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The purpose of this paper is to explore a novel breast volume measuring method by mesh projection based on three-dimensional (3D) point cloud data.

Mesh projection method, a rapid and accurate method to calculate the volume of models described by triangular meshes, was transplanted to calculate breast volume based on 3D point cloud data derived from a [TC]2 3D scanner. A simple landmarking procedure was developed to decide breast boundary. Breast volumes derived from mesh projection method were compared to the results of water displacement by statistical analysis to validate its accuracy.

A novel breast volume measurement method is developed based on mesh projection method. By comparison of water displacement, mesh projection method is proved to be accurate to calculate breast volume. Furthermore, a simple and standard breast boundary landmarking procedure is established, which avoids the arbitrariness of the definition of breast boundary and improves the repetition of landmarking.

A simple and convenient tool is provided for bra industries to rapidly and accurately measure breast volume.

Mesh projection method is primarily applied to determine breast volume based on 3D point cloud data. Meanwhile, a simple and standard breast boundary landmarking procedure is put forward.

Volume-based liquidity ratios suffer from potential measurement bias due to share restriction and may misrepresent actual liquidity. To address this issue, the authors develop two modified metrics, the free-float liquidity and the alternative free-float illiquidity ratios. These measures are well suited to estimate liquidity in the presence of trading constraints, as can be found in closely held/state-owned entities, IPOs/SEOs with lockup restrictions, dual-class share structures and family-owned businesses.

The authors modify the turnover illiquidity ratio, where the number of outstanding shares is scaled by the public free float, and use natural log transformation to normalize free-float liquidity. Our dataset is composed of daily observations for US stocks included in the S&P 500 index over the 2015–2018 period. To test the validity of free-float (il)liquidity ratios, the authors perform a correlation analysis for various liquidity metrics. To examine their empirical efficiency, the authors employ pooled OLS regression models for family firms as a subsample of liquidity-constrained entities, relying on five different identifiers of family-owned businesses.

The authors’ empirical testing indicates that the proposed free-float (il)liquidity ratios compare favorably with other volume-based methods, such as Amihud's ratio, liquidity ratio and turnover ratio. For the subsample of family organizations as a restricted-share setting, the authors report significant coefficients for our free-float measures across all the family firm identifiers used. In particular, as free-float decreases with progressive family influence, the advanced ratios capture an increase (decrease) in perceived liquidity (illiquidity) that is absent in the other benchmarks.

This study allows the authors to inform the ongoing debate on the management and governance of publicly listed companies with various impediments to trade. Traditional measures understate illiquidity (overstate liquidity) as the fraction of free trading shares is limited by design or circumstances. The authors’ proposed free-float metrics offer informational gains for family leaders to aid in their financing decisions and for non-family outsiders to guide their investment choice. As a constrained free float inhibits price discovery processes, the authors discuss how restricted stock issuers may alleviate the attendant negative effects on governance and information opacity.

Increasing load factor is crucial for transport efficiency and may benefit shippers because of its potential to reduce both environmental impact and transportation costs. The purpose of this paper is to explore how shippers can increase load factor in their road transport by identifying opportunities for logistics action and influences on load factor performance measures created by such opportunities.

A case study is performed of the outgoing goods flow from the central warehouse of a large retailer in Sweden. Data are collected from interviews with the shipper and its contracted freight forwarder, as well as from archival sources and visual observations, and applied to produce a framework.

Logistics actions that can increase load factor are identified and categorised according to packaging efficiency, loading efficiency and booking efficiency, all of which are linked to logistics variables and specific performance measures in the framework. Visual observations of volumetric load factor in vehicles indicate room for improvement via, for example, making lead times more flexible.

The framework’s principles can be used to support shippers in finding opportunities to increase load factor.

The framework clarifies the concept of load factor as a whole by explaining each logistics action’s contribution to increasing load factor, as well as the actions’ combined effect in the context of a shipper and its purchased transport share.

Liquidity is an important aspect of market efficiency. The purpose of this paper is threefold: first, this paper aims to discuss indicators that provide information about liquidity in agricultural land markets. Second, this paper aims to reflect on determinants of market liquidity and analyze the relationship with land prices. Third, this paper aims to conduct an empirical analysis for Germany that illustrates these concepts and allows hypothesis testing.

This study reviews liquidity dimensions and measurement in financial markets and derives indicators applicable to farmland markets. In an empirical analysis, this study exhibits the spatial and temporal variability of land market liquidity in Lower Saxony, a German federal state with the highest agricultural production value. This study uses a rich dataset that includes 72,547 sale transactions of arable land between 1990 and 2018. The research focuses on volume-based (number of transactions, volume and turnover) and time-based (trading frequency and durations) measures. A panel vector autoregression and Granger causality tests are applied to investigate the relation between land turnover and land prices.

The paper confirms the thinness of farmland markets but also reveals regional and temporal heterogeneity of land market liquidity. This study finds that the relation between market liquidity and prices is ambiguous. This study concludes that a high demand from expanding farms absorbs supply shocks regardless of the current price level in agricultural land markets.

Even though the relevance of agricultural land markets’ thinness is widely acknowledged in the literature, this paper is one of the first attempts to measure liquidity in agricultural land markets and to explain its relationship with land prices.

The purpose of this paper is to use a text-based sentiment indicator to explain variations in direct property market liquidity in the USA.

By means of an artificial neural network, market sentiment is extracted from 66,070 US real estate market news articles from the S&P Global Market Intelligence database. For training of the network, a distant supervision approach utilizing 17,822 labeled investment ideas from the crowd-sourced investment advisory platform Seeking Alpha is applied.

According to the results of autoregressive distributed lag models including contemporary and lagged sentiment as independent variables, the derived textual sentiment indicator is not only significantly linked to the depth and resilience dimensions of market liquidity (proxied by Amihud’s (2002) price impact measure), but also to the breadth dimension (proxied by transaction volume).

These results suggest an intertemporal effect of sentiment on liquidity for the direct property market. Market participants should account for this effect in terms of their investment decisions, and also when assessing and pricing liquidity risk.

This paper not only extends the literature on text-based sentiment indicators in real estate, but is also the first to apply artificial intelligence for sentiment extraction from news articles in a market liquidity setting.

For electronic commerce applications, the importance of quality information is self‐evident, especially for firms offering information products where information either significantly augments a physical product or constitutes the product itself. Aims to use a probabilistic simulation model is used to explore the relationship between information quality and market share for firms offering an information product.

In the Excel‐based Monte Carlo model information quality is represented as a function of four general quality attributes. For these attributes, quality gaps relative to best practices are calculated and these gaps are used to drive a volume model whose output includes market share. The model is used to examine various scenarios including cases dealing with differences in a firm's initial information quality levels, differences in innovation rates and their variability, and differences in a firm's proclivity to copy advances of competitors.

The results indicate that firms starting with information quality leads tend to maintain that lead and accrue market share. However, they may lose their lead if innovation rates lag behind the competition. Generally, variation and the ability for firms to copy advances are good for markets.

Some practical implications from the findings include: the criticality of innovation and its importance in fostering quality; the ineffectiveness of insular strategies; and evidence that specialization, while benefiting markets, does not necessarily benefit individual firms.

The model presents a mechanism for scholars and practitioners to – expeditiously and inexpensively – test the impact of various information‐quality strategies.

The purpose of this research is to understand the relationship between publicity, advertising activity and corporate sales in the context of a company’s existing reputation.

The study brings together four unique industry datasets and uses discriminant analysis and multiple regression methods to examine the relationship between existing corporate reputation, publicity, advertising activity and sales levels for major multi-national companies in the technology products sector.

Positive publicity is most important in distinguishing between firms with higher and lower sales. The effects of negative publicity and advertising are dependent on a firm’s existing reputation. For companies with weaker reputations, positive publicity in tandem with business-to-consumer (B2C) advertising is most highly associated with higher company sales. Conversely, for firms with stronger existing reputations, advertising has a significantly diminished role; positive and even negative publicity are most crucial in distinguishing between companies with high and low sales. Negative publicity can be harmful to these firms though if it is not balanced by more positive publicity. Finally, the topic of news coverage is related to sales. Generally, stories that are positive reporting on business outcomes, leadership and business future and marketing practices are most important in discriminating between firms with stronger vs weaker sales.

For this set of technology product firms, publicity and advertising are relevant for sales. Firms with higher levels of sales have both more positive and negative publicity, but the volume of positive stories is much higher. Attracting negative publicity is common for firms that achieve higher sales, but it is offset by a greater number of positive stories, an aspect that public relations efforts can influence. B2C advertising spending meanwhile matters more for firms with weaker rather than stronger existing corporate reputations. It is most effective for firms with weaker existing reputations to maximize the positive signals in the marketplace as exemplified by positive publicity and B2C advertising efforts.

Little research has examined the relationship between different forms of corporate communications and sales; this study is a rare examination using publicity, advertising spending, existing reputation and sales in a durable goods and services context where there has been a particular dearth of even basic advertising studies. Beyond understanding the relative importance of publicity v. advertising, it also uniquely focuses on the individual topics of news publicity.

The purpose of this paper is to examine the determinants of the volume of environmental disclosures and their quality, with particular focus on the role of audit committees (ACs) and the effects of the Smith report recommendations for the UK Corporate Governance Code.

Quantitative large sample analysis of UK FTSE350 companies for the period 2007-2011.

Firms with higher quality ACs make higher quality disclosures. Larger firms with block shareholders have greater volume of disclosures, whilst AC quality does not increase disclosure volume.

Findings are based on evidence from single country and imply further international comparative research.

ACs mitigate the requirement for prescriptive legislation on narrative accounting disclosures relating to environmental issues.

The paper contributes to research that has examined the relationship between corporate governance mechanisms, specifically ACs, and the quality of financial reporting by considering voluntary narrative disclosures on environmental matters.

The main purpose of this study is to examine the impact of corporate carbon emissions and disclosure on corporate value, especially regarding whether disclosure helps to reduce uncertainty in valuation as predicted by carbon emissions using a unique data set on Japanese companies.

Empirical analysis of the relations between corporate carbon emissions using compulsory filing data to Japanese Government covering more than 1,000 firms, corporate carbon management disclosure (CDP disclosure), and the market value of equity.

The authors find that corporate carbon emissions have a negative relation with the market value of equity, the disclosure of carbon management has a positive relation with the market value of equity, and the positive relation between the disclosure of carbon management and the market value of equity is stronger with a larger volume of carbon emissions.

The results may be important when considering the inclusion of carbon disclosure as a component of nonfinancial disclosure. In addition, the findings encourage Japanese companies to reduce carbon emissions and to disclose their carbon management activities.

The authors provide the first empirical evidence of an interactive effect between the volume of carbon emissions and carbon management disclosure on the market value of equity. And, the results concerning the relation between environmental performance, disclosure, and market value are readily generalizable, especially as all companies emit carbon, either directly or indirectly. In addition, the results are arguably free of problems with sampling bias and endogeneity as the authors employ data obtained from the compulsory filing of carbon emissions information.

Amid increased size and complexity of the banking industry, operational risk has a greater potential to occur in more harmful ways than many other sources of risk. This paper seeks to provide a succinct overview of the current regulatory framework of operational risk under the New Basel Accord with a view to inform a critical debate about the influence of data collection, loss reporting, and model specification on the consistency of risk‐sensitive capital rules.

The paper's approach is to investigate the regulatory implications of varying characteristics of operational risk and different methods to identify operational risk exposure.

The findings reveal that effective operational risk measurement hinges on how the reporting of operational risk losses and the model sensitivity of quantitative methods affect the generation of consistent risk estimates.

The presented findings offer tractable recommendations for a more coherent and consistent regulation of operational risk.