Industry 4.0 technologies in the manufacturing sector: Are we sure they are all relevant for environmental performance?

This research contributes to the debate about the relevance of Industry 4.0 technologies in improving environmental performance in the manufacturing industry. We employed a qualitative–quantitative approach in which 19 Italian operations managers were interviewed and 260 managers responded to an online questionnaire. The effects of various technologies were ranked using ordinal regression. Comments and suggestions gave context to the quantitative results. Sensors, radio-frequency identification, artificial intelligence and analytics were found to be most relevant in improving environmental performance, whereas simulation software contributed moderately. Additive manufacturing, cobots, robots, automated mobile robots and automated guided vehicles had a negative effect, augmented reality had no effect and other technologies indirectly affected environmental performance. We also found a lack of knowledge and application as well as scepticism about technologies such as artificial intelligence and augmented reality. Finally, there was concern about the disposal of electrical and electronic waste produced by these technologies.     

Alternative balanced scorecards built from paradigm models in strategic HRM and employment/industrial relations and used to measure the state of employment relations and HR system performance across U.S. workplaces

This paper constructs alternative balanced scorecards based on high‐performance work system (HPWS) and employment relations system (ERS) models. The models are depicted and compared in diagrams and used as framework skeletons for building separate HPWS and ERS scorecards, intended to provide a detailed data picture of the operational health and performance of an organization's employment/HR system and its operations, processes, and inputs/outputs. The scorecards are filled in with nationally representative data from 2,000+ U.S. workplaces using more than 50 employment/HR indicators, as reported by separate panels of managers and employees. The indicators for each workplace are aggregated into an overall HR/employment system score, ranked from low‐to‐high, and graphed as frequency distributions. These distributions provide a unique snapshot picture of the mean and dispersion of the state of employment relations and HR system performance for companies across the United State. They also reveal that “models matter” since the HPWS and ERS scorecards provide distinctly different evaluation assessments.     

The valuation relevance of environmental performance revisited: The moderating role of environmental provisions

This study attempts to broaden our understanding of the value relevance of environmental performance by providing empirical evidence on the moderating role of financial environmental reporting. Previous studies find that firms' environmental performance can be both positively and negatively associated with market value. Such contradictory findings can be attributed to the fact that environmental performance is associated with future economic benefits and costs. This study suggests that firms with recognized environmental provisions on their balance sheets enable investors to disentangle these opposite effects either by signaling strong future financial performance or by enhancing the reliability of environmental performance information. Regardless of the mechanism by which this moderation effect is invoked, it is hypothesized that capital market participants place a positive and significantly higher value on the environmental performance ratings of firms with recognized environmental provisions than on the ratings of firms without environmental provisions. Utilizing a sample of 692 firm-year observations of French listed firms and employing a linear price-level model that associates the market value of a firm's equity with its environmental performance, I provide empirical evidence to corroborate this thesis. In addition to contributing to the academic debate on the market valuation implications of environmental performance, this study intends to provide useful insights from a country that can be considered a pioneer of environmental reporting legislation; hence, it provides valuable lessons for other jurisdictions that are in the process of developing their sustainability reporting regulations. Finally, the findings of this study support the calls for more integrated reporting showing that the interaction of financial and non-financial information has market valuation implications.     

Asymmetric information consolidation and price discovery: Inferring bad news from insider sales

Due to the paucity of sources of negative firm‐specific information, US capital markets have more difficulty identifying and incorporating bad news into stock prices than they do good news. Even though insider selling is a potentially important proxy for undisclosed bad news, researchers have difficulty ex ante identifying information‐based sales due to an inability to separate liquidity‐motivated from information‐based insider trades. We hypothesize that when insiders in multiple firms sell shares of one firm in which they are insiders and at the same time buy shares of other insider portfolio firms, the sale is more likely to be information‐based, since the proceeds are reinvested. Conversely, when an insider sells one firm without purchasing others or sells multiple insider firms the sale is likely liquidity‐motivated. We find that insider sales identified as information‐based using this algorithm are followed by significant negative abnormal returns. Information‐based sales are also more likely to be associated with delistings, earnings declines and earnings restatements. Analysts are also more likely to revise their earnings forecasts downwards for these firms. It is thus possible to ex ante identify insider sales with information content. Our results will be of interest to investors and also to regulators designing insider trading rules.     

Lobbying as a potent political marketing tool for firm performance: A closer look

This study endeavors to enhance political marketing literature about the impact of lobbying on firm performance. Our sample is composed of 140 U.S. firms and spans the years 2007–2014 to encompass the 2007–2009 recession and the subsequent recovery period. Our findings indicate that lobbying expenses positively contribute to firm performance. Also, government contracts in both ways, dollar amount and number of government contracts, act as mediators between lobbying expenses and firm performance. In addition, organizational slack moderates the relationship between lobbying expenses and government contracts. The managerial implications suggest that lobbying expenses can be leveraged as a potent tool for firm performance. Firms with larger lobbying efforts acquired both, higher dollar amounts and a greater number of government contracts.     

Commemorating the 50‐Year Anniversary of Ball and Brown (1968): The Evolution of Capital Market Research over the Past 50 Years

We commemorate the 50th anniversary of Ball and Brown [1968] by chronicling its impact on capital market research in accounting. We trace the evolution of various research paths that post–Ball and Brown [1968] researchers took as they sought to build on the foundation laid by Ball and Brown [1968] to create a body of research on the usefulness, timeliness, and other properties of accounting numbers. We discuss how those paths often link back to the groundwork laid and questions originally posed in Ball and Brown [1968].     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

In the city: The John Lewis partnership and planned shopping centres

A defining feature of large-scale retailing during the period 1950–1980 was the emergence and evolution of planned shopping centres. During the 1950s, department stores in the United States were in the vanguard of this phenomenon. In contrast, British department stores continued operating from traditional high street sites, and had limited opportunities for expansion within planned shopping centres until the 1970s. This paper addresses the connection between department store retailing and the development of the planned shopping centre in Britain from the perspective of one enterprise: the John Lewis Partnership. The article demonstrates that the Partnership was willing to operate department stores within centrally located shopping centres, but was circumspect about operating stores in non-centrally located shopping centres.     

Perceptions of the benefits of the A3 planner in facilitating project-based learning in accounting education

This paper evaluates ways of instilling project management skills into accounting-based learning by the use of an iterative A3 planner to plan, monitor and review assignment progress. The application of an A3 planner to facilitate a project-based learning (PBL) group assignment in undergraduate accounting education has been critically evaluated in terms of both the student and tutor experience. The study uses a mix of qualitative and quantitative data. Quantitative data assisting exploration of perceptions were collected through 100 undergraduate students. A series of focus group discussions were carried out to investigate students’ engagement and tutors’ teaching experiences regarding the adoption of the A3 planner. The results suggest that the A3 planner promotes active planning and effective management of a PBL group assignment. It makes students’ thought processes more visible thereby facilitating and enhancing the tutoring/mentoring process. Moreover a more interactive and transparent approach by doing assignment via the use of an iterative A3 planner has ensured more feedback points and action based efficiency in the doing approach for learners.     

我国M2现状及未来趋势浅析

对我国当前M2快速增长的原因,从经济发展、居民储蓄和外汇储备等三个方面进行深入分析,并在此基础上对未来发展趋势进行预测分析。