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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.

This paper explores how digitalization affects the academic research publication process by taking into account the perspective of management scholars. It provides an overview of the digital professional services dedicated to academic research, and investigates academics' awareness of, the impact on the publication process of, and scholars' expectations regarding digital services and software.

This explorative study adopted a qualitative approach by performing direct observations of websites regarding digital professional research services and in-depth interviews with national and international management scholars.

The multiple digital professional services dedicated to academic research enable authors to develop a scientific paper independently or with the support of professionals. The scholars' awareness regarding the digital services and software was limited, because of both the plethora of options on the market and the frequent use of the same digital tools over time. In impact terms, these tools enable scholars to improve research quality and to increase productivity. However, the negative effects led scholars to express different expectations about how they can be improved and what difficulties should be overcome to favor the publication process.

The results of this study provide suggestions both for scholars who engage in academic research and digital services and software providers.

To the best of the authors' knowledge, this is the first study to examine the ongoing development of digitalization in support of the research publication process from the perspective of academics.

Water is a critical and contentious resource in California, hence any changes in reservoir management requires coordination among many basin stakeholders. The Forecast-Informed Reservoir Operations (FIRO) pilot project at Lake Mendocino, California explored the viability of using weather forecasts to alter the operations of a United States Army Corps of Engineers (USACE) reservoir. The pilot project demonstrated FIRO's ability to improve water supply reliability, but also revealed the key role of a collaborative Steering Committee. Because Lake Mendocino's Viability Assessment did not explore the features of the Steering Committee, this study aims to examine the relationships and interactions between Steering Committee members that supported FIRO's implementation at Lake Mendocino.

The project identified 17 key project participants who spoke at a FIRO workshop or emerged through chain-referrals. Using semi-structured interviews with these participants, the project examined the dynamics of human interactions that enabled the successful multi-institutional and multi-criteria innovation as analyzed through text-coding.

The results reveal the importance for FIRO Steering Committee members to understand the limitations and constraints of stakeholder counterparts at other organizations, the importance of building and safeguarding relationships, and the role of trust and belonging between members. The lessons learned suggest several interventions to support successful group collaboration dynamics for future FIRO projects.

This study identifies features of the Steering Committee that contributed to FIRO's success by supporting collaborative negotiations of infrastructure operations within a multi-institutional and multi-criteria context.

The hospitality and tourism industry faces a number of workforce challenges, especially the high turnover rates and associated replacement costs associated with continually identifying and hiring new employees. The purpose of this paper is to discuss how hospitality and tourism organizations can use electronic human resource management (eHRM) and artificial intelligence (AI) to help recruit and select qualified employees, increase individual retention rates and decrease the time needed to replace employees. Specifically, it discusses how e-recruiting and e-selection and AI tools can help hospitality and tourism organizations improve recruiting and selection outcomes.

Research on eHRM, AI, employee recruitment and employee selection are applied to the hospitality and tourism industry and insights for how eHRM and AI can be applied to the industry are discussed.

eHRM and AI have the potential to transform how the hospitality and tourism industry recruit and select employees. However, care must be taken to ensure that the insights gained and the decisions made are well received by employees and lead to better employee and organizational outcomes.

This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry.

This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry.

This article examines why Universal Primary Education (UPE) has shifted from being a developing country challenge more broadly in the last half of the 20th century to become largely a sub-Saharan Africa (SSA) challenge today. It discusses a number of national and education sector system-wide challenges that have constrained the implementation of UPE in SSA more so than in other developing regions.

This article reviews the literature and policy documents on a wide range of developing country issues, and discusses why most SSA countries have faced unparalleled challenges in achieving UPE.

SSA governments should take the opportunity offered by their post-pandemic “build back better” efforts to fundamentally reset education policies to address the key causes of this major development failure. The overarching objective must be to develop education systems that are more inclusive, equitable and responsive to national development needs by better serving the large population groups, parts of society and economic sectors that currently derive little benefit from public education spending. This article highlights the urgency and challenges associated with achieving this objective.

Although the main responsibility lies with SSA governments, this paper stresses that the global community will be affected in many ways by how effectively this crisis is addressed. Therefore, this effort merits sustained global support including through more catalytic use of aid.

The purpose of this systematic review is to highlight some of the business model changes restaurants, bars and beverage producers undertook to modify their operations in order to not only stay in business but also to better serve their employees and communities during the COVID-19 crisis.

An analysis was conducted on 200 industry articles and categorized into three major themes: expansion of take-out/delivery, innovative practices, and community outreach/corporate support, each are further subdivided into additional themes. The systematic review is further supported by personal interviews with industry professionals.

This research finds that there were many different approaches used in adjusting business models in response to the dining restrictions put in place due to COVID-19. From these approaches, themes were developed which resulted in uncovering some suggestions such as developing contingency plans, being flexible and creative, eliminating menu items, investing in a communication platform and getting involved with local government. In addition, some practices operators should be mindful of such as selling gift cards and starting a crowdfund.

This research provides a systematic analysis of business model changes that occurred due to COVID-19 dining restrictions. Researchers can use this information as a guide for further analysis on a specific theme introduced herein.

This research offers several practical implications which will assist the industry should another similar event occur in the future. The systematic analysis describes and documents some suggestions as well as practices to be mindful of in preparing contingency plans for the future.

This research documents an unprecedented time for the hospitality industry by examining how restaurant, bar and beverage producers around the country responded to COVID-19 restrictions. Distilling the multitude of information into succinct themes that highlight the business model changes that occurred will aid future research as well as operators.

This paper investigates the integration of leadership training into IT curricula to develop current and future skills needed by the IT job market. The technical and non-technical skills required for IT professionals are presented and a conceptual model for including leadership training in technical courses is outlined. To implement this model, we adopted the Problem-Based Learning approach to teach an IT course. Qualitative and quantitative data were gathered, through a survey, from 52 undergraduate students in the College of Information Technology at Zayed University. Our results show that our adopted approach was successful in teaching IT skills as well as developing leadership skills. Given these findings, we highlight the importance and feasibility of integrating leadership development on a daily basis within technical courses to develop both the technical and non technical skills required by the job market.

This study aims to integrate social identity and leader–member exchange (LMX) theory to investigate the processes and boundary conditions around LMX–performance relationships. Through the application of two leader–follower subsamples, the authors test three main objectives. What is the effect of multi-dimensional dyad value-congruence on LMX and how does congruence on these dimensions differentially influence leader and follower perceptions of LMX? In a subsample of followers including supervisor-rated performance, the authors develop a model that examines how individual values moderate the effect of dyad contact on supervisor-rated job performance mediated by follower LMX.

The participants for this study include graduate and undergraduate social work students who were taking part in a one-year work placement within a social work organization as well as their immediate supervisors. Across a four-month period, participants filled out measures of their supervisor contact, work values and LMX. Supervisor-rated performance was also included.

Findings from the dyadic subsample show that growth value congruence is a predictor of follower-rated LMX, with value congruence across all values having no effect on leader-rated LMX. Within a subsample of followers, findings suggest that follower-rated LMX mediates the relationship between dyad contact and supervisor-rated job performance, with individual work values moderating this effect.

The current study offers several contributions to the literature on LMX and job performance. First, in this study’s dyadic leader–follower sample, the authors extend propositions made by social identity theory around value congruence and LMX by offering support for a multi-dimensional and multi-target approach to questions of values and LMX. Second, within this study’s larger non-dyadic sample, the authors offer insights into previous conflicting findings around dyad contact and LMX, by offering support for the indirect effect of dyad contact on supervisor-rated performance via LMX. Third, within this second sample, the authors also extend the literature on values and LMX to show that the process through which LMX influences job performance is dependent on follower values.

Movies have mesmerized audiences for years, crossing boundaries of race, gender, age, culture, and nationality. They have also been used to teach people how to lead. One text that zeroes in on the essence of leadership is The Leadership Challenge, by Kouzes and Posner (2002). Through their research, they have highlighted five practices of effective leaders. It is our intent to share how we apply movies to teach the tenets of the groundbreaking leadership research of Kouzes and Posner, with proven ideas that work with students of leadership in any setting.

Using movies to teach leadership is a winning strategy; however, diligent planning is required to incorporate them successfully into leadership education. Movies are entertaining, informative, energizing, and educational, if used skillfully. The more facilitators use film, the more skilled they will become and the more the participants will benefit.