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This paper aims to provide new evidence that corporate site visits give institutional investors better opportunities to obtain information and exert monitoring powers, which reduce listed firms’ earnings management.

This paper explores how private communications affect firms’ earnings management by using a sample of institutional investors’ visits to the corporate sites of Chinese listed firms between 2010 and 2018. This study uses the performance-matched Jones model (Kothari et al., 2005) to measure accrual-based earnings management and Roychowdhury’s (2006) method to measure real earnings management. The authors also perform several robustness checks including an alternative measure of accounting accruals, a two-stage instrumental regression and the Heckman two-step approach.

Using a sample of institutional investors’ site visits to Chinese listed firms during the 2010–2018 period, this study finds that institutional investors’ site visits reduce listed firms’ earnings manipulation activities (both accrual-based and real). This association is robust to several checks, including an alternative measure of accounting accruals, a two-stage instrumental regression and the Heckman two-step approach. This study further documents that other private communication approaches such as private in-house meetings and conference calls moderate the effect of site visits.

As the Shenzhen Stock Exchange is one of the few stock markets to mandate that listed firms record and disclose their private communication information, this study also has implications for researchers and policymakers who work in other stock markets.

To the best of the authors’ knowledge, this study is the first comprehensive study of the impact of private communications on earnings management. This study extends the earnings management literature by examining institutional investors’ information acquisition process and revealing a negative association between their site visits and listed firms’ earnings management. Moreover, this study examines the effects not only on traditional accounting accruals but also on real earnings management. In addition to studies that emphasize the effect of corporate site visits on individuals and market reactions, this study examines the effect of site visits on firms’ financial misbehavior. This study shows that institutional investors’ corporate site visits provide external monitoring that mitigates listed firms’ earnings management behavior.

Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

This chapter explores the adaptation and evolution of stand-alone CSR reporting in two different political economies and late-capitalist countries: Brazil and South Korea. Instead of selecting between new institutionalism and the varieties of capitalism (VOC) approach, this study attempts to explore how the interaction between converging and diverging pressures appears in the adaptation and evolution of stand-alone CSR reporting (i.e., cross-fertilization process) in two countries.

Using qualitative content analysis this study focuses on the frameworks of CSR reports and the way CSR issues are described within the stand-alone CSR reports of four telecommunication companies in Brazil and South Korea.

Even though CSR reports in both countries have become similar due to the convergence of frameworks of CSR reporting, the key themes and the representation on each theme are still embedded within each form of market economy: a hierarchical market economy (HME) in Brazil and a network market economy (NME) in South Korea. From a cross-fertilization perspective, this chapter shows that the adaptation and evolution of CSR reporting occurs at two different levels of CSR reporting.

This study has three major values. First, it explains the two different levels of the adaptation and evolution process of CSR reporting by bringing a dynamic cross-fertilization view. Second, it provides a qualitative study that focuses on the content of CSR disclosures instead of the quantity of those disclosures. Lastly, it contributes to the academic and practical research on CSR in late-capitalist countries and in two under-researched types of political economies.

This research provides accounting-ethics authors and administrators with a benchmark for accounting-ethics research. While Bernardi and Bean (2010) considered publications in business-ethics and accounting’s top-40 journals this study considers research in eight accounting-ethics and public-interest journals, as well as, 34 business-ethics journals. We analyzed the contents of our 42 journals for the 25-year period between 1991 through 2015. This research documents the continued growth (Bernardi & Bean, 2007) of accounting-ethics research in both accounting-ethics and business-ethics journals. We provide data on the top-10 ethics authors in each doctoral year group, the top-50 ethics authors over the most recent 10, 20, and 25 years, and a distribution among ethics scholars for these periods. For the 25-year timeframe, our data indicate that only 665 (274) of the 5,125 accounting PhDs/DBAs (13.0% and 5.4% respectively) in Canada and the United States had authored or co-authored one (more than one) ethics article.

Unlike other types of corporate disclosure, corporate political disclosure (CPD), which is the disclosure of corporate political contributions and the related governing policies and oversight mechanisms, does not provide completely new information to stakeholders. Some of the information disclosed in CPD is available from other public records (e.g. the Federal Election Committee website or OpenSecrets website). Given this unique feature of CPD, it is interesting to investigate the cost and benefit tradeoff for firms of altering their CPD practice in response to policy and political uncertainty.

This study employs recently developed indexes of aggregate economic policy uncertainty (EPU) and a novel dataset of CPD transparency to examine the impact of EPU on CPD transparency and how the proprietary cost of corporate political activities moderates this association. The sample consists of S&P 500 companies from the 2012 to 2019 period.

The authors document that firms mitigate the heightened information asymmetry associated with higher aggregate EPU by increasing CPD transparency. The positive association between EPU and CPD is less pronounced for firms that are more sensitive to EPU, for firms that more actively manage EPU through corporate political contributions or lobbying activities and for firms that are followed by more analysts. The authors also find that more transparent CPD helps to mitigate the information asymmetry caused by heightened EPU. This study’s results hold when the authors control for other types of voluntary corporate disclosure.

This study contributes to the emerging literature on the determinants of CPD transparency by identifying EPU's positive impact on CPD transparency. This study also provides empirical evidence that the proprietary costs arising from the controversial nature of corporate political activities dampen firms' incentives to provide transparent CPD in response to heightened EPU, and that information on corporate political activities gathered and processed by financial analysts seems to lower the marginal benefit to companies of publicizing CPD on their own website.

Although still under-researched and characterized by a fragmented understanding, unlearning and forgetting have recently received increased scholarly attention. The purpose of this systematic literature review is to survey and evaluate key works in the field of organizational unlearning and forgetting. Through analyzing and synthesizing common themes, this paper aims to highlight research gaps and avenues for future research.

This paper follows a systematic approach of identifying, analyzing and synthesizing pertinent literature in the field of organizational unlearning and forgetting. In total, 63 works were thoroughly reviewed.

This paper highlights different levels and scopes, as well as antecedents and consequences of organizational unlearning and forgetting. Even though unlearning and forgetting has gained increased attention, researchers still need to provide robust conceptual and empirical evidence to advance the field.

By structuring the analysis and synthesis around various constructs, theories, typologies and related themes, this paper outlines several research gaps and proposes avenues for further research. Additionally, this systematic literature review resulted in the development of a framework based on the intentionality and depth of knowledge loss, which allows future researchers to position their research and differentiate themselves from other literature in the field.

In this chapter, four bi-objective vehicle routing problems are considered. Weighted-sum approach optimization models are formulated with the use of mixed-integer programming. In presented optimization models, maximization of capacity of truck versus minimization of utilization of fuel, carbon emission, and production of noise are taken into account. The problems deal with real data for green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country, and La Rioja, Spain.

Heterogeneous fleet of trucks is considered. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Modern logistic companies planning delivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, and utilization of fuel, carbon emission, and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution. The computational experiments were performed using the AMPL programming language and the CPLEX solver.

This study aims to examine the relationship between concrescent conversation environment (CCE), psychological safety and team effectiveness. Although CCE has been known to influence team outcomes, little is known about how it influences them. Integrating the social constructionist and social psychology perspectives, this study argues that CCE ignites a climate of psychological safety resulting in “joint-action” necessary for positive team outcomes.

Survey data were collected from 301 team members from US firms operating in different industries. Data were analyzed using SmartPLS.

The study establishes CCE as an antecedent to psychological safety and demonstrates that psychological safety mediates the relationship between CCE and team effectiveness.

This is one of the initial studies to show how verbal behaviors socially construct team dynamics in the shape of psychological safety to influence team outcomes. In doing so, the authors advance the theory pertaining to the role of social exchanges in team processes and outcomes.

The results provide insights on how managers can improve team outcomes by influencing the conversational environment of the team to elicit feelings of psychological safety. The results also suggest that managers must focus on relational outcomes as well, along with performance outcomes.

From a social constructionist perspective, team development is built upon the verbal behaviors of the members as they pursue tasks. However, the extant group dynamics literature undervalues conversations’ role in team processes and outcomes. This is the first study that examines the link between a team's conversational environment, psychological safety and team outcomes.

The purpose of this chapter is to optimize multi-criteria formulation for green vehicle routing problems by mixed integer programming. This research is about the road freight transportation of a Spanish company of groceries. This company has more power in the north of Spain and hence it was founded there. The data used for the computational experiments are focused in the northern region of Spain. The data have been used to decide the best route in order to obtain a minimization of costs for the company. The problem focused on the distance traveled and the altitude difference; by studying these parameters, the best solution of route transportation has been made. The software used to solve this model is CPLEX solver with AMPL programming language. This has been helpful to obtain the results for the research and some conclusions have been obtained from them.

This paper aims to investigate the strategy for low-cost yield optimization of miniaturized microstrip couplers using variable-fidelity electromagnetic (EM) simulations.

Usefulness of data-driven models constructed from structure frequency responses formulated in the form of suitably defined characteristic points for statistical analysis is investigated. Reformulation of the characteristics leads to a less nonlinear functional landscape and reduces the number of training samples required for accurate modeling. Further reduction of the cost associated with construction of the data-driven model, is achieved using variable-fidelity methods. Numerical case study is provided demonstrating feasibility of the feature-based modeling for low cost statistical analysis and yield optimization.

It is possible, through reformulation of the structure frequency responses in the form of suitably defined feature points, to reduce the number of training samples required for its data-driven modeling. The approximation model can be used as an accurate evaluation engine for a low-cost Monte Carlo analysis. Yield optimization can be realized through minimization of yield within the data-driven model bounds and subsequent model re-set around the optimized design.

The investigated technique exceeds capabilities of conventional Monte Carlo-based approaches for statistical analysis in terms of computational cost without compromising its accuracy with respect to the conventional EM-based Monte Carlo.

The proposed tolerance-aware design approach proved useful for rapid yield optimization of compact microstrip couplers represented using EM-simulation models, which is extremely challenging when using conventional approaches due to tremendous number of EM evaluations required for statistical analysis.