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In the wake of rapid banking consolidations in the USA, concerns have arisen about the accessibility of capital and financial services for new businesses. With fewer and more centralized banking options, the likelihood of these entities securing financing may be compromised. This study aims to explore the repercussions of this consolidation on entrepreneurial activities in the U.S. Midwest.

To measure entrepreneurship, this study examines various business application metrics: total applications, high-propensity business applications (i.e. those with a high likelihood of evolving into businesses with payrolls), business applications from corporations (applications stemming from corporations or personal service entities) and applications with planned wages (those indicating a forthcoming payroll date). To assess the banking sector’s consolidation, this study used the deposit-based Herfindahl–Hirschman Index (HHI), a well-known measure of banking concentration.

This research underscores the detrimental impact of banking consolidation on various new business formations. To illustrate, a one standard deviation surge in the HHI, roughly 1253 points, correlates with a decline of approximately 16 total business applications, 7.3 high-propensity business applications, 3.72 applications originating from corporations and 3 applications indicating planned wages – all per 10,000 individuals. The findings indicate that reduced banking competition could slow down new business formations and negatively affect entrepreneurship.

This study examines various business formation statistics and use deposits at the institution level to determine banking concentration.

This paper aims to discuss the suitability of topic modeling as a review method, identifies and compares the machine learning (ML) research trends in five primary business organization verticals.

This study presents a review framework of published research about adopting ML techniques in a business organization context. It identifies research trends and issues using topic modeling through the Latent Dirichlet allocation technique in conjunction with other text analysis techniques in five primary business verticals – human resources (HR), marketing, operations, strategy and finance.

The results identify that the ML adoption is maximum in the marketing domain and minimum in the HR domain. The operations domain witnesses the application of ML to the maximum number of distinct research areas. The results also help to identify the potential areas of ML applications in future.

This paper contributes to the existing literature by finding trends of ML applications in the business domain through the review of published research. Although there is a growth of research publications in ML in the business domain, literature review papers are scarce. Therefore, the endeavor of this study is to do a thorough review of the current status of ML applications in business by analyzing research articles published in the past ten years in various journals.

This chapter considers how to ensure that both knowledge preservation and curation are well supported in the architecture and infrastructure of any organization. Support at the enterprise architecture is critical if the business goals of use, reuse, curation, and recuration in the business context are to be achieved. Enterprise architecture is explained – its vertical and horizontal approaches. Preservation is aligned with the information and data architecture. Curation is defined as a new element in the business architecture layer. The authors explain how this approach supports variations in practice across the organization.

The article aims to provide a bibliometric and content analysis of the business application of blockchain technology.

Bibliometric analysis and content analysis were undertaken to accomplish the stated objectives of the study.

The results revealed publication and country collaboration trends, declining, emerging, and niche research areas, the topmost influential articles, authors, and most relevant journals.

As researchers have been myopic towards some mainstream research agendas studying the specific contexts of blockchain applications, this research believes a holistic approach to understanding blockchain technology's versatility to disrupt different business processes across a myriad of industries is lacking. In addition, to strengthen the research's conclusions, a content analysis of the most significant articles is conducted as part of the study.

This article aims to review critical thinking (CT) as a future skill in business.

The study employed two research methods: science mapping analysis based on bibliometric keyword co-occurrence data and systematic literature review following PRISMA guidelines. The application of two distinctive research methods meant that we could obtain a broad picture thematic overview as well as a detailed, fine-grained insight into the content of CT business research.

Research in CT in business studies is dominated by themes related to education, university and learning that far outweigh CT business application, which focuses on three research axes. These are specific business functions (e.g. accounting, marketing, human resources and identifying business opportunities), certain skills used in business (e.g. decision-making and creativity) and other business-related topics (including ethics, stakeholder relations and individual employee performance).

The article identifies new research gaps related to the link between CT and business performance, a firm’s ability to innovate and company characteristics. Moreover, the article highlights that CT positively influences business decision-making under the influence of cognitive biases and heuristics.

The article provides the first literature review on CT in business research. It uses a novel method of science mapping analysis to show unbiased algorithmic-based insight into the structure of the research, followed by a systematic literature review.

This study aims to empirically examine the factors that affect mobile loyalty (m-loyalty) and its influence on customer reuse intention towards mobile instant messaging services. This study identified measurement items to assess the business users and individual users reuse intention towards mobile instant messaging services and test the relationship in the conceptual model. This study bridges a literature gap focusing on m-loyalty and its impact on customer reuse intention, which has not received attention previously.

To evaluate the influence of the factors, this study identified and extracted the items from past literature to develop the survey instrument. This study surveyed 600 respondents including business users and individual users from the Delhi-National Capital Region of India and applied the structural equation modelling to test the conceptual model.

The results revealed that satisfaction and m-loyalty have a direct effect on the business users and individual users’ reuse intention of mobile instant messaging services. This study found that satisfaction, usability, perceived value, commitment, trust and m-loyalty influence on business users reuse intention. This study indicate that enjoyment has an insignificant relationship on m-loyalty for business users followed by usability and enjoyment has an insignificant relationship on m-loyalty for individual users. Further, female gender does not moderate the relationship between satisfaction and business users reuse intention. The cognitive absorption and the unified theory of acceptance and use of technology (UTAUT) theories supported evaluating the association between the factors in the context of business and individual users reuse intention of mobile instant messaging service.

The empirical findings imply that all the factors except enjoyment have directly influenced the business users reuse intention of mobile instant messaging. The significant influence of usability factor on the business users reuse intention towards mobile instant messaging is the major variation between the validated models of business and individual samples. The results of influencing factors of m-loyalty and its impact on customer reuse intention are associated with cognitive absorption and the UTAUT theories.

Focus on these factors can be beneficial for the business users, managers, mobile instant messaging service providers and application developers to increase customer loyalty and reuse intention for the mobile instant messaging services. This research will facilitate mobile instant messaging service providers to keep their services market relevant and focus on user satisfaction in building applications for loyalty.

This research identified measurement items from earlier literature to identify, analyze and verify the relevance of these factors in m-loyalty and customer reuse intention of mobile instant messaging services and fill the gap in customer reuse intention of mobile instant messaging services literature.

The paper aims to present a framework for integrating the concepts of business continuity and business resilience with the aim of developing a concept of always-on business.

Literature review, conceptual and case-based.

A conceptual model for integrated “always-on business” solution based on continuous comouting technologies, business continuity, disaster recovery, IT/business resilience and several organational frameworks.

Presented framework can be used for integrating business continuity and business resilience in modern digital age; and transforming business systems into “always-on business”.

This chapter aims to highlight the existing applications and future prospects of Artificial Intelligence (AI) in the tourist business. In addition, this chapter investigates the obstacles in using AI in the Indian tourist industry.

To achieve the study's aims, both primary and secondary data are used. Using secondary sources, desk research was conducted to investigate the existing uses and future prospects of AI application in the global tourism industry. In addition, qualitative interviews with 25 executives in the Indian tourist business were undertaken to study the obstacles to using AI in the Indian tourism industry.

The research found that the applications of AI in the worldwide tourist business are extensive. Nonetheless, corporations are actively using AI-based technology to improve the customer experience via chatbots, intelligent forecasting and smart, tailored travel experiences. The qualitative interviews found that the implementation of AI technology in the Indian tourist industry is hindered by budgetary restrictions, knowledge constraints and barriers relating to human resources.

The use of AI in the tourism business may significantly improve the client experience. As a consequence, the use of AI-based chatbots and intelligent travel aides is growing exponentially. The research examined the many uses of AI in the worldwide tourist industry as well as the obstacles associated with the deployment of AI in the Indian tourism industry.

The current study gives a quantitative analysis DT literature over the past ten years in domain of management and business where the field has witnessed a proliferation in studies. The study's primary areas of concentration were analyzing historical trends and identifying prospective future research opportunities in the field. Due of the way, it approaches innovation and problem-solving, design thinking has garnered a lot of interest from both academics and practitioners. Promoters and detractors, however, tend to have quite different perspectives on the program's core qualities, practicality and results.

The study adopts a bibliometric approach to a systematic literature review, where the analyses and visualizations are carried out using R Studio (Biblioshiny package) and VosViewer software. The study was conducted on 518 documents extracted from the Scopus database. To identify past research trends in the field, performance analysis based on productivity and/or impact of the research constituents was carried out to understand the intellectual structure of the field.

The study's findings indicated that few areas have received the most attention, which are presented as seven themes. While the emerging themes in the field include areas such as service design, service innovation, customer experience, innovation management, project management and 21st-century skills.

The studies are going deeper by breaking down concepts or processes and analyzing one aspect at a time, codesign and prototyping are such subareas within the realm of service or new product design and development.

This study is the first of its kind where a literature review has been conducted covering design thinking in the area of business management and accounting.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.