Search results

How to embed artificial intelligence (AI) in human resource management (HRM) is one of the core challenges of digital HRM. Despite regulations demanding humans in the loop to ensure human oversight of AI-based decisions, it is still unknown how much decision-makers rely on information provided by AI and how this affects (personnel) selection quality.

This paper presents an experimental study using vignettes of dashboard prototypes to investigate the effect of AI on decision-makers’ overreliance in personnel selection, particularly the impact of decision-makers’ information search behavior on selection quality.

Our study revealed decision-makers’ tendency towards status quo bias when using an AI-based ranking system, meaning that they paid more attention to applicants that were ranked higher than those ranked lower. We identified three information search strategies that have different effects on selection quality: (1) homogeneous search coverage, (2) heterogeneous search coverage, and (3) no information search. The more applicants were searched equally often (i.e. homogeneous) as when certain applicants received more search views than others (i.e. heterogeneous) the higher the search intensity was, resulting in higher selection quality. No information search is characterized by low search intensity and low selection quality. Priming decision-makers towards carrying responsibility for their decisions or explaining potential AI shortcomings had no moderating effect on the relationship between search coverage and selection quality.

Our study highlights the presence of status quo bias in personnel selection given AI-based applicant rankings, emphasizing the danger that decision-makers over-rely on AI-based recommendations.

This study investigates the relationship between child gender and a CEO’s top management hiring decisions.

Hypotheses were tested using secondary data on 121 S&P 500 male CEOs, their children, and their top management teams.

Results indicate that child gender is associated with a male CEO’s TMT hiring decisions. Specifically, we find that male CEOs with only daughters were significantly more likely to hire women to their TMTs than male CEOs with only sons and those with both sons and daughters.

This study provides evidence for the roles of familiarity, learning, and empathy in reducing gender biases in selection decisions. Top management hiring decisions have wide implications for organizational settings in general and for the breaking of the glass ceiling in particular.

Reducing gender bias in top manager hiring decisions directly relates to the United Nations’ Sustainable Development Goal 5 of achieving gender equality as women are consistently under-represented at the top of organizations across the world.

By focusing on the hiring of top managers, this study includes hiring decisions that directly impact firm operations. To our knowledge, this is the first study to examine the relationship between child gender and executive hiring decisions with a US S&P 500 sample.

This study aims to investigate the impact of Internet use on household financial market participation and portfolio choice.

Based on the Chinese General Social Survey 2017 (CGSS2017), this study empirically explores whether Internet use affects household financial market participation in China with an Endogenous Switching Probit model.

The results show that households using the Internet are more likely to invest in financial markets. Further research shows that households with high Internet use are significantly more likely to participate in financial markets than households with low Internet use. From the perspective of household portfolio choice, Internet use has a certain role in increasing the probability of portfolio diversification. However, among households that have invested in financial markets, those with a high-frequency use of the Internet do not show an impact on portfolio diversification.

This study complements existing research about the impact of Internet use or not on household financial market decisions and portfolio choice, expands the knowledge on the household financial market choice from the respective of the degree of Internet use.

This chapter reviews the econometric approaches typically used to deal with the spike of zeros when modelling non-negative outcomes such as expenditures, income, or consumption. Relying on the assumptions of selection on observables for evaluating a policy or treatment, this chapter discusses other issues that arise with spikes of zeros in the data, including the analyst's choice between full information versus quasi-likelihood methods, considering whether observed zeros are true or masking more complex behavioural decisions, and dealing with zeros that arise due to self-selection. This chapter ends with discussions of empirical strategies to deal with these behavioural assumptions and a brief review of the literature where such strategies were employed.

Agency theory postulates that research and development (R&D) investments are subject to managerial discretion and thus may not enhance firm value as expected. The inconclusive empirical findings in the literature is a testament of that. This paper aims to investigate the interplay between board gender diversity (i.e. women on boards) and value relevance of firms’ effort to innovate as indicated by firms’ R&D investments.

Through a sample of 1,626 US-listed firms from the period 2004 to 2019, the authors examine whether board gender diversity promotes or hampers value relevance of firms’ efforts to innovate. The authors use ordinary least squares as the baseline model and address potential endogeneity through instrumental variable two-stage least square, and selection bias through Heckman selection model. Finally, the authors use the financial crisis of 2008 as a natural experiment to investigate the effect of board gender diversity during the crisis period.

The results show that board gender diversity positively moderates the relation between R&D and firm value. In times of financial crisis, R&D does not destroy firm value in firms with gender diverse board. The results are robust to measurement error, endogeneity issue, particularly simultaneity and selection bias.

The findings in this study have several practical implications. Firms that invest heavily in R&D should be mindful of gender diversity in their board recruitment strategies to enhance innovation outputs and firm value. Current and potential investors (i.e. shareholders) should take into consideration board gender diversity in their investment decision-making processes as the results show that gender diverse boards promote more effective governance, which, in turn, leads to better alignment of R&D investments with shareholder value. Regulators aiming to improve corporate governance policies should encourage gender diversity on the boards. The results align with global initiatives such as the United Nations Sustainable Development Goals, particularly Goal 5 on gender equality. Policymakers may use the findings in this study to advocate for more gender diverse governance structures within corporations.

This study investigates the role gender diverse boards play in creating value from firms’ R&D activities.

This paper aims to examine whether the cooperation between female chief financial officers (CFO) and the proportion of female directors would impact investment efficiency. The investigation is grounded in the increasing number of female top managers globally and the notion that female tends to cooperate more with other female than with male.

This study uses publicly listed firms in Bursa Malaysia from 2016 to 2020, which yielded a sample of 2,022 firm-year observations. The authors used multivariate ordinary least square regression to test the relationship, and to correct for the selection bias, the Heckman selection and PSM test were used.

The authors find a positive relationship between female CFOs and investment efficiency. A higher proportion of female directors accentuates this result. The findings support the homophily argument that similar characteristics (gender) promote cooperation. This shows that cooperation between female CFOs and directors improves investment efficiency. The results suggest that the improvement in investment efficiency could relate to higher managerial discretion for female CFOs and their ability to collaborate with female directors. These results are robust to a series of additional endogeneity tests. The findings have important implications for policymakers and firms to encourage more appointments of females in top management positions.

By highlighting the cooperation between female CFOs and female directors, this study contributes to the understanding that cooperation among females improves investment efficiency.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This research endeavors to assess the influence of financial shared service centers (FSSCs) on the quality of accounting information within China’s A-share listed companies. Using a multi-period difference-in-differences (DID) model, the study aims to empirically examine the correlation between the adoption of FSSCs and the quality of accounting information.

The study uses a robust methodology to evaluate the relationship between FSSCs and accounting information quality (AIQ). Leveraging the established FSSCs within China’s A-share listed companies as the treatment group, this research adopts a multi-period DID model. This approach enables a rigorous empirical examination of the influence exerted by FSSCs on the overall quality of accounting information.

The present study delves into the impact of FSSCs on AIQ and conducts empirical analysis using data from Chinese A-share listed companies between 2004 and 2021. The findings substantiate that: FSSCs significantly bolster the quality of accounting information, a conclusion retained even after robustness tests. Specifically, FSSCs exhibit a positive correlation with the comparability, timeliness and disclosure quality of accounting information while demonstrating no significant influence on relevance, robustness and reliability factors.

First, the analysis primarily rests upon data from Chinese A-share listed companies between 2004 and 2021, potentially constraining the generalizability of findings across diverse contexts. Second, despite controlling for various factors, unobserved variables or external factors not encompassed in the model might influence the relationship between FSSCs and AIQ. Additionally, the study’s reliance solely on quantitative data confines exploration into qualitative aspects that might offer a more comprehensive understanding of FSSCs’ impact on AIQ.

This paper establishes a nuanced connection between FSSC operations and AIQ, furnishing direct empirical evidence for their economic implications and propounding a novel avenue for augmenting AIQ. And, it furnishes guidance for forthcoming FSSC development, accentuating the necessity of harnessing information technology to enhance the relevance, reliability and robustness of accounting information.

Majority of prior empirical studies assessing AIQ have focused on singular indicators, lacking a comprehensive depiction of its overall level. To address this gap, this paper pioneers the construction of a comprehensive index for AIQ, providing a holistic representation of its level. Furthermore, this study stands as the inaugural investigation into the relationship between China’s A-share listed firms’ FSSCs and the quality of accounting information.

This paper aims to examine the most commonly used categories of sustainability literature review regarding their purpose, nature, strengths, weaknesses and potential for impact. This paper also discusses the motivation, incremental contribution and framing that occurs by considering the research papers included in this Special Issue.

Given the paucity of clear guidelines for undertaking, writing and publishing literature review studies in sustainability research, this paper describes the main types and processes in conducting a literature review and emerging tools that can help advance the field.

This paper finds a variety of approaches in application with strengths and weaknesses, including the emerging role of software support, artificial intelligence and machine learning. This paper reviews the ethical implications of using emerging tools in the sustainability literature review methodology and their impacts on originality, authenticity and accountability. This paper discusses the seven carefully selected and meticulously reviewed articles in this Special Issue through the lens of these findings by specifically highlighting their purpose, strengths, weaknesses and practical and policy implications.

Through the systemization of ways to conduct meaningful literature reviews, this paper explores the significant relevance of the method in creating a basis of academic understanding and advancing future research that can have significant impacts on the industry. Through the discussion of the articles in this Special Issue, this paper highlights the practical and policy implications and limitations of literature reviews in sustainability research.

This paper highlights the purpose of literature reviews in identifying areas for further research and how the papers included in this Special Issue achieve this goal, i.e. how their findings possess specific positive externalities in summarizing and systematizing sustainability research.

This paper systematizes methods and processes for writing impactful literature reviews in sustainability research, particularly focusing on the use of emerging technology and the opportunities and challenges this may offer in this process.

Probiotic coadministration with soy beverages has been shown to have favorable results in human health. This study aims to conduct a systematic review of randomized clinical trials to examine the effect of probiotic soy beverages (PSB) on human health aspects such as lipid profile, oxidative stress and kidney function.

The study was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Relevant articles were extracted from PubMed, SCOPUS, Web of Science, Science Direct and Google Scholar up to April 2024. This paper searched all databases using the following keywords: (“Soy milk” OR “Soy beverage” OR “Fermented soy milk” OR “Soy Fermented Beverages”) AND (“Probiotic” OR “Probiotics”). The literature search did not consider language, age and publication date restrictions.

A total of 2,183 subjects were included in this review. PSB beneficially decreased low-density lipoprotein cholesterol and total cholesterol levels and increased high-density lipoprotein cholesterol. PSB beneficially affected superoxide dismutase, glutathione peroxidase, glutathione reductase and glutathione. PSB decreased serum creatinine and increased estimated glomerular filtration rate. Cystatin-C and progranulin decreased significantly in the PSB group. PSB had no significant effect on anthropometric indices, while decreased systolic and diastolic blood pressure.

This study provides a brief overview of the effect of PSB on lipid profile, oxidative stress, inflammation and kidney function for the first time.