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Research related to workplace accommodation requests for employees with mental illness is scarce, though evidence suggests that these individuals often fail to request accommodations even when needed. The authors' research study aimed to address these shortcomings by (1) assessing employees' knowledge of Americans with Disabilities Act (ADA) laws and how this knowledge influences employees' perceived need for and requests of accommodations; (2) examining the relationship between employees' perceived need for accommodations and employees' workplace outcomes and (3) examining the relationship between perceived need for accommodations and employees' actual accommodation requests, as well as how stigma influences this relationship.

The authors used two survey studies to investigate their research questions. Study 1 participants were recruited through Amazon's MTurk, and Study 2 participants were recruited through support groups for individuals diagnosed with mood disorders (i.e. depression and bipolar disorder).

The authors found significant gaps in both subjective and objective ADA-related knowledge among participants in their sample. The authors' Study 1 results also revealed an interaction between the perceived need for accommodations and accommodation requests in predicting job satisfaction and turnover intentions. When employees needed accommodations but did not request them, it resulted in worsened workplace outcomes. In Study 2, the authors aimed to identify barriers to requesting accommodations. The authors found that the relationship between perceived need for accommodations and actual accommodation requests was moderated by both public and self-stigma, thereby showing that stigma can impede individuals from requesting needed accommodations at work.

The authors' study sheds light on a population that has been relatively understudied in the workplace accommodations literature, namely those with mental illness. The authors first identify the perceived need for accommodations as an important factor in making accommodations requests at work, as prior work has failed to differentiate how the need for accommodations can vary across individuals. Next, the authors show how workplace outcomes (i.e. job satisfaction and turnover intentions) are negatively affected when employees need accommodations but do not request them. Finally, the authors demonstrate how both public stigma and self-stigma can reduce the likelihood that individuals request accommodations at work, even when needed.

This study aims to delve into the varying impacts of different types of emotions conveyed through retailers' review request texts on consumers' intention to write a review.

To verify the relationships between these variables, two laboratory experiments were conducted in this study.

The findings indicate that when accompanied by an objective statement, texts that evoke empathy and favor have a positive influence on consumers' inclination to write a review. Moreover, by examining the underlying mechanism, this study uncovers two interconnected mediators, namely persuasive intent and cognitive (affective) resistance, along with empathy and helping intention. Additionally, the study explores the moderating role of customer satisfaction with the product, shedding light on the contextual factors that influence the effects of emotional cues in review texts.

This research contributes to the literature and practice by focusing on the process of retailers' generating online reviews. This is one of the first studies to systematically examine the effects of emotional text in retailers' review request on consumers' reviewing intention from the perspective of emotional evocation. The experimental findings and the underlying mechanisms emphasize the impact of different types of emotions in retailers' review requests texts on consumers' reviewing intentions. It can help retailers better understand the psychological reactions of consumers when they ask reviews, which provide theoretical support for retailers to design more reasonable asking texts.

This study assessed two technology systems aimed at enabling a man with intellectual disability, blindness, deafness and motor and tactile discrimination problems to make verbal requests through simple one-hand signs.

The study was conducted according to an ABAB design. During the B (intervention) phases, the man used the two systems, which included (1) nine mini recording devices fixed on the man’s clothes or wheelchair (i.e. in positions the man touched with his sign movements) and (2) nine tags with radio frequency identification codes (fixed at approximately the same positions as the mini recording devices) and a dedicated tag reader, respectively. Making a sign (i.e. touching a recording device or reaching a tag) led to the verbalization of the request related to that sign.

During baseline, the mean frequency of signs/requests made was below 2 per session, and only some of those requests were identified/satisfied. During the intervention, the mean frequency of requests made and satisfied was about 10 per session with each of the systems.

The results, which are to be taken with caution given the preliminary nature of the study, seem to suggest that the systems can help translate simple signs into verbal requests.

The global cooperation and cooperation between nations at differing stages in anti-money laundering (AML) is critical. To improve the effectiveness of international cooperation in AML, it is essential to diversify international cooperation mechanisms and improve the capacity of law enforcement officers in the field of preventing this crime. This paper aims to provide a comparative analysis of mutual legal assistance (MLA) and extradition within the AML legal framework in Palestine and Malaysia. It investigates the gaps and weaknesses in Palestine’s AML legal framework and offers recommendations to address them.

The present paper is solely legal. The method adopted in this research paper is qualitative research with an emphasis on the doctrinal mechanism. As a result, it concentrates on procedures, protocols, legislation and policies.

The Malaysian AML legal framework offers a clearer and more comprehensive framework for MLAs and extradition than the Palestinian AML legal framework. This framework is supported by laws that meet the basic requirements to support the issues of AML international cooperation. Both countries agree that the absence of a “bilateral or multilateral agreement” is not considered a reason for rejecting international cooperation in the field of AML with foreign countries. Moreover, the Malaysian AML legal framework divides the roles well between the law enforcement agencies and the competent authorities competing to Palestine.

This paper would be beneficial for the Palestinian legislative, policymakers and law enforcement agencies to make international cooperation, especially with MLAs and extradition effective.

There is a growing trend among online merchants to conduct help-request marketing campaigns (HMCs), which refers to a kind of marketing campaign that leverages participants' help-request to encourage the subsequent engagement of participants' online friends. The paper aims to investigate how individuals respond to online HMCs in social networking groups (SNGs). Integrating the norm activation model and regulatory focus theory, this paper examines the mediation effects of the two facets of responsibility perception, i.e. perceived causality and perceived answerability.

A field experiment was conducted by organizing a real HMC on WeChat. To manipulate request individuation, experimental confederates were engaged to serve as requesters in the HMC. The actual responses provided by the recipients (subjects) were captured via the HMC pages. The multiple-group analysis was used for data analysis.

Empirical results reveal that request individuation strengthens the effect of relationship closeness on perceived causality but reverses the effect of relationship closeness on perceived answerability from being positive to negative. Except for the negligible impact of perceived answerability on inaction, both perceived causality and perceived answerability affect recipients' reactions to HMCs as expected.

First, social media platforms should promote other-oriented prosocial values when designing features or launching campaigns. Second, the designers of HMCs should introduce a “tagging” feature in HMCs and provide additional bonuses for requesters who perform tagging. Third, HMC requesters should prudently select tagging targets when making a request.

First, this paper contributes to the literature on social media engagement by identifying responsibility as an other-oriented motivation for individuals' social media engagement. Second, this paper also extends our understanding of responsibility by dividing it into perceived causality and answerability as well as measuring them with self-developed instruments. Third, this study contributes to the research on WOM by demonstrating that individuals' response behaviors toward help-requests embedded in HMCs can take the form of proactive helping, reactive helping or inaction.

The purpose of this paper is to understand how individuals seek to reduce the occurrence of unethical requests at work and the effects of such strategies.

The authors built a grounded theory through semi-structured interviews with 65 individuals who worked for companies involved in the Brazilian corruption scandal called Operation Car Wash.

The interviewees reported that they use two central strategies to avoid unethical requests: explicit moral communication (directly stating that they are not willing to adhere to an unethical request) and implicit communication (expressing such a refusal through moral symbols). Both strategies signal the morality of the communicator and lead the possible proponent of an unethical request to perceive a greater probability of being reported and, thus, avoid making such an unethical request. However, while explicit moral communication affects the perceived morality of the individual who would possibly make an unethical request, implicit (symbolic) moral communication does not. As a consequence, the risks of retaliation for making a moral communication are greater in the case of explicit moral communication, entailing that implicit moral communication is more effective and safer for the individual who wants to avoid unethical requests.

This paper broadens the literature on business ethics and moral psychology by shifting its focus from what organizations and leaders can do to prevent unethical behavior to what leaders can actively do to protect themselves from unethical requests.

This study examines shareholder and board motivations regarding corporate social responsibility (CSR) to understand boards' stewardship approaches to environmental issues.

Using content analysis, the authors classify CSR motivations in all environmental shareholder proposals and board responses of Fortune 250 companies from 2013 to 2017 from do little (a shareholder primacy perspective) to do much (a stakeholder pluralism perspective). The authors calculate the motivational dissonance for each proposal-response pair (the Talk Gap) and use cluster analysis to observe evidence of board stewardship and subsequent environmental disclosure and performance (ED&P) changes.

Board interpretations of stewardship are not uniform, and they regularly extend to stakeholders beyond shareholders, most frequently including profit-oriented stakeholders (e.g. employees and customers). ED&P changes are highest when shareholders narrowly lead boards in CSR motivation and either request both action and information or information only. The authors observe weaker ED&P changes when shareholders request action and the dissonance between shareholders and boards is larger. When shareholders are motivated to do little for CSR, ED&P changes are weak, even when boards express more pluralistic motivations.

The results show the important role that boards play in CSR and may aid activist shareholders in determining how best to generate change in corporate CSR actions.

This study provides the first evidence of board stewardship at the proposal-response level. It measures shareholder and board CSR motivations, introduces the Talk Gap, and examines relationships among proposal characteristics, the Talk Gap, and subsequent ED&P change to better understand board stewardship of environmental issues.

This paper aims to develop predictive methods, based on recurrent neural networks, useful to support facility managers in building maintenance tasks, by collecting information coming from a computerized maintenance management system (CMMS).

This study applies data-driven and text-mining approaches to a CMMS data set comprising more than 14,500 end-users’ requests for corrective maintenance actions, collected over 14 months. Unidirectional long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM) recurrent neural networks are trained to predict the priority of each maintenance request and the related technical staff assignment. The data set is also used to depict an overview of corrective maintenance needs and related performances and to verify the most relevant elements in the building and how the current facility management (FM) relates to the requests.

The study shows that LSTM and Bi-LSTM recurrent neural networks can properly recognize the words contained in the requests, thus correctly and automatically assigning the priority and predicting the technical staff to assign for each end-user’s maintenance request. The obtained global accuracy is very high, reaching 93.3% for priority identification and 96.7% for technical staff assignment. Results also show the main critical building elements for maintenance requests and the related intervention timings.

This work shows that LSTM and Bi-LSTM recurrent neural networks can automate the assignment process of end-users’ maintenance requests if trained with historical CMMS data. Results are promising; however, the trained LSTM and Bi-LSTM RNN can be applied only to different hospitals adopting similar categorization.

The data-driven and text-mining approaches can be integrated into the CMMS to support corrective maintenance management by facilities management contractors, i.e. to properly and timely identify the actions to be carried out and the technical staff to assign.

The improvement of the maintenance of the health-care system is a key component of improving health service delivery. This work shows how to reduce health-care service interruptions due to maintenance needs through machine learning methods.

This study develops original methods and tools easily integrable into IT workflow systems (i.e. CMMS) in the FM field.

Facilities management (FM) plays a key role in the performance of businesses to ensure the comfort of users and the sustainable use of natural resources over operation and maintenance. Nevertheless, reactive maintenance (RM) services are characterised by delays, waste and difficulties in prioritising services and identifying the root causes of failures; this is mostly caused by inefficient asset information and communication management. While linking building information modelling and the Internet of Things through a digital twin has demonstrated potential for improving FM practices, there is a lack of evidence regarding the process requirements involved in their implementation. This paper aims to address this challenge, as it is the first to statistically characterise RM services and processes to identify the most critical RM problems and scenarios for digital twin implementation. The statistical data analytics approach also constitutes a novel practical approach for a holistic analysis of RM occurrences.

The research strategy was based on multiple case studies, which adopted university campuses as objects for investigation. A detailed literature review of work to date and documental analysis assisted in generating data on the FM sector and RM services, where qualitative and statistical analyses were applied to approximately 300,000 individual work requests.

The work provides substantial evidence of a series of patterns across both cases that were not evidenced prior to this study: a concentration of requests within main campuses; a balanced distribution of requests per building, mechanical and electrical service categories; a predominance of low priority level services; a low rate of compliance in attending priority services; a cumulative impact on the overall picture of five problem subcategories (i.e. Building-Door, Mechanical-Plumbing, Electrical-Lighting, Mechanical-Heat/Cool/Ventilation and Electrical-Power); a predominance of problems in student accommodation facilities, circulations and offices; and a concentration of requests related to unlisted buildings. These new patterns form the basis for business cases where maintenance services and FM sectors can benefit from digital twins. It also provides a new methodological approach for assessing the impact of RM on businesses.

The findings provide new insights for owners and FM staff in determining the criticality of RM services, justifying investments and planning the digital transformation of services for a smarter provision.

This study represents a unique approach to FM and provides detailed evidence to identify novel RM patterns of critical service provision and activities within organisations for efficient digitalised data management over a building’s lifecycle.

Following the COVID-19 outbreak, there are concerns whether economies are becoming farther from equality and competency. While this matters to every economy, it is more crucial for developing ones who already suffer from income inequalities and lack of competency. The purpose of this paper is to address this issue.

This study uses an administrative data from the Iran's Social Security Organization (ISSO) that provides insurance to workers entitled to the Labor Law of Iran. The data contain more than 7,000,000 workers. The authors assess heterogeneous impact of the first wave of the pandemic by firms' size and average payment.

The authors’ estimation results indicate that, following the initiation of the pandemic, the workers whose corresponding firms are smaller, overall, are more prone to the pandemic and are more likely to submit a request for unemployment benefits. However, the relation is neither homogeneous across sectors nor linear among micro-sized firms. Few sectors indicate a positive relationship between size and likelihood of request submission, including cultural activity, shoemaking and clothing sectors. Besides the size, the authors investigate whether pay grades could explain the probability of becoming unemployed after the pandemic. Results show that workers whose corresponding firms pay less are more likely to submit a request. This is robust within different sectors.

The ISSO dataset is not a panel, so the authors cannot employ methods of causal inferences. The authors’ results should be seen as correlation; however, due to exogeneity and sharpness of the pandemic the result infers to some degree of causality. The data does not cover the informal sector, so the estimates are at lower boundary.

Administrative data on unemployment benefits during COVID-19 show that the pandemic interferes with competition by forcing low-paid workers and small firms to exit the market. This is an alarm for the competition in every economy, specially developing ones.