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Although service-learning increases several important development and learning outcomes in college students (Yorio & Ye, 2012), it is not clear whether service-learning is better preparing these students for their future careers (Gray, Ondaatje, Fricker, & Geschwind, 2000). To better understand the influence of service-learning on student development, an exploration of a leadership service-learning course and an important workplace attribute, Positive Psychological Capital, are theoretically explored.

The social change model of leadership (SCM) is a widely used leadership model in higher education. StrengthsQuest is conceptually similar to the individual values of the SCM in its aim to identify and grow individual talents. This model is based on the idea that individuals perform at higher levels when they build upon their identified talents (Clifton & Harter, 2003). Prior studies have not examined the relationship of hope or one’s belief in their identified StrengthsQuest talents to the individual values of the SCM. This study examines that relationship using the adult-trait hope and strengths self-efficacy scales. The relationship between these constructs along and other predictors of social change capacity were explored using canonical correlation analysis. Strengths self-efficacy, hope, and student engagement were statistically significant (73% of the variability among the individual values of the SCM). Gender, race, and community service were not statistically significant in this study.

Considering the substantial upcoming transfer of leadership to younger generations, it is critical to study the unique trait, skill, and behavioral associations of youth leaders. The purpose of this two-phase study was to quantitatively examine the relationship between positive psychological capacities (PsyCap), personality, and empathy with leadership skills in youth. Regression results from both phases revealed cognitive empathy and academic PsyCap as significant predictors of youth leadership life skills. These results follow earlier research that identified trait-based emotional intelligence as a significant predictor of leadership skills in youth. The combined results offer important considerations as leadership scholars and practitioners attempt to accurately predict and plan for the leadership transfer landscape over the next two decades. These combined results also serve as helpful considerations for youth leadership practitioners as program outcomes, learning objectives, and activities targeting the development of cognitive empathy and PsyCap will perhaps allow for more productive youth leadership development efforts and better documentation of their impact.

Combining the goal-setting and job demands-resources (JD-R) theories, we examine how two project resources, collaborative project leadership and financial project resources, enhance high project performance in community-academic health partnerships.

With a sequential explanatory mixed-method research design, data were collected through a survey (N = 318) and semi-structured interviews (N = 21). A hypothesised three-path mediation model was tested using structural equation modelling with bootstrapping. Qualitative data were examined using thematic analysis.

Project workers’ hope, goal-commitment and -stress: (1) fully mediate the hypothesised relationship between highly collaborative project leadership and high project performance; and (2) partially mediate the relationship between financial project resources and high project performance. The qualitative data corroborate and deepen these findings, revealing the crucial role of hope as a cognitive-motivational facilitator in project workers’ ability to cope with challenges.

Project leaders should promote project workers’ goal commitment, reduce their goal stress and boost project performance by securing financial project resources or reinforcing workers’ hope, e.g. by fostering collaborative project leadership.

The findings contribute to the project management and JD-R literature by considering the joint effects of project workers’ hope and two commonly studied project resources (collaborative project leadership and financial project resources) on high project performance. Moreover, we demonstrate the importance of the goal-setting and JD-R theories for understanding complex health-promotion projects connecting academic to community work.

This study aims to explore the influence of perceived hope, intrinsic spirituality and supervisor support on job involvement at the time of work from home during the COVID-19 pandemic.

The sample included 263 employees working from home (WFH) for the first time in their careers due to COVID-19. The authors applied structural equation model and multigroup analysis (MGA) in SmartPLS3 to examine the hypothesized relationships, and artificial neural network (ANN) analysis to determine the relative influence of the antecedents.

Results indicate that both personal (such as perceived hope and intrinsic spirituality) and job (supervisor support) resources determine job involvement during remote working, with a moderating impact of age on the relationship between intrinsic spirituality and job involvement. The ANN analysis shows that perceived hope is the most influential determinant of job involvement when employees work from home.

This study suggests that when employees work remotely, organizations can generate higher job involvement by conveying a higher perception of hope and spirituality and providing supervisor support through planned hope interventions, promoting prosocial behavior and making changes in leadership style (check on instead of check-in).

This study extends the job demands-resources (JD-R) model with new insights into the impact of personal and job resources on job involvement during the new normal remote working era.

The purpose of this research is to investigate how to introduce a financing scheme to tackle the manufacturer's capital constraint problem, discuss the effects of data-driven marketing (DDM) quality, cross-channel-return (CCR) rate and financing interest rate on the members' pricing and delivery-lead-time decisions and optimal performances, and analyzes `how to achieve the coordination within a dual-channel supply chain (DSC) by contract coordination.

This work establishes a DSC model with DDM, and the offline retailer can provide internal financing to the capital-constrained online manufacturer. The demand under the price is determined based on DDM quality, customer channel preference and delivery lead time. Then, combined with the Stackelberg game, the optimal pricing and delivery-lead-time decisions are discussed under the inconsistent and consistent pricing strategies with decentralized and centralized systems. Furthermore, it designs a manufacturer-revenue sharing contract to coordinate the members under the two pricing strategies.

(1) The increase of DDM quality will reduce the delivery-lead-time under the inconsistent or consistent pricing strategy and will push the selling prices; (2) The growth of the CCR rate will raise selling prices and extend the delivery-lead-time under the decentralized decision; (3) Under price competition, the offline selling price is higher than the online selling price when customers prefer the offline channel and vice versa; (4) The retailer and the manufacturer can achieve a win-win situation through a manufacturer-revenue sharing contract.

This paper contributes to the studies related to DSC by investigating pricing and delivery-lead-time decisions based on DDM, CCR, internal financing and supply chain contract and proposes some managerial implications.

The purpose of this paper is to investigate the design method of partial observer canonical form (POCF), which is one of the important research tools for industrial plants.

Motivated by the two-steps method proposed in Xu et al. (2020), this paper extends this method to the case of Multi-Input Multi-Output (MIMO) nonlinear system. It decomposes the original system into two subsystems by observable decomposition theorem first and then transforms the observable subsystem into OCF. Furthermore, the necessary and sufficient conditions for the existing of POCF are proved.

The proposed method has a wide range of applications including completely observable nonlinear system, noncompletely observable nonlinear system, autonomous nonlinear system and forced nonlinear system. Besides, comparing to the existing results (Saadi et al., 2016), the method requires less verified conditions.

The new method concerning design POCF has better plants compatibility and less validation conditions.

Given the limited studies that have started to focus on contexts where integrated reporting (IR) is voluntarily adopted, this paper aims to explore the moderating role of institutional characteristics on the association between voluntary report release and analyst forecast accuracy.

This study uses a quantitative empirical research method grounded on voluntary disclosure theory to provide empirical evidence on an international sample of companies choosing to release integrated reports. Preliminarily, a cluster analysis is used to group countries according to institutional patterns. Multivariate analyses detect the associations between report release choice and analysts’ forecast accuracy across clusters. Multiple econometric approaches are used to address the endogeneity concerns.

IR release is not informative for the market unless considering systematic variations across different institutional settings. Analysts’ forecast is more accurate for IR adopters located in strong institutional enforcement settings than for all the other companies. In the strong institutional setting that is also characterized by a pluralistic society, IR release benefits for the market are conditioned by the fact that the choice to release IR depends on environmental, governance and social disclosure-based managers remuneration and disclosure requirements. In weak institutional settings, IR release is not beneficial for the forecast accuracy.

Academics and practitioners can gain understanding of the usefulness of voluntary IR across different institutional settings.

The study advances the understanding of the IR’s informativeness, overcoming the common dichotomous distinctions between strong and weak institutional settings.

The purpose of this paper is to examine whether Fama–French common risk-factor portfolio investors herd on a daily basis for five developed markets, namely, Europe, Japan, Asia Pacific ex Japan, North America and Globe.

To examine the herd behavior of common risk-factor portfolio investors, this paper utilizes the cross-sectional absolute deviations (CSAD) methodology, covering a daily data sampling period of July 1990 to January 2019 from Kenneth R. French-Data Library. CSAD driven by fundamental and non-fundamental information is assessed using Fama–French five-factor model.

The results do not provide evidence for herding under normal market conditions, either when reacting to fundamental information or non-fundamental information, for any region under consideration. However, Fama–French common risk-factor portfolio investors mimic the underlying risk factors in returns related to size and book-to-market value, size and operating profitability, size and investment and size and momentum of the equity stocks in European and Japanese markets during crisis period. Also, no considerable evidence is found for herding (on fundamental information) under crisis and up-market conditions except for Japan. Ancillary findings are discussed under conclusion.

Further research on new risk factors explaining stock return variation may help improve the model performance. The performance can be improved by adding new risk factors that are free from behavioral bias but significant in explaining common stock return variation. Also, it is necessary to revisit the existing common risk factors in order to understand behavioral aspects that may affect cost of capital calculations (e.g. pricing errors) and valuation of investment portfolios.

This is the first paper that examines the herd behavior (fundamental and non-fundamental) of Fama–French common risk-factor investors using five-factor model.