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This study aims to investigate how to manage the stressors that facility managers (FMs) face with the aim of reducing their stress and strain levels.

Using the job demands-resources (JD-R) model, stressors are operationalized from job demands, job resources and personal resources constructs. A structured questionnaire was used to collect data from FMs based in Singapore.

FMs have significantly high levels of stress, but they are able to manage this well. Job demands that cause stress and strain are those relating to insufficient time to complete the work and difficulties in handling the work. The lack of job resources in terms of lack of organizational support and inadequate stress mitigation programs are associated with high levels of stress and strain.

The limitations are the relatively small sample size and absence of a database of FMs in Singapore, and correlation is not causation when determining the association between stressors and stress and strain.

Based on the recommendations, employers and FMs may manage the specific stressors identified so that FMs’ stress and strain levels are under control to enable them to work optimally.

This research discovered that the JD-R model is moderated by certain features of facilities management and FMs. When these features are present, FMs are predisposed to more stressors, and higher stress and strain. For the facilities management profession, the discovery is that there are significantly more job demands: for in-house FMs compared to those working for outsourced firms; for FMs who need to carry out estate and asset management, landlord activities and facility planning compared to FMs who focus on operations and maintenance; and for FMs who work longer than five days compared to those who work a five-day week.

As of now, the digitization of corporate finance presents a paradigm shift in business strategy, innovation, financing and managerial capability around the globe. However, the prevailing finance scholarly works hardly document the impact of the digitalization of corporate finance on firm performance with global evidence and analysis. Hence, the contemporary debate on whether firm performance is genuinely stimulated because of the digitalization of corporate finance or not has been a pressing issue in the relevant literature. Therefore, the purpose of this study is to identify a data-driven, concise response to an unaddressed finance issue if the performance of high-digitalized firms (HDFs) outperforms that of their counterpart peers for wealth maximization.

The first stage test models examine the firm performance of relatively high-digitalized firms as opposed to low-digitalized firms based on the system GMM. The second stage test of the probabilistic (logit) model infers that the probability of being HDFs explores because of better performance. Then, the authors execute robust checks based on the different quantile regressions and Z-score-based system GMM. In addition, the authors recheck and present the test results of the fixed effect and random effect to capture time-invariant individual heterogeneity. Finally, the supplementary test findings of firms’ credit strength by using Altman five- and four-factor Z-score models are presented.

By using cross-country panel analysis as 15 years’ test bed for HDFs and low digitalized firms (LDFs), the test results indicate that the overall firm performance of a digitalized firm is significantly better than that of a non-digitalized firm. The global evidence documents that HDFs are exposed to higher values and are financially more persistent as compared to their counterparts. The finding is remarkably concomitant across several possible subsample analysis, such as country–industry–size–period analysis.

This study can be remarkably effective in encouraging managers, policymakers and investors to acknowledge the need for adopting the required digitalization. Overall, this original study addresses a core research gap in the corporate finance literature and remarkably provides further direction to rethink the assumptions of firm digitalization on additive value and thereby identify optimal decisions for wealth maximization. The findings also imply that investors require an additional risk premium if they invest in relatively LDFs, which have relatively lower market value and weaker firm performance.

From an investors point of view, the academic novelty contributes to an innovative and unsettled issue on the impact of digitization of corporate finance on firm performance because there is a new question of high or low digitization of corporate finance in the global market. Hence, this academic novelty contributes to sharing global evidence of the digitalization of corporate finance and its effect on firm performances. In addition, an intensive critical review analysis is conducted based on the most recent and relevant scholarly works published in the top-tier journals of finance and business stream to fix the hypothesis. Overall, this study addresses a core research gap in the corporate finance literature; notably provides further direction to rethink firm digitalization; and thereby identifies optimal decisions for shareholders’ wealth maximization.

Recent studies have observed rise in consumer’s ethical concerns about the online retailers while making a purchase decision. The impetus for businesses to use corporate social responsibility (CSR) is evident, but the effects of CSR motives on corresponding processes underlying cause-related marketing (CRM) patronage intention have not been thoroughly examined. This study, anchored on attribution theory, established a research model that better explains the influence of CSR motives on patronage intentions toward CRM-oriented online retailers. Additionally, this study aims to examine the moderating role of spirituality (SPT) on CSR motives and CRM patronage intention (CPI).

Primary data has been collected from 722 respondents and analyzed by using deep neural-network architecture by using the innovative PLS-SEM-ANN method to predict/rank the factors impacting CPI.

The results revealed the normalized importance of the predictors of CPI and found that value-driven motive was the strongest predictor, followed by strategic motive, SPT, age and stakeholder-driven motive. In contrast, egoistic motive, education and income were found insignificant.

The pandemic has transformed the way consumers shop and fortified the online economy, thereby resulting in a paradigm shift toward usage of e-commerce platforms. The results offer valuable insights to online retailers and practitioners for predicting patronage intentions by CSR motives and, thus, effectively engage CRM consumers by designing promotions in a way that would deeply resonate with them. This study assessed and predicted the factors influencing the CPI s, thereby guiding the online retailers to design CSR strategies and manage crucial CRM decisions.

Employees play a vital role in the success of a corporation. While boards of directors are created to protect shareholders’ interests, it is unclear if these directors also ensure employee welfare. In this vein, our paper examines the relationship between board leadership structure and employee well-being.

The authors employ several analysis techniques, including univariate analysis, ordinary least squares (OLS) regressions, two-stage least squares (2SLS) regressions, propensity score matching methodology, the Heckman Selection model and difference-in-differences analysis. The sample comprises USA public firms for the period 1998–2018.

Our findings indicate that having an independent chairperson can significantly benefit the welfare of employees, especially for firms with overly powerful chief executive officers (CEOs) and during times of financial distress.

Independent leadership structure is one of the crucial board characteristics that have not been examined to explain employee welfare at firms. We find that an independent chairperson can mitigate the negative effect of overly powerful CEOs on employee benefits. Importantly, independent chairpersons are beneficial for employees in difficult times and when CEOs are busy with daily activities.

This paper aims to investigate the increasing trend of multigenerational co-living in the USA and to research the socioeconomic and cultural determinants of such decision.

This study uses the 2017 American Housing Survey data to run descriptive and regression analysis.

The authors find household income appears consistently to be the most significant factor determining multigenerational co-residence decision across all household compositions. Latino households are most likely to co-reside with multiple generations, followed by Asian and African American households. Immigrants tend to live in multigenerational co-residential housing units with smaller sizes and more impoverished neighborhoods, but show greater flexibility in making residential arrangements once they gain better education. In addition, older householders or female householders are significantly more likely to co-reside with multiple generations. Living in metropolitan areas has no impact on co-residence choice, although some evidence suggests that multigenerational co-residential families tend to live in inferior neighborhoods.

This study provides updated evidence on multigenerational co-residence choice in the contemporary United States. The findings provide evidence on how households make residential choices in response to financial hardships and contribute to the theoretical understanding of the variations of such decisions among immigrants and different ethnic and aging groups.

This study on multigenerational co-residence choice imposes important practical implications. The unprecedented COVID-19 pandemic creates ideal research setting to study how households cope with the tremendous uncertainties in the job markets and financial markets. Although multigenerational co-living may work well for some households with lower or moderate-income for financial reasons, it is not an attractive option for every family.

Sharing a home with multiple generations can be challenging. Policymakers should design policies and programs to provide households with guidance on how to live peacefully in multigenerational settings and make multigenerational co-living an appealing and cost-effective housing option for American families of all means.

This study contributes to the existing literature by providing new evidence on the determinants of multigenerational co-residence decision. This study’s findings are fundamental to guide policymakers in carrying out policies and programs aimed at providing a more appealing and cost-effective housing arrangement for American families. The evidence on the senior and minority subsamples are especially meaningful as the vast majority of the baby boom generation in the USA is aging and substantial growth is expected in multigenerational households over the next several decades. Understanding the increasing burden of old-age depression in aging societies will help policymakers prioritize public resources in city planning to address the needs of this rapidly growing population.

Although risk culture is a key determinant for an effective risk management, identifying the risk culture of a firm can be challenging due to the abstract concept of culture. This paper proposes a novel approach that uses unsupervised machine learning techniques to identify significant features needed to assess and differentiate between different forms of risk culture.

To convert the unstructured text in our sample of banks' 10K reports into structured data, a two-dimensional dictionary for text mining is built to capture risk culture characteristics and the bank's attitude towards the risk culture characteristics. A principal component analysis (PCA) reduction technique is applied to extract the significant features that define risk culture, before using a K-means unsupervised learning to cluster the reports into distinct risk culture groups.

The PCA identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining the risk culture of banks. Cluster analysis on the PCA factors proposes three distinct risk culture clusters: good, fair and poor. Consistent with regulatory expectations, a good or fair risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

The relationship between culture and risk management can be difficult to study given that it is hard to measure culture from traditional data sources that are messy and diverse. This study offers a better understanding of risk culture using an unsupervised machine learning approach.

Drawing on social exchange literature, this study explores the mediating role of affective commitment between employees' assessments of contract breaches and opportunistic silence, along with the invigorating effect of hostile attribution bias.

We tested the hypotheses using multi-wave data collected from employees working in higher education institutions in Pakistan.

Perceived contract breaches elicit intentional, selfish and retaliatory motives of silence, largely because employees lack emotional attachments to their organization. This mechanism is more prominent among employees who tend to blame others and perceive them as antagonistic even when they are not.

For human resource managers, this investigation highlights a crucial feature – affective commitment – by which employees' perceptions of psychological contract breaches facilitate opportunistic silence. Our results suggest that this process is more likely to intensify when employees have distorted thinking, motivating them to attribute the worst motives to their employer's actions.

Perceived contract breaches within universities can have far-reaching societal consequences, affecting trust, reputation, economic stability, and the overall quality and accessibility of education and research. Addressing and preventing such breaches is essential to maintaining the positive societal role of universities.

This study provides novel insights into the process that underlies the connection between perceived contract breach and opportunistic silence by revealing the hitherto overlooked role of employees' hostile attribution bias, which renders them more susceptible to experiencing unfavorable forms of social exchange.