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The purpose of this article is to determine the regional economic factors and bank characteristics that significantly contribute to changes in bank liquidity. We also seek to identify regions that may be most susceptible to liquidity tightening.

For this article we use data on deposits from commercial banks, Federal Reserve survey data and indicators of regional and agricultural economic conditions. We specify a panel regression with fixed effects to model how liquidity at agricultural banks has changed and to identify the most significant drivers.

Our results suggest that small banks and banks with branch networks located in areas more concentrated in agricultural production bear the greatest risk of reduced liquidity.

Prior to the pandemic and more recently, lower deposit growth, combined with strong demand for agricultural loans, has led to reductions in liquidity at agricultural banks. Lower liquidity could reduce credit availability for farm borrowers and increase risks for banks that must rely on alternative sources of funding to meet loan demand.

Previous research has shown that exogenous shocks from other economic sectors, such as energy, can significantly affect bank liquidity, but research is limited on how agricultural bank liquidity is affected by downturns in the agricultural economy and other regional economic factors. Another contribution is this paper’s analysis of regional disparities in bank liquidity.

Despite well‐publicised successes and failures, the evidence base for the impact of a workplace on an organisation’s business performance remains small and confused. Theoretical perspectives are, with few exceptions, limited to matching physical environment to task. The concept from complexity theory of “edge of chaos” – a critical density of connectivity (Kauffman’s K) between the agents in a network in which adaptability is maximised – may explain how workplaces enable, or retard innovation. Formal rectilinear open plan offices are conceived as freezing occupants in a state of connectivity as low as traditional cellular designs. Offices without minimal acoustic or visual privacy (high K) may create chaotic stress and reversion as individuals seek to recreate safety. In between are offices known to have enhanced informal conversation between their occupants and resultant innovation.

The aim of this paper is to demonstrate the role the behavioural environment plays in office productivity.

The paper reviews the literature from the occupier perspective. This approach enables a greater appreciation of the social context of offices. The review establishes the need to link work process with the office environment. It identifies the need to understand how occupiers make sense of space through personalisation. The balance between the positive interactions in the office and negative distractions are explored.

The review of the literature reveals that by adopting the occupier perspective potential tensions can be identified between individual, private and team‐based collaborative work areas. These tensions can have an impact on the office occupier's productivity.

This paper establishes that to ensure office environments are designed for optimum productivity; consideration needs to be given to the role of the behavioural environment. Office environments need to be designed to enhance collaboration, whilst at the same time ensure individual private work is not compromised.

Fintech businesses have the tendency to revolutionize the entire world. Especially, the tasks associated with banking needs, and therefore, there is a significant scope for Fintech in the banking industry. Although when the country’s major population is unbanked and most of the population is also financially excluded, then the scope of Fintech gets exaggerated for microfinance institutions (MFIs), and therefore, the significance of Fintech for MFIs is much higher than the commercial and Islamic banks. Hence, this chapter has been written purposively to illuminate the impact, role, significance and implications of Fintech for MFIs in Pakistan in order to boost the knowledge and understanding of diverse stakeholders. The specialty of this chapter is that it is written specifically with reference to Pakistan as there is least research work with respect to the application of Fintech in MFIs. Similarly, the chapter also contains the anatomy of the value chain activities of MFIs and their linkage with the role of Fintech applications in boosting the performance of MFIs. Last, but not the least, the chapter also has a detailed discussion on factors that are required to boost the usage of Fintech in the MFI sector. Therefore, this chapter is pervasive for academicians, researchers, entrepreneurs, intrapreneurs and students for grasping, understanding and applying recent knowledge towards the betterment of academic and pragmatic activities.

The COVID-19 pandemic created a broad array of challenges for hospitals. These challenges included restrictions on admissions and procedures, patient surges, rising costs of labor and supplies, and a disparate impact on already disadvantaged populations. Many of these intersecting challenges put pressure on hospitals' finances. There was concern that financial pressure would be particularly acute for hospitals serving vulnerable populations, including safety-net (SN) hospitals and critical access hospitals (CAHs). Using data from hospitals in Washington State, we examined changes in operating margins for SN hospitals, CAHs, and other acute care hospitals in 2020 and 2021. We found that the operating margins for all three categories of hospitals fell from 2019 to 2020, with SNs and CAHs sustaining the largest declines. During 2021, operating margins improved for all three hospital categories but SN operating margins still remained negative. Both changes in revenue and changes in expenses contributed to observed changes in operating margins. Our study is one of the first to describe how the financial effects of COVID-19 differed for SNs, CAHs, and other acute care hospitals over the first two years of the pandemic. Our results highlight the continuing financial vulnerability of SNs and demonstrate how the factors that contribute to profitability can shift over time.

Entrepreneurial ecosystems have quickly become one of the most popular topics in entrepreneurship research. Ecosystems are the characteristics and factors of a place that support high-growth entrepreneurship. This provides the ability for the field to provide important policy insights about how to aid the development of high growth, innovative ventures, as well as generate new insights into the relationship between the entrepreneurship phenomenon and the contexts it takes place within. However, work in the field remains undertheorized, with a little understanding of how the entrepreneur benefits from being in a strong ecosystem. This chapter argues that it is helpful to return to Ed Malecki’s work in a previous volume of this series, which explored the importance of networks. His work has contributed to a very broad stream of work on entrepreneurial environment. Using this as a starting point, this chapter distinguishes between “top-down” approaches to study ecosystems, which focus on the actors and factors that make up an ecosystem, and a “bottom-up” approach, which instead examines the ways in which entrepreneurs use their ecosystem to get the resources, knowledge, and support they need. The chapter concludes by suggesting how a research agenda for a bottom-up study of ecosystems can be informed by Malecki’s work.

The importance of key account management (KAM) as a management technique in business-to-business markets has grown in recent years. The success of KAM programmes is highly dependent on the efforts of individual employees, specifically key account managers. Research on KAM at an individual level is important but lacking in the academic domain. This study aims to fill this gap by developing and evaluating a model of key account manager personality traits and how they impact the adoption of artificial intelligence (AI) technologies. The study also depicts the effect of the adoption of AI technologies on competitive advantage and firm performance.

The study examines how the adoption of AI technologies impacts firms’ competitive advantage and performance. The study used competitive advantage as a mediator and organisational culture as a moderator. A mixed-method analysis was used to conduct the study. In the first phase, an exploratory study was conducted using interviews with 26 key account managers from the automobile industry and thematic analysis to establish 9 constructs. In the second phase, which is a confirmatory study, 496 respondents finally responded to the questionnaire.

All constructs are used for confirmatory analysis and validate the data. Our research shows that key account managers’ adoption of AI technologies is influenced significantly by personality traits. Extraversion, agreeableness, conscientiousness, neuroticism and openness have substantial links to adopting AI technologies, which impacts firms’ competitive advantage and performance. Organisational culture significantly moderates the association between agreeableness and the adoption of AI technologies.

The findings of this research allow organisations to optimise team composition, customise training programs based on individual traits and incorporate personality assessments into recruitment processes for streamlined technology adoption and improved competitiveness. Overall, these actions aim to enhance AI integration, driving competitive advantage and client satisfaction.

This study stands out as one of the limited inquiries examining how the Big-five personality traits of key account managers influence the integration of AI technologies and its resulting impact on company performance. Therefore, this research makes notable contributions to the realms of organisational psychology and technology adoption studies.

Based on previous literature on big data analytics (BDA) and supply chain (SC) management, the purpose of this paper is to address the factors determining firms’ intention to adopt BDA in their daily operations. Specifically, this study classifies potential factors into four categories: technological, organizational, environmental factors, and SC characteristics.

Drawing on the innovation diffusion theory, a model consisted of direct technological and organizational factors as well as moderators was proposed. Subsequently, survey data was collected from 210 organizations. Then we used SPSS and SmartPLS to analyze the collected data.

The empirical results revealed that perceived benefits and top management support can significantly influence the adoption intention. And environmental factors, such as competitors’ adoption, government policy, and SC connectivity, can significantly moderate the direct relationships between driving factors and the adoption intention.

Given the fact that big data (BD) usage in logistics and SC management is still in the start-up stage, the interpretations toward BDA might vary from different perspectives, thus causing some ambiguity in understanding the meaning and potential BD has. In addition, we collected data through questionnaires completed by IT managers, whose viewpoint may not fully represent that of an organization.

This paper tests the organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.

This research helps top managers assess the benefits of BDA as well as how to adjust their business strategy along the changes of environment and SC maturity.

This paper contributes to the literature of organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.