Journal of Accounting and Finance

Production Costs Recognition: Time-Based Methodologies

Steven Goad, Mary Fischer — Fri, 15 Nov 2024 00:00:00 -0500

This analysis presents a review of time-based costing methodologies: Time-Driven Activity-Based Costing (TDABC), Duration-Based Costing (DBC) and Program Accounting Costing (PAC). Cost accounting systems are crucial for businesses to allocate costs to make informed business decisions. TDABC, DBC and PAC are approaches in this domain, offering unique advantages and applications. The concepts, methodologies, advantages, and limitations of each approach are explored to provide insights into their suitability for different industries and organizational contexts. The analysis finds comparing Time-Driven Activity-Based Costing, Duration Based Costing and Program Accounting Costing are analogous methodologies with different applications relating to timing cost recognition and are like comparing triples wearing the same but different colored outfits.

Financial Statement Forecasting and Financing

Tom Arnold, Kenneth P. Moon — Fri, 15 Nov 2024 00:00:00 -0500

Using a “plug” figure or “slack term” within a pro forma analysis is the standard method to allow a forecasted balance sheet to have assets equal to liabilities and equity. Seemingly, different types of plug values are demonstrated to be mathematically linked to each other. Further, by exploring cash as a plug figure, a solution emerges for a “target revenue growth rate” in which cash is not depleted. If a private equity venture can generate revenue growth above the target revenue growth rate, cash will accumulate and improve the return on the private equity investment.

The Value of Non-Value Activities

W. Terry Dancer, Harshita Chopra, Anh Duong — Tue, 19 Nov 2024 00:00:00 -0500

The essence of manufacturing is first an idea, then a facility, then the purchase of raw materials, then hiring of labor, then we turn on the electricity and transform raw material into our product. This essence gives a foundation we can build on. Many believe only value-added activities such as materials and labor add value to the product. However, others believe that activities such as inspections, machine setups, and even wait time adds value to the product. The premise of this paper is anything you are willing to pay for has value, even if it labeled a “so-called” non-value-added activity and buyers willingly pay for non-value added activities every time a product is purchased. The question becomes: “What is the value of Non-Value added activities?”

Islamic Banks’ Bootstrap Efficiency and Its Determinants: Cross Country Evidence from Nine South and Southeast Asian Countries

Abdus Samad — Sun, 29 Dec 2024 00:00:00 -0500

This paper employs bootstrap Data Envelopment Analysis (DEA) to first estimate the technical efficiencies under constant returns to scale (CRS) and variable returns to scale (VRS) for Islamic banks across nine South and Southeast Asian countries (Indonesia, Malaysia, Brunei, Singapore, Maldives, Thailand, Sri Lanka, Bangladesh, and Pakistan). The findings reveal that the average VRS technical efficiency for the region is 82.1%, which is higher than the CRS technical efficiency of 76.6%, indicating input wastage of 17.9% and 23.4%, respectively. A cross-country comparison shows that Malaysia's Islamic banks have the highest average CRS efficiency (80.1%) and VRS efficiency (87.2%) in the region, followed by Pakistan, Bangladesh, and Indonesia. In the second stage, using Simar and Wilson's (2007) truncated regression, the study identifies that bank capital risk (EQTA), bank credit risk (NPLL), and bank liquidity (CASTA) are significant internal factors negatively influencing both CRS and VRS technical efficiencies in loans and deposit production. Among external factors, the bank loan market structure (Herfindahl-Hirschman Index (HHI)), per capita GDP, and a country-specific dummy variable significantly and positively impact bank efficiencies. The significance of bank internal and country-specific factors has important policy implications for bank management.

The Accuracy of Multiples Used to Estimate the Market Value of Large U.S. Pharmaceutical Companies

Ginette McManus, Rajneesh Sharma — Sun, 29 Dec 2024 00:00:00 -0500

Many researchers and analysts have shown that expensing R&Ds can distort the profitability measures and market value estimates of R&D intensive firms and treat R&Ds as assets. This paper assesses the valuation accuracy of five goodwill, five enterprise and two price multipliers that can be used to estimate the market values of large U.S. pharmaceutical companies with significant R&D expenditures during the 2010-2022 period. Our results support that goodwill multipliers generally provide the smallest estimation errors of the market values of pharmaceutical firms with significant R&Ds and that gross profit is a superior measure of the profitability of these firms.

Hedging Risks of Demand and Lead Time Variabilities in Healthcare Inventory Management

Roger Lee Mendoza — Sun, 29 Dec 2024 00:00:00 -0500

This paper proceeds from the premise, derived from the literature, that uncertainty is predominantly a demand-side and/or lead time problem in healthcare inventory management. It conceptually explores how organizational exposure to the risks of uncertain demand and lead time may be hedged, especially considering that forecasting stock-outs and overstocks can be quite challenging in healthcare. We examine these challenges probabilistically. Theoretically, by inquiring into the underlying premises of aggregate demand, order quantity, and reorder point. And practically, regarding the implications of hedging inventory risks under conditions of uncertainty. Three measures that can efficiently hedge against demand and lead time variabilities under a continuous review inventory system are identified and analyzed: safety stock with service level, stock-out and overstock costing, and low-cost reorder point. Mathematical modeling, simulation, and optimization enhance integrated financial and operational problem-solving. With appropriate technology and software, demand forecasting and risk-hedging offer real-time visibility into stock levels. These should help healthcare organizations make critical, data-driven decisions and contain costly understocking and unnecessary overstocking when demand and lead time are stochastic and discreet.

Accountability and Governance in Kenya's Sustainable Development Goals Implementation: A Developing Country Perspective

Jesse Gitahi — Tue, 31 Dec 2024 00:00:00 -0500

This study analyzes how accountability mechanisms and governance structures impact the achievement of SDG targets, providing a comprehensive review of Kenya’s progress, a developing country facing unique governance challenges. Specifically, the paper aims to define key concepts of accountability and governance within the Kenyan context, assess the frameworks in place for ensuring transparency and resource management, and evaluate their alignment with international best practices. A review of relevant literature was conducted, analysis of available reports on Kenya’s SDG progress, and case studies that highlight successes and failures in accountability and governance. While Kenya has made significant strides in some areas, gaps in governance and accountability continue to limit the full realization of the SDGs. Case studies reveal how governance reforms and partnerships with international organizations have yielded positive outcomes in certain SDG initiatives, yet systemic challenges persist. The paper concludes by offering recommendations for enhancing governance and accountability frameworks in Kenya. These recommendations have broad implications for other developing countries facing similar challenges.

Risk-Adjusted Returns of Ethical Companies

Nell Gullett, Mahmoud Haddad, Laura Hatch — Tue, 31 Dec 2024 00:00:00 -0500

This study examines the investment performance of companies recognized for their socially responsible behavior, specifically focusing on the long-time honorees of Ethisphere's World’s Most Ethical Companies list. The analysis includes 28 publicly traded organizations from sectors such as Technology, Financials, and Consumer Goods, with stock returns and sector Net Asset Values (NAVs) used to assess risk-adjusted performance. Key metrics include the Sharpe Ratio, Jensen Alpha, and Treynor Ratio, all of which measure returns relative to risk. Results show that while more than half of the companies underperformed their respective sectors, the overall ethical portfolio generated positive risk-adjusted excess returns, primarily driven by strong performance from the technology sector. These findings suggest that ethical companies may provide valuable investment opportunities, particularly in sectors like technology and finance.

Innovative Insights: Impact of Crypto News on Corporate Earnings Through GenAI Models With Bert Framework

Karina Kasztelnik, Steven Campbell — Tue, 31 Dec 2024 00:00:00 -0500

This study represents a pioneering investigation into cryptocurrency news's repercussions on publicly traded companies' corporate earnings. Leveraging advanced Generative AI (GenAI) models and the BERT framework for sentiment analysis, we meticulously integrated comprehensive data from the Financial Modeling Prep API to employ a rigorous event study methodology alongside advanced machine learning algorithms. Noteworthy insights were derived from the BERT model, shedding light on the rationales behind abnormal returns and facilitating an in-depth analysis of material and immaterial impacts. The study’s findings underscore the significant impact of both positive and negative cryptocurrency news on cumulative abnormal returns (CAR), particularly within firms deeply entrenched in crypto activities. Notably, deliberate news, including official announcements, exerts a more pronounced influence than unintentional market reactions. This innovative approach furnishes actionable insights for financial services, investment management, and corporate communication, providing a framework for enhancing predictive models, investment decisions, and risk management strategies.

Impact of Auditors’ Industry Specialization and Longevity on Professional Skepticism

Robert Sollfrey, Medhanie Mekonnen, Wen-Wen Chien, Roger Mayer — Tue, 31 Dec 2024 00:00:00 -0500

As a result of financial scandals, such as GE Co. and AIG, professional skepticism received increased significance in the field of auditing. Grounded in Hurtt’ s professional skepticism framework, this quantitative correlational study aimed to examine the relationship between years of auditor experience, the extent of industry specialization of the auditor, and the variation in the level of professional skepticism. The study included data from 68 U.S. accountants and auditors. The results of the multiple regression model showed that at F(2, 65) = 4.414, p = 0.016, R2 = 0.12, auditor’s industry specialization was a significant factor, which is positively associated with professional skepticism. Auditor’s industry specialization was statistically significant (ß= .316, t = 2.704, p = .009), accounting for a higher contribution to the model. Auditor’s longevity in the field was not statistically significant, thus, did not explain any significant variance in the performance of professional skepticism. The results of this study extended research on professional skepticism attributes and expanded our understanding of predictive variables.