Journal of Applied Business and Economics
The Journal of Applied Business and Economics (JABE) is dedicated to the advancement and dissemination of business and economic knowledge by publishing, through a blind, refereed process, ongoing results of research in accordance with international scientific or scholarly standards. Articles are written by business leaders, policy analysts and active researchers for an audience of specialists, practitioners and students. Articles of regional interest are welcome, especially those dealing with lessons that may be applied in other regions around the world. This would include, but not limited to areas of marketing, management, finance, accounting, management information systems, human resource management, organizational theory and behavior, operations management, economics and econometrics, or any of these disciplines in an international context. Focus of the articles should be on applications and implications of business, management and economics. Theoretical articles are welcome as long as their focus is in keeping with JABE’s applied nature.
Exxon Mobil Acquisition of Pioneer Natural Resources: A Test of Market Efficiency
On October 23, 2023, ExxonMobil announced a record-setting $59.9 billion all-stock acquisition of Pioneer Natural Resources, marking the largest energy sector M&A deal of the 21st century. This research employs event study methodology to test the semi-strong form of the EMH, which posits that markets rapidly absorb information, preventing significant stock price gains from new data. The study analyzes the impact of this merger on the stock prices of 30 NYSE-traded energy companies. By examining historical stock and S&P 500 index data, the research calculates holding period returns and average excess returns. Results reveal statistically significant positive impacts on stock prices and an overreaction approximately 30 days prior to the announcement, suggesting anticipatory market behavior. Following the announcement, stock prices declined towards equilibrium, aligning with semi-strong EMH principles. The findings support the semi-strong EMH, indicating potential trading opportunities up to 30 days before the announcement, consistent with behavioral finance literature. This case study offers valuable insights into M&A strategies within the energy sector and underscores the influence of external factors, regulatory changes, and industry knowledge on market responses.
Copyright (c) 2025 Journal of Applied Business and Economics
Integrating Cognitive, Emotional, and Informational Predictors of Pro-Environmental Behavior
This study aims to identify the factors that determine pro-environmental behavior. The study's sample consisted of 392 volunteer participants. A structural equation model was employed to examine the predictors of pro-environmental behavior. The determinants that we investigated are internet use, environmental knowledge, perceived environmental pollution threats, and environmental sensitivity. The fundamental findings of the current study indicate that environmental sensitivity is the most significant predictor of pro-environmental behavior. Furthermore, the study found that environmental sensitivity plays a significant mediator role not only between perceived environmental pollution threats and pro-environmental behavior but also between environmental knowledge and, pro-environmental behavior.
perceived environmental pollution threat
Human Capital: Recognition and Reporting
This discussion provides the definition, background, types, and categories of the business entity’s human capital workforce. Investors, business regulators and other stakeholders believe human capital has value that should be measured and disclosed on the entity’s financial statements. Various means to determine human capital value are identified and discussed. together with available disclosure guidelines. Support for reporting human capital values on the entity’s financial statement is presented together with information about why human capital should not be reported. Investors, stakeholders, and other financial statement users’ perspective regarding the availability of human capital value information are presented with the reporting framework.
Optimizing Veterinary Practice Economics: The Impact of Mid-Level Practitioners on Revenue, Profitability, and Workforce Efficiency
This study examines the economic effects of integrating Veterinary Professional Associates (VPAs), a mid-level practitioner role, into companion animal veterinary practices. In the context of a veterinarian shortage, we investigate how VPAs can boost efficiency, productivity, and financial performance. Using a mixed-methods approach, combining over 40 interviews with a partial budget model, we estimated the impact of adding one full-time VPA to a 3.5-veterinarian practice. Our model projects an annual revenue increase of $566,500 and a net profit increase of $177,850. These gains result from optimizing labor by shifting routine tasks to VPAs and allowing veterinarians to focus on higher-value activities. The study provides empirical evidence for the economic benefits of introducing mid-level practitioners in veterinary healthcare, offering insights into workforce optimization in labor-constrained markets.
A New Algorithm for the Weighted Tardiness Problem
We study the single machine weighted tardiness problem. In view of its NP-hard nature, we explore mathematical properties and dominance conditions to develop an algorithm that is powerful yet extremely simple to implement. Our proposed algorithm is then compared with some well-known heuristics that are currently available in machine scheduling literature. These computational results indicate that our proposed algorithm not only does well but also enables manual solutions for small problem sets due to its simplicity. We believe that future studies with an emphasis on exploring more properties and dominance conditions will result in optimal solutions even for large problem sets.
Valuing Ecosystem Services in the Ecuadorian Amazon: Strategic Applications of ESVD-Based Benefit Transfer for Conservation Finance
This paper demonstrates how ecosystem service valuation can inform conservation finance strategies using the Benefit Transfer Method (BTM) and internationally recognized valuation databases. We apply the Ecosystem Services Valuation Database (ESVD) to estimate the economic value of services provided by a 60-hectare property in the Ecuadorian Amazon. Using BTM, we compare Net Present Value outcomes across three scenarios: Carbon Sequestration Only, Extractive Use, and Full Ecosystem Services. Results show that the full valuation scenario—i.e. the “True Economic Value” (TEV)—far exceeds the outcomes in both the carbon-only and extractive-use cases. By year 100, this value is 4.8 times greater than extractive use and 3.1 times greater than carbon-only, underscoring the long-term importance of intact ecosystems. We then examine financing pathways, including payments for ecosystem services (PES), biodiversity credits, conservation easements, and REDD+, and propose investment structuring options informed by ESVD-derived valuation. Drawing on recent developments, we argue for diversified, multi-service approaches that more fully capture the ecological and economic value of tropical forests.
Introducing Cultural Entropy as a Framework for Understanding Cultural Tourism
This paper explores cultural entropy as a novel framework for understanding cultural tourism. It examines how increasing cultural complexity impacts authenticity, sustainability, and accessibility, highlighting strategies to manage uncertainty in cultural interactions. Using a simple model that relates a tourist's utility to their capacity for cultural entropy and the carry cost in entropy of multiple cultural competencies, an optimal number of cultural alternatives is deduced based on their relative preference between the number of alternatives and cognitive space to savor them. Future research into managing entropy as it relates to tourist impact on cultural homogenization, heritage conservation and visitor engagement are suggested.
The Effect of Political Corruption on IPO Initial Return: A Long-Term Country Analysis
We investigate the effect of political corruption on IPO (Initial Public Offering) initial return using a long-term country level data. Using country-level variables spanning 55 countries over a period of more than 10 years, we find a positive relationship between the average political corruption index and the equally weighted average IPO initial return. Country characteristic variables, such as country size, GDP, or the number of IPO firms within each country, do not have a significant effect on the IPO initial return. The result implies political corruption is an important factor affecting IPO initial return.
The Impacts of IT and EC Investments and Time Trends of the Speeds of Adjusting the Actual Toward the Maximum Pay upon CEO Compensation: An Extension
We analyze the impacts of information technology (IT) and e-commerce (EC) investments and time trends of the speeds of adjusting the observed (actual) toward the desired (maximum) pay upon chief executive officer (CEO) compensation in US firms, based on the adjustment model and its associated adjustment valuation (AV) approach, under the assumption of stochastic and dynamic adjustment speed (AS); and, then, we compare the new results to the findings of Lin and Chen (2024) based on the assumption of dynamic and variable AS. A comparative analysis strongly suggests that the new results are more realistic in a world full of uncertainty (Lin et al., 2019, pp. 769 and 777).
stochastic (random) and dynamic adjustment speed (AS)
complementarity (COM) and substitutability (SUB)
The Role of Fairness in Retaining Open Source Software Contributors: An Organizational Justice Framework for Platform Engagement
By facilitating open source software (OSS) development online software platforms are constantly contributing to the tremendous growth of open source software. The main purpose of this study is to explore the relationship between volunteer OSS developers and OSS platforms. To achieve the goal, this study proposes a theory that perception of justice about the OSS platform defines the ongoing relationship between OSS platform and OSS developers. Drawing on social exchange theory, the study examines how perceptions of justice in rewarding contributors impact information systems and technology professionals’ engagement with an OSS platform and their intention to contribute to future projects hosted by the OSS platform. The findings reveal that various dimensions of justice significantly affect both engagement and sustained participation intentions among information systems and technology professionals. The research advances open source literature by exploring the relationship between information systems and technology professionals contributing to open source projects and platform organizations, offering valuable insights for platforms seeking to foster long-term, voluntary engagement and enhance their standing within the open-source community.
The Inflation Reduction Act and Its Impact on Fuel Cell Companies: A Financial and Market Analysis
The Inflation Reduction Act (IRA), enacted in August 2022, aimed to accelerate the adoption of clean energy through substantial tax credits and incentives for hydrogen production and fuel cell technologies. This paper evaluates the financial performance and stock price trends of three leading U.S. fuel cell firms, Plug Power Inc., Bloom Energy Corp., and FuelCell Energy Inc., to assess whether IRA incentives improved stability and investor sentiment. Despite the Section 45V Clean Hydrogen Production Tax Credit and extended Investment Tax Credit (ITC), long-term profitability remains out of reach. Plug Power’s revenue declined 29.5% from 2023 to 2024, while FuelCell Energy’s net losses widened by 45%. Bloom Energy fared better with tighter cost controls and lower debt, yet remains unprofitable. Stock analysis shows early optimism gave way to skepticism as losses mounted: Plug Power’s share price collapsed from $30 to below $3, FuelCell Energy followed suit, and Bloom Energy’s decline was less severe. The findings suggest IRA incentives alone cannot secure industry success; operational discipline, efficient cost structures, and revenue growth remain essential for sustaining investor confidence.
The Cost of Complying With U.S. GAAP and Cross-Listed Firms’ Valuations
The study examines the capital market consequences of foreign firms’ cost of complying with U.S. GAAP. It builds upon a prior research that explores the effect of foreign firms’ U.S. GAAP compliance cost on their cross-listing decisions and listing choices (Lin 2011). Two cost constructs established at the firm level, reconciliation and disclosure, are adopted as proxy for firms’ compliance cost. The valuation analyses confirm the existence of cross-listing and exchange-listing premium. Although individual firms’ reconciliation costs play a little role in valuation, disclosure costs are found to negatively affect the value of cross-listed firms, i.e., firms with less disclosure of accounting information than what U.S. rules require, thus incurring higher disclosure costs, are valued less by the market. This result holds even after the strength of home country disclosure regime is considered. This study extends prior research by investigating the role of firm-specific compliance costs on valuation and provides new evidence on the source of the cross-listing premium.
Approaching Human-Level Data Coding? A Systematic Comparison of OpenAI, DeepSeek, and Human Coders in Qualitative Analysis of Customer Reviews
The rapid growth of online reviews presents both opportunities and challenges for qualitative research. Human coding ensures contextual accuracy but is difficult to scale. This study compares human coding with AI-assisted coding using OpenAI GPT-4o and DeepSeek r1 on customer reviews of a complex DIY product. Results show both platforms capture underlying relationships, with OpenAI aligning more closely with human coding and DeepSeek demonstrating stronger internal consistency. Systematic AI errors mainly take the form of conservative Type I errors. Findings suggest AI can complement, rather than replace, human coders to enhance scalability and efficiency.
Influence of Financial Flexibility on Performance of State-Owned Sugar Manufacturing Corporation Projects in Western Kenya
This study examined the influence of financial flexibility on performance of State sugar manufacturing corporations in Kenya. The study was guided by Modigliani and Miller’s capital structure model mainly (trade-off, pecking order and agency cost) theories, and was based on pragmatic paradigm which provides for the use of both qualitative and quantitative research methodologies. It targeted a population of 1,145 people, drawn from employees of State sugar corporations, and used a sample size of 291, obtained from Krejcie and Morgan's (1970) Table. A structured questionnaire and interview guide were used to collect data. SPSS version 25 was used to analyse data and Hypothesis was tested at a=0.05 significance level. Pearson’s correlation and linear regression analysis showed a positive correlation between the variables (p = 0.000 < 0.05), implying that financial flexibility significantly influences the performance of State sugar firms. It was recommended that, to enhance financial flexibility in State sugar corporations, the Government should focus on strategies that help reduce costs, improve revenue generation, and strengthen financial management practices.
performance of state-owned sugar manufacturing corporation projects
The Impact of IRC § 199A on the Value of Non-Publicly Traded Business Organizations
The objective of this paper is to assess the influence of tax reductions from the Tax Cuts and Jobs Act (“TCJA”), on the firm value of non-publicly traded business organizations. The TCJA provided a reduction in the graduated corporate tax from a top rate of 35% to a flat 21%, while simultaneously providing up to a 20% deduction of taxable income produced by passthrough entities under Internal Revenue Code (“IRC”) § 199A. While the overall value of non-publicly traded businesses increased after the TCJA, we find somewhat mixed results.
Flows Without Faces: Hidden Logistics in Non-Places
Behind the apparent neutrality of non-places lies a highly sophisticated logistical architecture that remains largely overlooked in academic research. Drawing on sociology, anthropology, and logistics management, the article demonstrates how material, human, and informational flows are tightly orchestrated to generate both fluidity and anonymity in international airports, mega-malls, and other transit environments. Two empirical illustrations highlight the underlying engineering that sustains performance while shaping user experience. A four-dimensional model—flow centrality, logistical coordination, adaptability, and experience construction—provides scholars and practitioners with a transferable framework for analyzing diverse non-places. The interdisciplinary perspective advanced here reframes non-places not as passive byproducts of hypermodernity but as intricate circulation systems in which the control of flows emerges as a critical driver of performance.
Online Brand Communities as A Services Marketing Channel: An Exploratory Study of Apple Support Community Using a Machine Learning Approach
Online brand communities are a vital services marketing channel and relationship marketing tool. Community members share a common interest and actively engage in community activities, such as content engagement, product, experiences and ideas sharing. These online brand communities offer a range of benefits, including enhanced customer service, incentives for active members, and strengthened brand loyalty. We particularly focus on customer service aspect of online brand communities and investigate how membership types and product categories affect the resolution rate of consumer problems. Using a machine learning approach, we explore dynamic interactions among members within the Apple Support Community over a time span of one year from 2023 to 2024. We investigate the contribution from varying membership types, examine variation in consumer experiences across different product categories and discuss the implications for marketers of consumer service strategies.
The Effects of Independent Non-Executive Directors (INED) on Company Performance — A Comparison of H-Shares and Red Chips Companies
This study will examine the influence of and relationship between independent non-executive directors (INEDs) and the performance of non-state-owned enterprises (NSOEs) and state-owned enterprises (SOEs) businesses listed on the Hong Kong Stock Exchange (SEHK). It is well known and reported that the number of Chinese companies coming to Hong Kong for listing on the SEHK has increased since the first listing of H-share company Tsingtao Brewery Co Ltd (00168.HK) in 1993. As the market capitalisation and influence in Hong Kong of these companies has increased in the last 20 years, the effects of their performance have received more attention. It is important to examine whether an increase in the number of independent non-executive directors (INEDs) will influence the behavior of major shareholders and the performance of state-owned enterprises (SOEs). This study aims to assist policymakers and regulators in assessing the need for further revisions to the current INED policy. Additionally, the findings may be applicable to other emerging markets and regions around the world that feature SOEs.
The Impact of Major Global Disruptions on Profitability and Revenue Expansion Among Leading Corporations
This study examines the performance of select industries within the Fortune 500 that experienced increased demand during the COVID-19 pandemic, utilizing data from the EDGAR database and SEC filings. Findings indicate that industries prioritizing digital transformation through technological innovation, operational agility, and strategic adaptation were better equipped to navigate disruptions, sustain growth, and achieve resilience. The results underscore the critical role of integrating digital strategies into core business models, not only as a response to immediate crises but also as a sustainable foundation for long-term competitiveness in an increasingly digital economy.
Moderating Role of National CSR Ratings: Empirical Evidence on the Relationship Between CSR Disclosure and Firm Risk
The growing importance of CSR has fueled extensive research on its link to firm risk, yet little attention has been given to how home-country CSR ratings shape this relationship, particularly for foreign firms listed on U.S. exchanges. This study examines the moderating effect of national CSR ratings in the relationship between firm CSR disclosure and risk. Using 23,579 firm-year observations from 2006 to 2018, we find that investors will evaluate socially responsible firms from countries with low CSR ratings more favorably. This study enriches our understanding of the CSR-firm risk relationship, providing important implications for investors and corporate managers.
The Long-Term Effect of the First Course in Accounting on Graduation Rates
We study the impact of business major student performance in the Introductory Financial Accounting (IFA) class on their graduation rates. The results show that the student GPA in the first semester, the cumulative final exam score in the IFA class and the term in which the class is taken significantly impact graduation rates. Though past studies have indicated that first term GPA is a good predictor of graduation rates, we find that performance in the IFA class has additional predictive value of graduation rates. Our results remain robust after controlling race, gender, major and embedded tutors.
State of Persistence: Unemployment Hysteresis in Ten U.S. States: Bootstrap Nonlinear Unit Root Tests in Regional Labor Markets
This study examines the extent to which the hypothesis of hysteresis holds across different U.S. states by analyzing unemployment data. Implementing advanced nonlinear unit root tests, in combination with bootstrap techniques, the analysis investigates whether temporary shocks—such as recessions or the COVID-19 pandemic—can result in permanent changes in unemployment and other labor market outcomes. Our results reveal mixed outcomes consistent with recent literature on the hysteresis hypothesis in the U.S. The LNV and Sollis tests generally support the natural rate hypothesis. In contrast, the KSS and Kruse tests provide evidence of permanent effects in several states.
In modern times, the issue of media trust and its impact on people’s media use has taken on increased importance. The degree to which people trust the news media and how much it relates to their use of different types of media is not apparent, particularly among members of Gen Z. This research examines news media trust and its influence on media use on Gen Z. Specifically, this research examines media and information consumption among Gen Z for gathering political news and their level of trust among various digital channels. This was accomplished via an online survey of Gen Z college-aged students (N=99) enrolled at a private university in the northeastern United States. The longitudinal study was administered during two academic semesters, one during fall 2023 and the other in fall 2024 during the presidential election. The empirical findings supported the hypothesis that there is a significant difference between the level of media trust and political ideology. However, there was no significant difference in the average media trust value between Republicans and Democrats The study also found that as a person’s media trust increased so did their weekly usage of various social media networks. Specifically, the findings also indicated that Facebook, Twitter, Pinterest, Snapchat, and TikTok usage frequency had a positive correlation with media trust
Cluster Analysis and Population Density Theories: An Exploratory Study of Indigenous Female Entrepreneurship
The last twenty years have seen significant contributions in the literature on women entrepreneurship. This has been augmented with studies that are engaged in comparative analyses across gender, borders, and industries. While these studies provide insights into the status of women entrepreneurs, what is often missing and what has not emerged are niche studies that look at women entrepreneurs from a particular group, a particular ethnicity, a particular genre - going deep in any of these directions, with rigorous statistical analyses while focusing on and deriving conclusions from said in-depth focus. In essence, studies asking questions that call for comprehensive, multiple layer analyses with statistically backed answers that produce substantial conclusions in terms of their contribution to the forum of women entrepreneurs in general and specific niche groups of women entrepreneurs in particular. With this in mind, we turn our attention to the world of Native American entrepreneurs and specifically Native American female-owned enterprises and examine these questions as we consider the context on female entrepreneurship from the setting of the Indigenous community.
United States vs. Dane Watson: A Teaching Case
This teaching case can be used in various classes: accounting, tax, business law, or ethics. It can be used at either the undergraduate level or the graduate level, perhaps with different learning objectives. It is derived from a real criminal court case where the defendants paid workers using gold and silver coins with a fair value above their face value. For tax purposes, the defendants were using the face value of the coins as the amount of compensation even though the coins were immediately traded for cash. Also, the workers were required to sign independent contractor agreements, so no income, Social Security, or Medicare taxes were withheld.
Leveraging Data-Driven Decisions: A Predictive Model to Enhance Student Success in Higher Education
Higher education institutions often face challenges in achieving key success metrics, such as on-time graduation rates, particularly when supporting students with diverse backgrounds, needs, and barriers. This study examines a detailed dataset containing student demographics and academic records from College of Business at a large public university spanning ten years. Our results highlight significant achievement gaps based on factors such as gender, age, race, family income, and parents’ education levels. These gaps persist even among students with similar academic histories. We develop prediction models that enable institutions to identify high-risk students early, facilitating timely intervention and providing a framework for comparing institutional efforts to improve student success. This study highlights how data-driven approaches can enhance institutional management by enabling proactive identification of challenges, optimizing resource allocation, and supporting strategies that improve student outcomes.
Teaching Economics With Case-Based Learning and Problem-Based Learning
We explore the impact of two active learning methods – case-based learning (CBL) and problem-based learning (PBL) – and summarize our experiences using these methods in an applied managerial economics course. Our empirical analysis evaluates cognitive, affective, and behavioral dimensions of learning. In the cognitive category, analysis of student exam performance on topics covered by either CBL or PBL demonstrates improvements compared to topics covered only in traditional lectures. In the affective category, which focuses on student satisfaction, and the behavioral category, which concerns student skills, survey evidence demonstrates a positive impact of active learning.
Simple Rules for Determining How States Can Save for a Rainy Day
Various articles have been written concerning the level of savings states should accumulate to weather an economic downturn, and since states have differing business cycle characteristics a one-size-fits-all approach does not seem to make much sense. Once the level of accumulated savings is determined, the next question concerns the savings rate that will enable the state to achieve its desired accumulated savings. This article builds on the work of Wagner and Elder (2007) and presents a simplified approach to determine the appropriate savings rate based on each state’s risk preferences.
Bridging Climate Awareness and Green Actions: The Role of Employee Psychological States in Fostering Pro-Environmental Behaviors
The study examines how climate change awareness impacts pro-environmental work behavior in organizations through three proactive psychological states. The study results suggest that climate change awareness increases pro-environmental work behaviors through three psychological states (environmental self-efficacy, environmental accountability, and environmental passion). In addition, green pay and rewards enhance employees’ psychological states toward pro-environmental work behavior. This paper revealed how climate change awareness influences pro-environmental work behavior by affecting employees’ proactive psychosocial states. In addition, the multilevel study explains how individual and organizational variables interact to influence personal initiatives toward environmentally friendly work behaviors.
Artificial Intelligence Applications and the Impact on Banking Operations
Artificial Intelligence (AI) has emerged as a powerful force in the banking and financial sectors, reshaping traditional processes and unlocking new opportunities for efficiency and inclusion. However, its adoption is not without challenges, particularly concerning ethical risks, regulatory compliance, and operational limitations. The purpose of this paper is to explore AI in banking applications and its impact on banking operations. First, a literature review examines the multifaceted role of AI in banking, exploring its applications, the ethical risks it poses, and the strategies required to ensure equitable and responsible deployment. Second, we study 39 banks and their AI applications. Third, based on our research, we develop and distribute opinion surveys to students. The survey results show that students believe most jobs eliminated due to AI will be in the lower levels of financial organizations, particularly bank tellers. While AI offers substantial benefits, its success relies on robust governance frameworks, transparent systems, and ongoing efforts to mitigate bias.