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This study aims to reveal the quantity, quality and cultural differences of negative corporate social performance (CSP) disclosures in large firms' corporate social responsibility (CSR) reports. Firms are expected to be transparent about the impacts and outcomes of their CSP. A central aspect of transparency is balance, which means disclosing both positive and negative CSP.

Content analysis was applied to 75 CSR reports of large firms chosen from the Forbes Top 500 list. The firms belong to three cultural clusters: Anglo, Confucian Asia and Germanic/Nordic Europe.

Firms made few negative CSP disclosures, yet the quantity of negative CSP disclosures varied among cultural clusters. Reports from Germanic/Nordic Europe showed the highest number of negative CSP disclosures, reports from Confucian Asia showed the lowest number and the Anglo cluster's number fell in between. The Asian firms communicated corrective actions more often than firms from the other clusters.

This study focused on negative CSP disclosures in the CSR reports – not omitting negative CSP. The practice of self-laudatory CSR communication decreases the likelihood that relevant stakeholders will believe what firms report about.

Studies on the quality and quantity of negative disclosures are rare; by examining cultural differences, this study contributes to the limited body of knowledge.

This study aims to explore the impact of controversial firms’ corporate sustainability assessments on their risk exposure according to the environmental, social and governance (ESG) paradigm.

This study conducts a cross-sectional study using the ordinary least squares approach to test how corporate social responsibility practices affect firms’ risk exposure, testing the three single impacts of ESG components and the impact of an overall ESG assessment. This study considers the largest Standard & Poor’s (S&P) 500 stock market index companies and focus on a double-risk measurement – systematic and idiosyncratic – developing an empirical study on 132 controversial companies listed on the S&P index.

Empirical findings indicate that the overall ESG assessment and the environmental and social sub-dimensions decrease idiosyncratic firm risk. At the same time, no significant results are found according to the systematic risk component.

This study fits into the domain of risk management research, investigating whether additional and non-financial disclosures regarding sustainability issues decrease information asymmetries, improving investors’ decision-making and stakeholders’ relations. Prior literature has shown limited evidence on the relationship between corporate social performance (CSP) and firm risk based on controversial companies. The main contribution is to consider the controversy as an independent factor from the industry sector, given that the implications of CSP actions and practices are mainly firm-specific.

Due to increasing supply chain complexity, the supply chain uncertainty has become an imperative issue, which hinders the development of modern logistics and supply chain management. The paper attempts to conceptualize reverse logistics uncertainty from supply chain uncertainty literature and present the types of reverse logistics uncertainty in a triadic model.

The concept of reverse logistics uncertainty is developed based on a triadic model of logistics uncertainty and supply chain uncertainty literature. A desk research is conducted to develop a taxonomy of reverse logistics uncertainty. To better depict the reverse logistics uncertainty, we use case studies to discuss the types of reverse logistics uncertainty in the triadic model.

The study reveals four types of supply chain uncertainties in the reverse logistics. We call them reverse logistics uncertainty. Type-A and Type-B uncertainty are new types of supply chain uncertainty in the reverse logistics.

The types of reverse logistics uncertainty have not been empirically validated in industries. Especially, the two new types including Type-A and Type-B reverse uncertainty need further exploration.

Although reverse logistics has been discussed in the past decades, very few studies have been conducted on the supply chain uncertainty in returns management arena. The paper offers valuable insights to better understand the supply chain uncertainty in the reverse logistics. This also provides suggestions for both managers and researchers to reflect on the reverse logistics uncertainty management and business sustainability.

Customer social participation (CSP) is a new phenomenon that has emerged with the evolution of social media. Current literature designates customer participation in social media as “CSP”. Although CSP has been investigated in the online brand community context in social media, it has been little investigated in the context of student customers using WhatsApp – a highly trending social media platform among learners. Thus, this study aims to investigate the effectiveness of CSP in informal WhatsApp groups for academic purposes among undergraduate students of management studies.

The study adopted a single cross-sectional survey design. A structured online questionnaire was employed. Using convenience sampling technique, data were collected from 170 undergraduates of the Bachelor of Management Studies programme at the Open University of Sri Lanka.

The results revealed significant positive effects of functional, social and hedonic benefits with CSP. Meanwhile, the relationship between psychological benefits and CSP was insignificant. Furthermore, there is no influence of age and level of study on CSP among the learners in informal WhatsApp groups. Moreover, at present, the level of CSP in WhatsApp for academic purposes among students is moderate.

The role of the student as the customer and student behaviour in informal WhatsApp groups established for academic purposes have been little investigated in the field of open and distance education services. In this context, this study empirically validated the model of participation benefits and CSP in WhatsApp groups informally established for academic purposes.

The purpose of this paper is to examine the efficacy of the Japanese ten-item personality inventory (TIPI-J), a short version of the big five (BF) questionnaire, on crowdsourcing. The BF traits are indicators of personality and are said to be an effective predictor of study performance in various occupations. BF can be used in crowdsourcing to predict crowd workers’ performance; however, it will be difficult to use in practice for two reasons like the time-and-effort issue and the bias issue. In this study, an empirical analysis is conducted on crowdsourcing to examine if TIPI-J can solve those issues.

To investigate the issues, two tasks are posted on a crowdsourcing provider. Both TIPI-J and full version BF are conducted before and after selecting crowd workers. Structural validity and convergence validity are tested with correlation analysis between before (TIPI-J) and after (full version BF) data to examine the bias issue. Additionally, those correlations are compared with previous study and significances are examined.

The correlations in “conscientiousness” is 0.45-0.50, respectively, compared with a previous study, those two correlations did not show significance. This indicates that no clear bias exists.

This is the first research to investigate the efficacy of TIPI-J on crowdsourcing and showed that TIPI-J can be a useful tool for predicting crowd workers’ performance and thus it can help to select appropriate crowd workers.

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

The purpose of this study is to examine the moderating role of the characteristics of the chief executive officer (CEO) on the association between CEO power and corporate social responsibility (CSR) performance.

This paper conducts multiple regression analyses to empirically test the proposed hypotheses based on a sample of US-based publicly held companies. The sample period extends from 2000 to 2018. Firm-level CSR ratings are obtained from the Kinder, Lydenberg and Domini (KLD) database (currently known as MSCI ESG STATS). Financial data and CEO data are retrieved from Compustat and ExecuComp databases, respectively. Additional test and robustness analysis are performed.

This paper shows that firms with more powerful CEOs are less likely to engage in CSR activities. The negative association between CEO power and CSR is found to be exacerbated by CEOs who are younger, more competent and overconfident; however, this negative association is mitigated by CEOs who are female. This paper also finds that gender plays a more important role among CEO characteristics. Collectively, the findings highlight the potential opportunities to better understand the role of various CEO characteristics that jointly affect CSR.

First, this is the first study providing a comprehensive empirical analysis of how various CEO characteristics jointly affect CSR. Prior studies that focus on standalone CEO characteristics offer an incomplete picture of the relation between a single CEO characteristic and a firm's CSR performance. The current study thus extends the research field by examining the association between seemingly unrelated CEO characteristics and CSR performance. The results also highlight that gender is the critical factor moderating the relationship between CEO power and CSR performance when it is compared with CEO age, ability and overconfidence. Second, the authors add to the literature on employee selection by showing that female CEOs mitigate the negative effect of managerial power on CSR performance. Although the currently available empirical research in management control systems focuses on ex-post analyses of moral hazard mitigation for incumbent employees, both the economics and management literature acknowledge ex ante evidence suggesting that employee selection is even more important. Our findings may provide insight into the selection of CEOs.

The purpose of this paper is to highlight the opportunity for the energy policy in Brazil to tackle the very high cost-effectiveness potencial of solar energy to the power system. Three mechanisms to achieve ambitious reductions in the greenhouse gas emissions from the power sector by 2030 and 2040 are assessed wherein treated as solar targets under ambitious reductions in the greenhouse gas emissions from the power sector. Then, three mechanisms to achieve these selected solar targets are suggested.

This paper reviews current and future incentive mechanisms to promote solar energy. An integrated energy system optimization model shows the most cost-efficient deployment level. Incentive mechanisms can promote renewable sources, aiming to tackle climate change and ensuring energy security, while taking advantage of endogenous energy resources potential. Based on a literature review, as well as on the specific characteristics of the Brazilian power system, under restrictions for the expansion of hydroelectricity and ambitious limitation in the emissions of greenhouse gases from the power sector.

The potential unexploited of solar energy is huge but it needs the appropriate incentive mechanism to be deployed. These mechanisms would be more effective if they have a specific technological and temporal focus. The solar energy deployment in large scale is important to the mitigation of climate change.

The value of the research is twofold: estimations of the cost-effective potential of solar technologies, generated from an integrated optimization energy model, fully calibrated for the Brazilian power system, while tacking the increasing electricity demand, the expected reduction of greenhouse gas emissions and the need to increase the access to clean and affordable energy, up to 2040; proposals of three mechanisms to deploy centralized PV, distributed PV and solar thermal power, taking the best experiences in several countries and the recent Brazilian cases.

The purpose of this paper is the need to build a novel approach that would allow flexible modeling and solving of food supply chain management (FSCM) problems. The models developed would use the data (data-driven modeling) as early as possible at the modeling phase, which would lead to a better and more realistic representation of the problems being modeled.

An essential feature of the presented approach is its declarativeness. The use of a declarative approach that additionally includes constraint satisfaction problems and provides an opportunity of fast and easy modeling of constrains different in type and character. Implementation of the proposed approach was performed with the use of an original hybrid method in which constraint logic programming (CLP) and mathematical programming (MP) are integrated and transformation of a model is used as a presolving technique.

The proposed constraint-driven approach has proved to be extremely flexible and efficient. The findings obtained during part of experiments dedicated to efficiency were very interesting. The use of the constraint-driven approach has enabled finding a solution depending on the instance data up to 1,000 times faster than using the MP.

Due to the limited use of exact methods for NP-hard problems, the future study should be to integrate the CLP with environments other than the MP. It is also possible, e.g., with metaheuristics like genetic algorithms, ant colony optimization, etc.

There is a possibility of using the approach as a basis to build a decision support system for FSCM, simple integration with databases, enterprise resource planning systems, management information systems, etc.

The new constraint-driven approach to FSCM has been proposed. The proposed approach is an extension of the hybrid approach. Also, a new decision-making model of distribution and logistics for the food supply chain is built. A presolving technique for this model has been presented.

The purpose of this paper includes two interconnected objectives. The first is to provide a reconceptualisation of social value creation as social constraint alleviation. The second is to respond to the call put forward by Giuliani and Macchi (2014) to produce synergies between bodies of literature exploring the development impact of businesses. The paper focuses on ideas from the global value chain/global production networks (GVC/GPN), business and human rights, corporate social responsibility (CSR), international business (IB) and (social) entrepreneurship literatures.

The paper offers a reconceptualisation of social value creation by building on the synergies, complementarities and limitations of existing concepts identified through the literature review.

The reconceptualisation of social value creation put forward in this paper contributes to the literature in the following way. It offers a useful and clear definition of the term “social” (Devinney, 2009), and it attends to the limitations of the constraint concept as put forward by Ted London and his collaborators (London, 2011). Furthermore, it sketches out the basic ideas of a two-system approach to allow for the differentiation between symptom treatment and root cause alleviation. Finally, it offers a refinement of Wettstein’s (2012) proposed capability-based remedial action concept. The paper furthermore proposes that there are three distinct ways in which businesses generally respond to social constraints.

The paper illustrates how the redefined concept of social value creation can connect different bodies of literature and help make sense of existing empirical results, without engaging in definitional debates.