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Article
Publication date: 11 February 2025

Mark Kohlbeck and Lin Wang

The purpose of this study is to examine the effect of audit committee (AC) tenure on corporate governance, a topic that has been long debated. Social capital theory explains how…

41

Abstract

Purpose

The purpose of this study is to examine the effect of audit committee (AC) tenure on corporate governance, a topic that has been long debated. Social capital theory explains how directors’ effectiveness varies through tenure. Consistent with this theory, this paper argues that AC tenure has an inverted U-shaped relationship with AC governance.

Design/methodology/approach

This paper estimates a quadratic function that regresses constructs for AC governance on the average AC, the AC chair, and nonchair tenure, and their respective square terms. The constructs for AC governance include financial reporting quality measures and perceived auditor independence measures.

Findings

This paper finds that average AC, AC chair, and nonchair tenure have inverted U-shaped relationships with financial reporting quality, consistent with social capital theory. This paper also finds similar associations when examining perceived auditor independence. The results are generally consistent with AC directors accumulating knowledge and social capital, which improves AC governance to an optimal level, following which entrenchment and familiarity occur and AC governance declines.

Originality/value

To the best of the authors’ knowledge, this is the first study in AC governance literature to show a nonlinear relationship between AC tenure and AC governance. This paper extends Huang and Hilary (2018) by demonstrating that a nonlinear effect is also present in the AC, a key board committee responsible for monitoring financial reporting quality and appointing auditors and approving their services. This paper further documents that the AC subsumes the effect of the overall board in some areas of AC oversight, and reconciles the inconclusive findings of prior research by showing a nonlinear relationship between AC tenure and AC governance.

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Article
Publication date: 12 November 2024

Yan Liu and Qiang Wang

This study aims to examine the performance implications of blockchain implementation in the supply chain and explore how blockchain functions and supply chain processes of…

81

Abstract

Purpose

This study aims to examine the performance implications of blockchain implementation in the supply chain and explore how blockchain functions and supply chain processes of blockchain implementation moderate the effect on firm performance.

Design/methodology/approach

Using 220 blockchain implementations announced between January 2015 and December 2022, we use the event study methodology to estimate the effects of blockchain implementation on the firm value. Regression analyses are conducted to examine the moderating effects of blockchain functions and supply chain processes.

Findings

First, there is a positive and statistically significant relationship between blockchain implementation in the supply chain and firm value. Second, we find that abnormal returns from blockchain implementation are higher when used with blockchain’s contract automation function and applied in downstream processes, supporting the moderation effects.

Originality/value

The study provides empirical evidence on the effects of the blockchain implementation on firm performance, taking into account the complexity of blockchain functions and supply chain processes. It enriches the current understanding of how blockchain implementation in the supply chain contributes to firm value.

Details

Industrial Management & Data Systems, vol. 125 no. 1
Type: Research Article
ISSN: 0263-5577

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Publication date: 5 November 2024

Frank Fernandez, Hilary L. Coulson and Yali Zou

Abstract

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Leadership Talks
Type: Book
ISBN: 978-1-83753-555-2

Available. Open Access. Open Access
Article
Publication date: 28 October 2024

Lisa Heldt and Ekaterina Pikuleva

This paper aims to investigate the emergence of blockchain-enabled traceability in complex multi-tiered supply chains, focusing on the perspective of upstream suppliers…

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Abstract

Purpose

This paper aims to investigate the emergence of blockchain-enabled traceability in complex multi-tiered supply chains, focusing on the perspective of upstream suppliers. Blockchain technology receives attention for its potential to enable better traceability and thus sustainability risk management, yet there is limited empirical evidence on how actual implementation unfolds. We aim to understand how blockchain adoption unfolds in practice, particularly in critical mineral supply chains that are critical to the sustainability transition yet linked to severe environmental and human rights risks and to explore the role of traditionally non-focal firms in this process.

Design/methodology/approach

Adopting a process-based case study design, our research is grounded in data collected through participant observation (>12 months) within an upstream mining company, supplemented by interviews and document review. Our study employs the complex adaptive systems (CAS) lens and uses an abductive approach for data analysis.

Findings

In our case, blockchain-based traceability in the cobalt supply chain was co-constructed over time, fundamentally driven by a large upstream supplier but enabled through supply-chain-spanning collaboration with like-minded downstream actors and successive expansion into the opaque midstream, enabled through a stakeholder alliance forum and formalized in the blockchain. We find, however, that visibility, standards, trust and follow-up capacities need to exist in their own right, ideally prior to blockchain implementation.

Originality/value

Our paper provides empirical insights from an upstream (vs downstream) perspective and investigates blockchain’s implementation (vs potential) to complement and ground existing research. Further, we extend the CAS framework by emphasizing agency and visible horizon of traditionally non-focal firms.

Details

International Journal of Physical Distribution & Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0960-0035

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Article
Publication date: 17 January 2025

Hilary Mati Kilonzo, Moses Muriithi and Benedicto Onkoba Ongeri

Housing finance is frequently difficult to provide in developing nations due to unstable macroeconomic conditions and a lack of supportive legal, technological and regulatory…

19

Abstract

Purpose

Housing finance is frequently difficult to provide in developing nations due to unstable macroeconomic conditions and a lack of supportive legal, technological and regulatory frameworks (Lea and Bernstein, 1996). Governments in these countries have, therefore, created a range of organizations and initiatives to improve the flow of capital to the housing market on a footing that is affordable to their populations given the household income levels (Ram and Needham, 2016). Housing, however, is by its very nature a significant investment requiring a considerable capital outlay at the onset (Dasgupta et al., 2014). This makes acquiring it challenging, particularly in underdeveloped nations where saving tendencies are quite low partly because of low-income levels (Keller and Mukudi-Omwami, 2017). As a result, many developing nations struggle with severe housing issues that lead to slums, overcrowding and related health issues.

Design/methodology/approach

The theoretical model for analyzing housing finance in Kenya in this study incorporates both demand and supply aspects, drawing from Brueckner’s (1994) framework. This model divides factors influencing demand into certainty and uncertainty conditions faced by households. In terms of certainty, the model considers factors that households can predict reliably. First is income, households are assumed to have stable income, allowing accurate assessment of budget constraints and mortgage decisions. Second is interest rates. While interest rates fluctuate, the model assumes that households have information about current rates, enabling informed decision-making. Finally, existing housing costs, such as rent or mortgage payments, are treated as fixed and predictable, facilitating accurate budget planning. Conversely, uncertainty factors include future income, future interest rates and housing prices. Households face uncertainty regarding future income, which can impact their mortgage repayment ability due to job market changes or unforeseen events. The model does not predict future interest rate changes, which can affect the affordability of mortgages. Furthermore, future fluctuations in housing prices add uncertainty to the benefits of homeownership and mortgage debt. Due to these uncertainties, the model in this study assumes certainty conditions, focusing on households maximizing their utility. In Brueckner’s model, a utility function captures household preferences and well-being linked to consumption choices, specifically between housing (H) and nonhousing goods (N). The utility function helps determine optimal income allocation, influenced by income (M), prices (P) and return on savings (t). The utility maximization problem involves selecting optimal amounts of housing and nonhousing consumption while managing housing credit (C).

Findings

The study confirms a significant long-run relationship between house finance and several macroeconomic variables, including interest rates on credit, inflation, unemployment and gross domestic product (GDP). The negative and significant error correction term indicates the presence of an equilibrium relationship, suggesting that the housing finance market in Kenya self-corrects swiftly in response to economic shocks. This efficiency could be attributed to increasing competition among financial institutions or a growing public awareness of housing finance options, implying a relatively well-developed market. Such responsiveness suggests that government policies aimed at influencing housing finance might have a quicker impact. For instance, introducing subsidies to reduce credit rates could rapidly boost housing finance activity (World Bank, 2019). However, the flip side of a fast-adjusting market is potential volatility, where rapid swings in economic factors could lead to significant fluctuations in housing finance availability, posing risks for both lenders and borrowers (Braun et al., 2022). Moreover, a rapid adjustment might not necessarily reflect a perfectly healthy market; it could indicate underlying issues like speculation or easy access to credit, potentially leading to bubbles or financial instability (Agnello et al., 2020).

Originality/value

This study reveals key insights into the determinants of housing finance in Kenya, demonstrating a significant long-run relationship between housing finance and economic variables such as interest rates, inflation, unemployment and GDP. The efficient adjustment of the housing finance market to economic changes suggests that government policies can rapidly influence housing finance, although this responsiveness also implies potential volatility and risks, including financial instability. Policymakers should, therefore, focus on maintaining macroeconomic stability and monitoring the housing market for signs of overheating. Encouraging competition among lenders and diversifying housing finance products can help ensure sustainable market adjustments. Credit interest rates show a modest but positive relationship with housing finance, suggesting that a stable lending environment could stimulate activity. Policymakers should manage credit availability to prevent excessive expansion and instability, enhancing financial inclusion and fostering competition in the banking sector. Inflation positively impacts housing finance, with rising inflation driving demand for real assets like housing. However, significant interest rate hikes by the Central Bank to combat inflation could reduce mortgage affordability. A flexible interest rate policy, along with targeted interventions like subsidized rates for first-time buyers, is necessary to balance market stimulation with inflation control. Unemployment’s negative impact on housing finance underscores the need for robust unemployment benefits and job training initiatives to support financial stability during job losses. Targeted housing finance programs for low- and middle-income earners can also improve mortgage accessibility. The positive correlation between GDP growth and housing finance indicates that economic expansion drives housing demand. Policymakers should prioritize initiatives that promote long-term economic growth, such as infrastructure development and innovation. Finally, the insignificance of savings interest rates in influencing housing finance suggests that traditional monetary policy may have limited effects. Promoting financial literacy and developing tailored savings instruments could strengthen the connection between savings and housing finance over time.

Details

International Journal of Housing Markets and Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8270

Keywords

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Abstract

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Leadership Talks
Type: Book
ISBN: 978-1-83753-555-2

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Article
Publication date: 9 December 2024

Carrie Q. Gui, Meng Lyu and Joseph H. Zhang

This study aims to review and synthesize the burgeoning field of auditing research utilizing Chinese data. Over the past decades, there has been a remarkable rise in such…

56

Abstract

Purpose

This study aims to review and synthesize the burgeoning field of auditing research utilizing Chinese data. Over the past decades, there has been a remarkable rise in such research, driven by China’s abundant audit data, distinctive institutional features and enduring cultural influences. The purpose is to comprehensively review auditing studies featured in top-tier accounting journals, shedding light on the unique contributions made possible by Chinese data. By identifying key themes across domains, this paper aims to underscore the cultural and contextual disparities between China and Western countries, predominantly the USA, within the area of auditing.

Design/methodology/approach

This study presents a systematic review of China-themed auditing research, primarily published in seven leading global accounting journals. The researchers conducted a comprehensive search of the websites of these journals, identifying relevant articles using search terms such as “China auditing,” “Chinese Stock Market and Accounting Research (CSMAR),” “institutional environment,” and “internal control.” After the initial search, 54 relevant articles were selected and reviewed. The study covers all China-specific auditing research, categorizing key themes into six areas to explore how scholars use Chinese data to address important auditing questions.

Findings

The findings reveal a significant increase in auditing research utilizing Chinese data, prominently featured in top-tier academic journals. This study categorizes six central themes, highlighting the broad range of topics explored using Chinese audit data. More importantly, the research identifies substantial cultural and contextual differences between China and Western nations, particularly the USA, that influence the auditing profession and markets. Exploring these themes underscores the invaluable insights derived from Chinese data, shedding light on areas not previously addressed by studies relying solely on Western datasets.

Originality/value

The value of this study lies in its comprehensive examination of seminal auditing studies using Chinese data, making a distinctive contribution to the auditing literature. This paper highlights the inadequacies of Western datasets in addressing certain auditing questions and emphasizes the unique advantages offered by China’s extensive public audit data, institutional characteristics and cultural determinants. The identified gap in the literature underscores the unexplored opportunities for further research in the Chinese auditing context. This study, therefore, provides a roadmap for future scholars, encouraging the exploration of new avenues and fostering a deeper understanding of the cultural nuances influencing auditing practices in China.

Details

Journal of Accounting Literature, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-4607

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Article
Publication date: 4 January 2024

Takehide Ishiguro and Akihiro Yamada

This study investigates the relationship between foreign ownership, earnings quality and overinvestment in Japanese zombie firms.

143

Abstract

Purpose

This study investigates the relationship between foreign ownership, earnings quality and overinvestment in Japanese zombie firms.

Design/methodology/approach

The study makes use of data from Japanese firms listed on the first section of the Tokyo Stock Exchange from 2009 to 2019. The study employs logistic and multinomial logistic models to test whether the overinvestment behavior of zombie firms is mitigated by foreign shareholdings and earnings quality.

Findings

The results show that (1) zombie firms tend to overinvest; (2) an increase in foreign ownership mitigates the overinvestment of zombie firms and (3) the mitigation of zombie firms' overinvestment by foreign ownership is stronger with higher earnings quality.

Originality/value

This study extends the discussion of earnings quality and investment efficiency to the zombie firm setting. Previous studies in accounting suggest that high earnings quality enhances firms' investment efficiency. The findings suggest that both a change in ownership structure and high-quality accounting information are necessary to mitigate the inefficiency of zombie firms.

Details

Asian Review of Accounting, vol. 32 no. 5
Type: Research Article
ISSN: 1321-7348

Keywords

Available. Open Access. Open Access
Article
Publication date: 29 April 2024

Giovanna Culot, Guido Orzes, Marco Sartor and Guido Nassimbeni

This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition…

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Abstract

Purpose

This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions.

Design/methodology/approach

The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective.

Findings

Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection.

Originality/value

This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.

Details

Supply Chain Management: An International Journal, vol. 29 no. 7
Type: Research Article
ISSN: 1359-8546

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Article
Publication date: 17 September 2024

Solomon Oyebisi, Mahaad Issa Shammas, Hilary Owamah and Samuel Oladeji

The purpose of this study is to forecast the mechanical properties of ternary blended concrete (TBC) modified with oyster shell powder (OSP) and shea nutshell ash (SNA) using deep…

18

Abstract

Purpose

The purpose of this study is to forecast the mechanical properties of ternary blended concrete (TBC) modified with oyster shell powder (OSP) and shea nutshell ash (SNA) using deep neural network (DNN) models.

Design/methodology/approach

DNN models with three hidden layers, each layer containing 5–30 nodes, were used to predict the target variables (compressive strength [CS], flexural strength [FS] and split tensile strength [STS]) for the eight input variables of concrete classes 25 and 30 MPa. The concrete samples were cured for 3–120 days. Levenberg−Marquardt's backpropagation learning technique trained the networks, and the model's precision was confirmed using the experimental data set.

Findings

The DNN model with a 25-node structure yielded a strong relation for training, validating and testing the input and output variables with the lowest mean squared error (MSE) and the highest correlation coefficient (R) values of 0.0099 and 99.91% for CS and 0.010 and 98.42% for FS compared to other architectures. However, the DNN model with a 20-node architecture yielded a strong correlation for STS, with the lowest MSE and the highest R values of 0.013 and 97.26%. Strong relationships were found between the developed models and raw experimental data sets, with R2 values of 99.58%, 97.85% and 97.58% for CS, FS and STS, respectively.

Originality/value

To the best of the authors’ knowledge, this novel research establishes the prospects of replacing SNA and OSP with Portland limestone cement (PLC) to produce TBC. In addition, predicting the CS, FS and STS of TBC modified with OSP and SNA using DNN models is original, optimizing the time, cost and quality of concrete.

Details

World Journal of Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1708-5284

Keywords

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