Banks’ deferred tax assets during the financial crisis

Review of Quantitative Finance and Accounting - Prior studies have demonstrated that the net deferred tax liabilities of industrial firms are valued by market participants in a manner consistent...     

Non-Governmental Organizations, Shareholder Activism, and Socially Responsible Investments: Ethical, Strategic, and Governance Implications

In this article, we document the growing influence of non-governmental organizations (NGOs) in the realm of socially responsible investing (SRI). Drawing from ethical and economic perspectives on stakeholder management and agency theory, we develop a framework to understand how and when NGOs will be most influential in shaping the ethical and social responsibility orientations of business using the emergence of SRI as the primary influencing vehicle. We find that NGOs have opportunities to influence corporate conduct via direct, indirect, and interactive influences on the investment community, and that the overall influence of NGOs as major actors in socially responsible investment is growing, with attendant consequences for corporate strategy, governance, and social performance.     

A spatial interaction model for deriving joint space maps of bundle compositions and market segments from pick-any/J data: An application to new product options

We propose an approach for deriving joint space maps of bundle compositions and market segments from three-way (e.g., consumers x product options/benefits/features x usage situations/scenarios/time periods) pick-any/J data. The proposed latent structure multidimensional scaling procedure simultaneously extracts market segment and product option positions in a joint space map such that the closer a product option is to a particlar segment, the higher the likelihood of its being chosen by that segment. A segment-level threshold parameter is estimated that spatially delineates the bundle of product options that are predicted to be chosen by each segment. Estimates of the probability of each consumer belonging to the derived segments are simultaneously obtained. Explicit treatment of product and consumer characteristics are allowed via optional model reparameterizations of the product option locations and segment memberships. We illustrate the use of the proposed approach using an actual commercial application involving pick-any/J data gathered by a major hi-tech firm for some 23 advanced technological options for new automobiles.     

Preference for a career in retailing: a question of personality

Drawing on previous findings from the field of brand personality research and employer branding, this paper aims to explore the symbolic attributes of the retail industry image in South Africa and to identify those personality traits that distinguish preferred industries from the retail industry. The research provides a contemporary overview of the current image of the retail industry in South Africa from the perspective of young university students and allows retailers to strengthen their joint communication effort accordingly. Therefore, a quantitative survey study with 1426 participants from five South African universities was conducted. Participants assessed personality characteristics of the retail industry as well as their most preferred industry. The main results suggest that retail and non-retail students hold different personality perceptions of the retail industry and that prior retail involvement accounts for this difference to some extent. Moreover, the analysis shows that retailing performs significantly worse on those personality attributes that are of major importance for future job seekers. Additionally, the study identifies those attributes that exert a strong effect on students’ preferences for the retail industry. The findings provide useful communication themes for educational institutions, retail companies, and industry associations in order to foster positive personality perceptions associated with the retail industry.     

Individual Large Shareholders,Earnings Management,and Capital‐Market Consequences

Using a large hand‐collected sample of all blockholders (ownership ≥ 5%) of S&P 1500 firms for the years 2002–2009, we first document significant individual blockholder effects on earnings management (accrual‐based earnings management, real earnings management, and restatements). This association is driven primarily by these large shareholders influencing rather than selecting firms’ financial reporting practices. Second, the market's reaction to earnings announcements suggests that investors recognize the heterogeneity in blockholders’ influence on earnings management. The results highlight the highly individualized effects of blockholders and a mechanism through which shareholders impact reported earnings.     

Monday returns and asset pricing

The seasonal patterns observed on Monday stock returns are still unexplained by different asset pricing models. We attempt to fill this gap in the finance literature by using the Fama-French (Journal of Financial Economics 33:3–56, 1993) risk factors to explain the Monday seasonal. The results in the study show that Monday returns are explained by risk factors such as the market return, the size of the firms, and the book-to-market ratios of firms.     

Deriving joint space positioning maps from consumer preference ratings

Joint space multidimensional scaling maps are often utilized for positioning analyses and are estimated on survey samples of consumer preferences, choices, considerations, or intentions so as to provide a concise spatial depiction of the competitive landscape including relevant dimensions or attributes, competing brands, and consumers in the same joint space representation. Care has to be given concerning the underlying scale properties of such survey data so as not to distort the resulting joint space positioning map. We present a new joint space multidimensional scaling procedure for positioning analyses for displaying the structure in such survey data when such common ordered successive category measurement scales such as Likert, Edwards, semantic differential, etc., are employed. We present the technical details of this stochastic ordered preference multidimensional scaling vector model as well as the maximum likelihood estimation-based algorithm devised for parameter estimation. Favorable comparisons are made with several existent multidimensional scaling methods in representing the internal structure for such data in marketing positioning studies. An actual commercial positioning application concerning large sports utility vehicles consideration to buy judgments is presented with predictive validation comparisons with other multidimensional scaling joint space procedures.     

A two-stage technology foresight model with system dynamics simulation and its application in the Chinese ICT industry

Technology foresight is a process that identifies the critical technologies a country or industry needs to develop in order to shape a desired future. In this paper, a two-stage technology foresight approach is proposed. During the first stage, critical technologies are identified and evaluated by nationwide experts through Delphi surveys. In the second stage, a system dynamics simulation model is used to estimate how critical parameter values are likely to impact the attainment of foresight goals. A detailed illustration of this two-stage process is provided by a technology foresight case study in the Chinese information and communication technologies (ICT) industry. Because it was identified by the first-stage Delphi method as a critical technology, the diffusion of 4th generation wireless telecommunication technology (4G) was simulated, and experimentation was conducted. Suggestions are provided regarding how the Chinese information industry would need to expand the IP network infrastructure in order to support technology foresight goals under different scenarios.     

A sectoral approach to Okun’s Law

The study adds to the existing literature on the relationship between output and unemployment by using a sectoral specification of Okun’s Law to capture the differential sensitivity of the unemployment rate to output developments in the services and manufacturing sectors. Using quarterly data for the period between 2000 and 2012, we show that Malta’s unemployment rate has been more sensitive to output developments in the services sector than to those in the manufacturing sector. We use different equation specifications and the youth unemployment rate to show that the impact resulting from developments in the manufacturing sector occurs mainly via lay-offs while developments in the services sector affect the unemployment rate via the hiring of new entrants into the labour market.