Search results

Previous studies have mainly focused on the negative impact of illegitimate tasks on recipients but ignored its impact on observers. Drawing on deservingness theory, this research developed a moderated serial mediation model to examine the underlying mechanism in the relationship between observed illegitimate tasks and observers’ helping behaviour.

This research tested the model using a sample of 218 employees in China through a two-wave field study. A path analysis was conducted with the bootstrapping procedure to test the hypothesized model.

The results showed that the effect of observing illegitimate tasks was contingent upon the degree of the observer’s interpersonal liking towards the recipient. Specifically, when the observer had a high level of interpersonal liking for a coworker, the observer may perceive that the coworker was undeserving of being assigned illegitimate tasks, which increased sympathetic emotion and the sequent helping behaviour.

This study shifted the perspective of the illegitimate task literature from the recipient to the third parties. Additionally, it provided a finer-grained understanding of the mechanism between observed workplace disrespectful treatment and the observer’s helping behaviour.

The debate surrounding the influence of parental nutritional knowledge on offspring’s susceptibility to overweight/obesity persists, with a dearth of research elucidating the mechanisms involved. This study aims to explore if and how parental nutrition knowledge affects adolescents' overweight and obesity, by highlighting the mediating effect of parental perceived severity of obesity.

A questionnaire was conducted in Zhejiang Province, China, with a sample of 2,298 students as well as their parents during November–December 2022. Logistic regression and propensity score matching methods was used to validate the relationship between parental nutrition knowledge and adolescents' overweight/obesity, while the multiplication coefficient method was used to test the mediation effect.

Parental nutrition knowledge significantly reduces the odds ratio for adolescent obesity, without affecting the likelihood of overweight. The perceived severity of obesity fully mediates the relationship between parental nutrition knowledge and adolescents' overweight and obesity.

By exploring mediating factors, the analysis offers an innovative explanation of the process by which nutritional knowledge influences health behaviors. Lack of relevant motivation or beliefs is an important reason for the failure of nutritional knowledge. If parents do not have sufficient awareness of the dangers of overweight or obesity, they will have inadequate motivation to apply nutritional knowledge in guiding dietary or exercise decisions. We also supplement the literature by demonstrating the health belief model in highlighting the mediating mechanism of perceived severity in the relationship between parental nutrition knowledge and adolescents' obesity.

Extending the research focus on subjective beliefs and cognitive motivation bears important policy implications for designing education campaigns to effectively restrain the obesity rate. Considering that many Chinese parents have insufficient awareness of the dangers of childhood overweight and obesity, even considering “chubby children” as symbols of “cuteness” and “health”. This can largely undermine their motivation to apply nutritional knowledge to restrain adolescents' overweight and obesity. Consequently, education campaigns, public health professionals and government agencies can be developed aiming to increase parental nutrition knowledge, especially on the hazards of obesity.

With the prevalence of overweight and obesity among adolescents, it is critical to control students' weight and health. Families, especially parents, are vital to the physical and mental health of adolescents. This research confirmed that improving parental nutrition knowledge is necessary for maintaining a healthy weight for adolescents. Results also emphasized that the association between parental nutritional knowledge and adolescents' overweight or obesity was mediated by parental perceived severity. This indicates that interventions designed to enhance parental nutritional knowledge should pay more attention to strengthening parental cognition of and beliefs in obesity.

This paper added to the debate on the impact of parental nutritional knowledge on adolescent’s overweight and obesity. Based on the health belief model, it also identified a novel pathway and mechanism by highlighting the importance of subjective motivations and beliefs such as the perceived severity of obesity in influencing overweight/obesity. Conclusions bear important policy implications for designing education campaigns to effectively restrain the obesity rate.

Building on the core concept of anthropomorphism and the empathy-helping theory, this research aims to examine how product anthropomorphism and buyer usage intentions affect sellers’ pricing in second-hand markets as well as explore the psychological dynamics underlying these effects.

To test the hypotheses, a series of four experiments were conducted. Studies 1a (n = 140) and 1b (n = 140) employed a one-factor (product anthropomorphism: yes vs no) between-subject design and used chi-square analysis. Study 2 (n = 145) and Study 3 (n = 162) employed a 2 (usage intention: protective vs destructive) × 2 (product anthropomorphism: yes vs no) between-subject design and used two-way ANOVA and moderated mediation analysis.

The study found that even when potential buyers with destructive (vs protective) usage intentions offer higher prices, sellers of anthropomorphized (vs non-anthropomorphized) products are less willing to choose them (Studies 1a and 1b). When potential buyers express destructive (vs protective) usage intentions, sellers of anthropomorphized (vs non-anthropomorphized) products are less willing to offer discounts (Study 2), and the lowest price they are willing to accept is higher (Study 3). The level of perceived capacity for pain mediates these effects (Study 3).

These findings offer insights into the application of product anthropomorphism strategies and the second-hand transactions of used anthropomorphized products.

Mechanoreception is crucial for robotic planning and control applications, and for robotic fingers, mechanoreception is generally obtained through tactile sensors. As a new type of robotic finger, the soft finger also requires mechanoreception, like contact force and object stiffness. Unlike rigid fingers, soft fingers have elastic structures, meaning there is a connection between force and deformation of the soft fingers. It allows soft fingers to achieve mechanoreception without using tactile sensors. This study aims to provide a mechanoreception sensing scheme of the soft finger without any tactile sensors.

This research uses bending sensors to measure the actual bending state under force and calculates the virtual bending state under assumed no-load conditions using pressure sensors and statics model. The difference between the virtual and actual finger states is the finger deformation under load, and its product with the finger stiffness can be used to calculate the contact force. There are distinctions between the virtual and actual finger state change rates in the pressing process. The difference caused by the stiffness of different objects is different, which can be used to identify the object stiffness.

Contact force perception can achieve a detection accuracy of 0.117 N root mean square error within the range of 0–6 N contact force. The contact object stiffness perception has a detection average deviation of about 15%, and the detection standard deviation is 10% for low-stiffness objects and 20% for high-stiffness objects. It performs better at detecting the stiffness of low-stiffness objects, which is consistent with the sensory ability of human fingers.

This paper proposes a universal mechanoreception method for soft fingers that only uses indispensable bending and pressure sensors without tactile sensors. It helps to reduce the hardware complexity of soft robots. Meanwhile, the soft finger no longer needs to deploy the tactile sensor at the fingertip, which can benefit the optimization design of the fingertip structure without considering the complex sensor installation. On the other hand, this approach is no longer confined to adding components needed. It can fully use the soft robot body’s physical elasticity to convert sensor signals. Essentially, It treats the soft actuators as soft sensors.

The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production planning problem when a manufacturer can observe historical demand data with high-dimensional mixed-frequency features, which provides fine-grained information.

In this study, a two-step data-driven optimization model is proposed to examine production planning with the exploitation of mixed-frequency demand data is proposed. First, an Unrestricted MIxed DAta Sampling approach is proposed, which imposes Group LASSO Penalty (GP-U-MIDAS). The use of high frequency of massive demand information is analytically justified to significantly improve the predictive ability without sacrificing goodness-of-fit. Then, integrated with the GP-U-MIDAS approach, the authors develop a multiperiod production planning model with a rolling cycle. The performance is evaluated by forecasting outcomes, production planning decisions, service levels and total cost.

Numerical results show that the key variables influencing market demand can be completely recognized through the GP-U-MIDAS approach; in particular, the selected accuracy of crucial features exceeds 92%. Furthermore, the proposed approach performs well regarding both in-sample fitting and out-of-sample forecasting throughout most of the horizons. Taking the total cost and service level obtained under the actual demand as the benchmark, the mean values of both the service level and total cost differences are reduced. The mean deviations of the service level and total cost are reduced to less than 2.4%. This indicates that when faced with fluctuating demand, the manufacturer can adopt the proposed model to effectively manage total costs and experience an enhanced service level.

Compared with previous studies, the authors develop a two-step data-driven optimization model by directly incorporating a potentially large number of features; the model can help manufacturers effectively identify the key features of market demand, improve the accuracy of demand estimations and make informed production decisions. Moreover, demand forecasting and optimal production decisions behave robustly with shifting demand and different cost structures, which can provide manufacturers an excellent method for solving production planning problems under demand uncertainty.

We examine whether the social capital of the area where a firm’s headquarters is located affects that firm’s credit rating. Given that credit rating agencies only infrequently visit a firm’s headquarters, it is pertinent to investigate whether this soft information is considered.

In order to test whether social capital affects firms’ credit ratings, we estimate the following model using an ordinary least squares regression: Rating_it = β₀ + β₁ Social Capital_it + ∑ Controls_it + Industry fixed Effects_i + State−year fixed effects_it + ε_it. We follow recent accounting and finance research and measure societal-level social capital at the county level (Jha & Chen, 2015; Cheng et al., 2017; Hasan et al., 2017a, b; Jha, 2017; Hossain et al., 2023). We use four inputs to calculate social capital: (1) voter turnout in presidential elections, (2) the census response rate, (3) the number of social and civic associations and (4) the number of nongovernmental organizations in each county.

W provide evidence that social capital has a causal effect on credit ratings. Interesting is that this effect is not merely localized to firms near credit rating agencies. We also find that the effect of social capital on credit ratings is concentrated among firms with moderate levels of default risk. For firms with extremely low or extremely high default risk, social capital appears irrelevant to credit ratings, suggesting that social capital plays a larger role in more ambiguous contexts or when greater judgment is required. We demonstrate that the effect of social capital on credit ratings disappears when the rating agency has extensive experience in a particular region. This result is consistent with rating agencies stereotyping certain regions of the USA and using that information to inform their ratings when they have less experience in the region. Finally, we find that while social capital is associated with credit ratings, it has no association with future defaults.

Though we cautiously followed prior studies and were confident in our data construction process, it is possible that we are measuring social capital with error.

Our findings suggest that credit rating agencies could benefit from reevaluating how they incorporate non-financial information, such as social capital, into their assessment processes, potentially leading to more nuanced and equitable credit ratings. Additionally, firms could use these insights to bolster their engagement with local communities and stakeholders, thereby enhancing their creditworthiness and attractiveness to investors as part of a broader corporate strategy. The findings also underline the need for regulatory frameworks that foster transparency and the inclusion of social factors in credit evaluations, which could lead to more comprehensive and fair financial reporting and rating systems.

Recognizing that social capital can influence economic outcomes like credit ratings may encourage both communities and firms to invest more in building and maintaining social networks, trust and civic engagement. By demonstrating how social capital impacts credit ratings, our research highlights the potential to address inequalities faced by regions with lower social capital, guiding targeted social and economic development initiatives. Moreover, understanding that regional social capital can influence credit ratings might affect public perception and trust in the impartiality and accuracy of these ratings, which is essential for maintaining market stability and integrity.

Our research provides fresh insights into how social capital, an intangible asset, influences credit ratings – a topic not extensively explored in existing literature. This sheds light on the dynamics between social structures and financial outcomes. Methodologically, our use of the 9/11 attacks as an exogenous shock to measure changes in social capital introduces a novel approach to study similar phenomena. Additionally, our findings contrast with prior studies such as Jha and Chen (2015) and Hossain et al. (2023), by delving deeper into how proximity and familiarity impact financial assessments differently, enriching academic discourse and refining existing theories on the role of local knowledge in financial decisions.

The present study examines the impact of sustainable transitions on the energy and environmental efficiency (EEE) of nations across the developed and developing world. It studies the temporal shift in the share of renewable sources in energy generation. It also analyses the shift in the efficiency frontier of nations using data envelopment analysis (DEA). Further, it studies the macro-level drivers of EEE in the countries.

As the first step, we benchmark the EEE of the developed and developing nations using DEA. Subsequently, we look at the influence of institutional quality, human capital, R&D and knowledge systems on EEE, to develop a comprehensive understanding of the macro-level drivers of EEE.

Our analyses reveal that a country’s institutional quality, human capital and R&D are critical determinants of EEE. The results show that while human capital has a significant positive impact on EEE, R&D expenditure alone has no substantial impact. The findings also suggest that knowledge diffusion disperses best practices across nations and bridges EEE gaps.

Attempts to promote sustainable energy transitions and improve EEE have met with varying levels of success. The results of this study will provide a useful guideline for the governments to achieve the goal of EEE through sustainable energy transitions (SET).

Unlike previous studies, we adopt a multi-factor EEE assessment. We also examine additional influences like the human capital of a nation and its knowledge management system to develop a comprehensive understanding of the macro-level drivers of EEE.

This quantitative study, rooted in the resource-based view (RBV) theory, aims to investigate the relationships among green transformational leadership, green process innovation, employee environmental beliefs and firm environmental performance in Italian manufacturing companies. This study unfolds a nuanced narrative of how strategic green transformational leadership, coupled with environmentally conscious processes, can synergistically enhance an organization's overall environmental performance.

The multi-item survey questionnaire used in this study was distributed to leaders in a diverse sample of Italian companies. A total of 296 valid responses were obtained from the surveys. The collected data were analysed using statistical methods such as correlation, confirmatory factor and structural equation modelling using SPSS software.

The direct influence of green transformational leadership on firm environmental performance is supported. It also confirms the positive impact of green process innovation on environmental outcomes. It identifies green process innovation as a mediator between green transformational leadership and firm environmental performance, and employee environmental beliefs moderate the link between green transformational leadership and firm environmental performance.

This research contributes by advancing understanding within the RBV framework by elucidating the specific mechanisms through which green transformational leadership programs promote green process innovation, enhance environmental performance for organizational success, achieve sustainability goals and foster collaboration and stakeholder engagement.

This study emphasizes the significance of establishing green leadership programs, encouraging green process innovation and systematically monitoring environmental performance to accomplish organizational success and sustainability goals.

This study presents a novel and original examination by integrating the RBV theory on the relationships between green transformational leadership, green process innovation and firm environmental performance, shedding new light on the role of employee environmental beliefs.

This study aims to explore the country’s contribution to research on halal food small- and medium-sized enterprises (SMEs) taken from the Scopus database for 10 years from 2013 to 2022 so that it can provide an overview of the effort that needs to be made by the government to improve research in this field.

The method used in this study was bibliometric analysis. The data comes from the Scopus database over the past 10 years (2013–2022). To create data visualization and network analysis using VOSviewer, Scimago Graphica, Bibliometrix and MS Excel.

Research on halal food SMEs has grown by almost 25%, with Malaysia leading with 447 publications. The UK is the leading country in publishing research articles with 44 journals. Malaysia has the most institutions (40 institutions for 25% globally). Malaysia has most research funding agencies (22 for 14% globally). Malaysia has the highest number of citations in halal food SMEs, with 3547 citations, followed by China and Indonesia. Malaysia has also the highest number of collaborating researchers and the most invitations. Future research focuses on sustainability, social issues, Internet of Things technologies, innovative technologies and strategies to increase productivity and competitiveness.

This research is a reference and overview of future research in halal food SMEs with the perspective of a country contribution angle. It provides input to the government on what needs to be done to develop research in the halal field in line with the goal of a country becoming the center of the global halal industry.

Little is established about the mechanism through which employee voice is connected to employee mental health. Drawing from social exchange theory, this study examines how employee engagement practices are associated with employee voice, which further influences employee mental health. In addition, the study includes parallel mediation and examines whether perceived interpersonal justice (PIJ) and empathetic leadership (EL) mediate the relationship between employee engagement practices and employee voice.

Three time-lagged surveys of 457 employees in the Indian information technology (IT) sector were accomplished.

As hypothesised, employee engagement practices have a positive influence on employee voice. Secondly, employee voice has a positive influence on the employee’s mental health. PIJ and EL were also found to be significant parallel mediators for the relationship among employee engagement practices and employee voice.

This study displays the positive influence of employee engagement practices on employee voice. Further, the employee’s voice influences the employee’s mental health. Therefore, it suggests means for improving its pervasiveness in an organisation.

This research paper is an important contribution as it is one of the few studies examining the role of PIJ and EL as parallel mediators of employee engagement practices and employee voice. It also answers repeated calls for more research on employee mental health in the IT sector.