining. Additionally, our algorithm's input data only contains social-spatial data and aggregated cellphone matrices. Due to the ubiquitous nature of such data worldwide, our algorithm demonstrates significant transferability to other regions for ABM generation while preserving individual privacy. We demonstrate the input data and the proposed algorithm step by step. The ABM generated using MATSim is validated against real-world data regarding mode share, distance share, travel time distribution and traffic counts. Overall, this research would serve as valuable guidance for ABM modellers in data collection and specific modelling setups, lowering the entry barrier of ABM research towards more efficient, representative and reproducible ABMs.

Modelling the Interaction Between Incumbents and New Entrants with a Game Theory Approach: A Case Study of Public Transportation

The transformative influence of new entrants on industries and heightened competition underscores their significance. Mature companies, threatened by their entry, deploy multiple incentives to forestall market penetration. Conversely, consumers embrace fresh participants, creating a dichotomy in reactions. This has spawned escalated conflicts between mature firms and newcomers, rooted in the latter's market entry. This study navigates this landscape by delving into the strategies, preferences, and priorities of these actors, seeking stable equilibrium and reconciliation points for these conflicts. Employing thematic analysis, it distills options, feasible scenarios, and relative preferences of each stakeholder. These insights undergo scrutiny via the GMCR + decision support model. Among 21 conceivable scenarios, the study unveils three equilibria and a semi-stable state, suggesting mature companies recalibrate their stance to explore synergies with new entrants. This research offers a panoramic perspective on the intricate interactions between mature companies and new entrants, transcending the narrow confines of entry barriers.

Migrant Women in the UK’s Digital Economy: The Elimination of Labour Market Barriers in the Digital Labour Market

This research paper delves into the complexities migrant women face within the UK labour market, with a specific focus on the digital economy’s role as both a barrier and a conduit for employment opportunities. Migrant women in the UK encounter dual barriers to labour market entry: systemic challenges rooted in migration and gender biases, and the digital divide that exacerbates access and inclusion issues within the burgeoning digital economy. Through an exploratory descriptive analysis, this study explores how digitalism—defined as the integration of digital technologies into economic and societal practices—circumvents traditional labour market entry barriers such as languages barriers. By setting out the grounds for a potential hypothesis and further research in the era of AI, this paper underlines how through the implementation of AI tools, traditional barriers such as language barriers are eliminated in the digital labour market.

Housing Market Segmentation as a Driver of Urban Micro-Segregation? An In-Depth Analysis of Two Viennese Districts

The concept of segregation analyses the unequal distribution of social groups between neighbourhoods. It rests on two assumptions: that of homogeneous neighbourhoods and of a market liberal housing system. Both assumptions are applicable the context of American cities, but they display severe limitations when applied to the European context. Vienna’s housing market is particularly highly segmented, not only throughout the city as a whole but also within neighbourhoods. In the densely built-up area, residential buildings of different segments with different underlying rent regulations and entry barriers can be found side by side. Therefore, buildings are expected to show varying tenant and owner structures, which undermines the idea of a homogeneous neighbourhood. Against this background, we analyse at the micro scale small neighbourhoods defined by 100 m grid cells in a case study of two inner-city Viennese districts (districts 6 and 7) characterised by a particularly vivid housing-transformation and commodification dynamic. Using a novel and fine-grained dataset combining building information with the socio-economic data of households, we investigate the patterns and dynamics of income inequality and income segregation, as well as the relationship between housing market segments and socio-economic patterns. As data comprise two cross-sections for the years 2011 and 2020/21, changes in the neighbourhoods during the house-price boom period are also considered. This leads us to ask the question: How do housing market segmentation and its related changes affect income inequality and segregation at the micro scale? Our analysis delivers two main results: Firstly, we show the existence of marked social variation and related dynamics at the micro scale, even within a small urban area. Secondly, we show that the spatial distribution of housing market segments has a strong impact on income inequality in the neighbourhood.

How sustainability can get a competitive advantage: State of the art for stationary battery storage systems

Stationary battery storage systems are becoming a critical energy infrastructure around the world. Therefore, responsible handling of battery materials is a fundamental precondition to avoid future social, environmental, and political conflicts. Global battery regulations support sustainable batteries to drive new business models on reuse, remanufacturing and recycling. With strict environmental market entry barriers, the EU will set minimum sustainability standards with the new EU-Battery Directive. The US Inflation Reduction Act provides financial incentives for a scale-up of the domestic battery industry. A hotspot analysis for the residential storage system VARTA.wall shows that a combination of reuse and recycling strategies can reduce the climate change impact by up to 45% and mineral resource use by up to 50% compared to initial battery designs. However, specific sustainability criteria and manufacturer-independent standards need to be set up by politics and industry organizations to bring the necessary technical and logistic infrastructure to the market. The challenge is to set up sustainability criteria strict enough to ensure responsible material handling but still allow cost-effective, practical solutions as well as affordable battery standards. Therefore, our analysis shows the limits of current and the need for future regulations to shift market incentives to sustainable batteries and their infrastructure.

SP8.6 - Exploring Barriers of Entry for Women Pursuing Surgery: Impact of a Conference on the Confidence, Understanding, and Preparedness of Attendees

Abstract In the UK, women are underrepresented in surgery. Women make up only 16% of consultant surgeons and 34% of surgical registrars in the UK, whilst 59% of medical students are female. This project aims to explore the impact of conferences on perceived barriers and attitudes of female medical students aspiring to become surgeons. A survey was administered to 130 attendees, yielding 95 eligible responses, at a national student-led conference held at UCL encompassing speaker events, workshops, and speed mentoring. Pre- and post- questionnaires were provided. This included an open ended question on personal barriers, and a 5-Point Likert Scale to assess opinions on barriers of entry, confidence in surgical skills, preparedness for a surgical career, and understanding of challenges faced by women in surgery. Wilcoxon Signed-Ranks Test was used to assess statistical significance. The study included participants aged 18-30 from 23 universities and NHS trusts, representing 7 ethnic groups and 12 medical professions, with medical students comprising 87% of the cohort. Following the conference, 14 barriers of entry were analysed and there was a notable average increase in measured outcomes: confidence in surgical skills by 175%; preparedness by 192%; and understanding of the challenges faced by 177%. Overall, an average increase of 181% across reported metrics. Overall, the study data has demonstrated the effectiveness of the UCL Women in Surgery conference in empowering students pursuing surgical careers. Specialised conferences offer safe spaces for networking, mentorship, and field insights, while also mitigating financial barriers through low registration costs. Representation matters, and supporting aspiring surgeons by addressing barriers of entry for women is crucial.

Discourses of Hate

Since the COVID-19 pandemic, the global North has seen a drastic increase in usage of platform apps’ services. Platforms such as Uber, Lyft, DoorDash, and Deliveroo have become staples that connect consumers directly to workers on standby, ready to be activated at a moment’s notice to rideshare or deliver food orders. These companies offer low barriers of entry and flexible work hours, which is the ideal situation for many migrants looking for work. The scope of this research aims to build an understanding of the intersection between the rise of the far-right and the anti-immigration rhetoric in Canada and the EU that influences the hate faced by racialized migrants working highly visible gig jobs in the platform economy. By examining academic articles, news reports, and social media communications of far-right groups a major theme is apparent. The online rhetoric of the far-right can be categorized through its usage of fear and hate against racialized migrants. Migrants have been depicted as sexual threats to women, economic threats to workers, and an overall threat to the white population through demographic replacement. This conspiracy theory, known as the ‘Great Replacement’, found its way into the discursive attempts of far-right groups and political parties (ex. Chega - Portugal; VOX - Spain) to promote anti-immigration and violence against migrants. The threat that this rhetoric poses to racialized migrant workers has yet to be fully explored, and despite passing mention in a few academic articles, the violence faced by workers in the platform economy is not common in the literature, even more so in regards to its intersection with race based hate. This gap brings further questions concerning alliances among workers, advocacy groups, and trade unions based along the lines of ethnic, racial, and gendered differences to combat the growth of support for the far-right. With reasonable speculation, this research contends that far-right rhetoric and violence will continue to be targeted at racialized migrants in visible spaces and jobs, such as those in the gig economy which requires further labour solidarity and activism to aid migrants in vulnerable situations.

BARRIERS TO MARKET ENTRY AND STRATEGIES FOR SUCCESS: A STUDY ON SMALL AND MEDIUM ENTERPRISES (SMES) IN GHANA AND TANZANIA

Small and Medium Enterprises (SMEs) play a pivotal role in the economic development of emerging economies, yet they face substantial barriers to market entry that can impede their growth and sustainability. This study aims to analyze the major barriers to market entry encountered by SMEs in Ghana and Tanzania and explore the strategic approaches adopted to overcome these challenges. Utilizing a comprehensive literature review, this research synthesizes existing knowledge on entry barriers such as regulatory constraints, access to finance, market competition, and infrastructure deficits. The findings indicate that while both countries face similar obstacles, the intensity and impact of these barriers vary due to distinct economic and policy environments. Moreover, the study identifies successful strategies, including innovation, networking, and capacity building, that SMEs employ to navigate these challenges. By highlighting these barriers and strategies, this study contributes to a deeper understanding of the SME landscape in Ghana and Tanzania, offering insights for policymakers and practitioners to foster a more supportive business environment. The research emphasizes the need for targeted policy interventions to reduce entry barriers and enhance the competitive capabilities of SMEs. Future research should further investigate the dynamic interactions between these barriers and strategies across different sectors.

DIB‐BOT: An Open‐Source Hardware Approach for Plate‐Integrated Droplet Interface Bilayer Deposition

AbstractDroplet interface bilayers (DIBs) offer a controlled lipid environment for studying membrane‐bound processes, with applications in artificial cells, biosensing, and biophysics. Current DIB fabrication faces challenges due to time‐consuming processes and specialized equipment, limiting scale‐up and hindering statistical significance in single‐molecule assays. This research introduces “DIB‐BOT,” an open‐source solution combining a nanoinjector and a 3D printer. DIB‐BOT enables rapid, reproducible DIB fabrication, overcoming manual limitations. Using off‐the‐shelf components, DIB‐BOT ensures high spatial reproducibility, minimal user input, and scalable experiments. The system's utility is demonstrated through pairwise droplet assembly and a fluorescence plate‐reader assay. Compared to manual fabrication, DIB‐BOT shows a 10‐fold reduction in droplet volume error, a threefold reduction in positional error, and 100% droplet yield. This method lowers entry barriers to DIB research, expanding its applications and enhancing data quality.