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Given the urgency of corporate engagement in sustainable development, companies seek ways to involve their employees in sustainability efforts. In this regard, gamified systems have gained attention as a novel tool to promote sustainable employee behavior. However, as the research field matures, researchers and practitioners are confronted with a scattered academic landscape that makes it difficult to grasp how gamification can be designed to engage employees in sustainable behavior and to understand how gamification effects unfold at psychological, behavioral and corporate levels of sustainability.

This paper uses a systematic literature review to consolidate the existing knowledge on gamification designs and their effects on sustainable employee behavior.

Studies have explored a variety of utilitarian and achievement-, immersion- and social-related gameful affordances to promote positive behavior- and system-related psychological effects as a basis for employee engagement in sustainable behavior. However, the evidence regarding their impact on rational decision-making processes and overcoming the intention-action gap inherent in sustainability is still limited. Nevertheless, several studies in focused areas indicate the potential to elicit behavioral changes that drive sustainability outcomes at the corporate level as well.

Our study provides three main contributions. First, we develop a conceptual framework that illustrates how gamification can drive sustainable behavior in the workplace. Second, we derive seven agenda points to guide future research on gamification for corporate sustainability. Third, we deduce three practical approaches to use gamification as a strategic intervention to promote sustainable behavior in organizations.

The purpose of the study is to test the precursors of presenteeism. The research has examined the relationship between workplace bullying and presenteeism via depression and anxiety. Furthermore, moderating the role of toxic leadership is also investigated which may strengthen or weaken workplace bullying and mental health relationships.

The mediations and moderation models were tested in SPSS software through the Preacher and Hayes PROCESS macro technique. Data was gathered from 165 employees, working in public and private universities of Pakistan.

The results supported that depression and anxiety act as mediators in the relationship between bullying and presenteeism. Further, toxic leadership moderated the relationship between bullying and depression, bullying and anxiety.

As per the author’s knowledge, rare studies have determined that bullying can increase mental health issues and presenteeism in employees. Bullying and toxic leadership together increase the loss of psychological resources that force employees to work while feeling sick.

The primary aim of this research is to conduct a comprehensive investigation into the essential elements of Industry 4.0 implementation within Indian Micro, Small and Medium Enterprises (MSMEs). Acknowledging the MSME sector as a crucial contributor to the Indian economy and industrial development, the study delves into the assessment of MSMEs based on Industry 4.0 components. Additionally, it explores the profound impact of these components on various performance factors, including organizational performance, sustainability performance and human-related aspects. The paper further ranks these identified components based on their significance within the MSME sector.

Employing a combination of methodological approaches, the research utilizes the Best and Worst Method (BWM), Data Envelopment Analysis (DEA) and calculates the Maturity Index for Industry 4.0 components. The BWM, a recognized multi-criteria decision-making technique, is initially applied to determine the weights and rankings of the identified components. Furthermore, the study evaluates 30 MSMEs, spanning manufacturing and service sectors, through the DEA approach. Industry 4.0 components are treated as inputs, and performance factors serve as outputs. Data for the analysis are collected through questionnaires distributed to the selected MSMEs. Lastly, the Maturity Index for MSMEs is also calculated.

From the result of the BWM method “assistive manufacturing” was found to be a highly weighted key component of Industry 4.0. From the DEA analysis out of 30 MSMEs 13 SMEs were highlighted as being efficient, whereas 17 MSMEs were judged to be inefficient. Furthermore, from the maturity index calculation, overall Maturity Index was determined to be 3.33 which shows that Industry 4.0 is in its initial stage of implementation, but it has gained pace in its implementation.

The research contributes to practical implications by offering a more accurate assessment of the state of Industry 4.0 implementation within MSMEs. The introduced maturity index proves instrumental in pinpointing key components that have received inadequate attention. This information is crucial for MSME managers and policymakers, guiding them in allocating resources effectively, addressing areas requiring attention and facilitating progress in the implementation of Industry 4.0. The study serves as a valuable tool for MSMEs to enhance their overall operational efficiency.

The research’s originality lies in its application of a comprehensive approach, combining BWM, DEA and the introduction of a maturity index for Industry 4.0 components in the MSME context. By employing these methodologies, the study not only identifies influential components but also provides a nuanced understanding of their relative significance. The research contributes significantly to the broader understanding of Industry 4.0 adoption, particularly, in the vital MSME sector within the Indian context. The findings are valuable for researchers, practitioners and policymakers seeking insights into improving the efficiency and effectiveness of MSMEs in the era of Industry 4.0.

This research was conducted to establish and validate a model between self-efficacy, learning motivation and academic satisfaction. The mediating effect of classroom engagement between learning motivation and academic satisfaction was also tested.

This empirical investigation was conducted over a sample of 446 students from state-owned universities in Haryana, India. The sample was drawn using the stratified random sampling technique. A semi-structured questionnaire was distributed for data. Structural Equation Modeling (SEM) using AMOS was used for data analysis.

The study’s results found that self-regulation, perceived control, persistence and competence were significantly associated with learning motivation, which further proved the significant association with academic satisfaction. The mediating effect of classroom engagement between learning motivation and satisfaction was significant.

This study uniquely examines the interplay between self-efficacy, learning motivation and academic satisfaction among university students, highlighting the crucial mediating role of classroom engagement. By focusing on students from top state-owned universities, it provides valuable insights into how classroom dynamics influence academic outcomes.

This study explores the effects of competitive intensity and innovation orientation on export outcomes, including export entrepreneurship (EE) and export performance (EP), and determines the direct and moderating impact of corporate social responsibility (CSR) among exporting agricultural and food (agri-food) small and medium-sized enterprises (SMEs) in Iran.

Using systematic random sampling, 296 firms participating in the international food and agricultural industries exhibition filled out a questionnaire. Smart PLS3 software was used to analyze the data.

The competitive intensity has positive effects on export entrepreneurship of Iranian agri-food SMEs. Additionally, innovation orientation, CSR and EE positively impact EP. However, the moderating impact of CSR on the relationship between innovation orientation and EP was not supported by data.

The current study enriches the existing knowledge in international business in the specific setting of exporting agri-food SMEs operating in a developing economy.

This study investigates the influence of market and hierarchy organizational cultures on international project performance and examines the mediating role of relational capital.

In-depth interviews and a cross-sectional questionnaire survey were conducted to collect primary data within international projects. Hierarchical regression analysis was used to test the hypotheses based on data collected from 62 respondents.

The results reveal that both market and hierarchy cultures affect international project performance positively. Additionally, communication, cooperation and trust help enhance project performance; however, commitment is not. This study also proves the mediating role of relational capital between organizational culture and project performance.

This study selected only two types of organizational culture represented by Chinese construction enterprises. Future studies can explore the mediating role of relational capital between other varieties of organizational culture and project performance.

Given the high complexity and risks faced by projects abroad, both organizational culture, the internal environmental factor and relational capital being the external resource, are crucial for project success. This study clarifies the relationship between organizational culture, relational capital and project performance overseas. Empirical evidence to enhance international project performance for construction enterprises is provided. This study also makes contributions to international contractors who want to implement projects in developing countries.

This research aims to examine how social media characteristics influence job applicants' intentions to apply for positions, with a focus on the mediating roles of employer brand attractiveness and person-organization fit. This study is grounded in signaling and congruity theories.

The researchers use a convenience sampling method among 260 new graduates of the number of private universities in Iran. Structural equation modeling was then used to analyze the data.

The results demonstrate that social media characteristics, specifically social presence and informativeness, significantly impact both employer brand attractiveness and person-organization fit. Furthermore, both employer brand attractiveness and person-organization fit fully mediate the relationship between social media characteristics and job application intentions.

This study extends existing literature by empirically demonstrating the crucial role of social media characteristics in shaping job applicant behavior. It provides valuable insights for practitioners by highlighting the importance of carefully crafting social media content to effectively communicate organizational values and culture, thereby enhancing employer brand attractiveness, fostering person-organization fit and, ultimately, increasing the likelihood of attracting qualified candidates.

The study aims to explore the relationship between the SDGs and the environmental and social impacts of university classes. It evaluates the potential contributions of different teaching models to the SDGs, providing insights into sustainable teaching systems.

In-person classes exhibited hotspots in transportation and energy consumption. Scenarios I and II, involving virtual and hybrid classes, increased eutrophication potential and water scarcity due to higher food consumption, negatively impacting SDGs. However, all scenarios showed positive contributions to SDGs 2, 3, 6, 9, 11, 12, 13, 14 and 15.

This research integrates Life Cycle Assessment (LCA) with the United Nations Sustainable Development Goals (SDGs) to assess the environmental and social impacts of classes at the Federal University of São Carlos, Sorocaba campus in Brazil. Three scenarios were analyzed: (I) virtual classes, (II) hybrid classes and (III) in-person classes with improved energy efficiency.

The study primarily focuses on environmental and social impacts, excluding other factors like class quality. Integrating Life Cycle Costing and Life Cycle Sustainability Assessment could provide a more holistic evaluation in the future.

The methodology adopted offers valuable insights for managing the impacts of university performance and aligning teaching systems with the SDGs. It enables institutions to make informed decisions for sustainability in education.

The research emphasizes the importance of considering social impacts alongside environmental ones when assessing sustainability in educational institutions. It encourages universities to engage stakeholders in sustainability efforts.

This research innovatively combines LCA and the SDGs in the context of university education providing a replicable methodology for evaluating and enhancing sustainability in teaching systems and from a more quantitative perspective.

University students often encounter academic challenges and setbacks, which can impact their beliefs about their capabilities, leading to a phenomenon known as learned helplessness. This study explores the antecedents of learned helplessness through the interaction between teacher support, self-efficacy, and cultural dimensions such as power distance, uncertainty avoidance, and masculinity.

Drawing from constructivism, the authors empirically examined a conceptual model utilizing structural equation modeling (SEM). A total of 268 university students completed a self-survey on learned helplessness via a Google Form.

The study shows that LH is influenced by personal attributes, perceived support, and cultural context. Higher self-efficacy is linked to lower LH scores, while teacher support indirectly affects LH through self-efficacy. Power distance and uncertainty avoidance also directly impact LH. Additionally, cultural influences indirectly affect LH through perceived support and self-efficacy. However, the hypothesized connections between masculinity and LH were not supported.

The study advances LH literature by exploring it among university students using a multidimensional, constructivist approach, providing valuable insights for educational authorities. We illuminate how individual, social, and cultural factors influence LH, underscoring the serial mediation between self-efficacy and perceived teacher support. Existing literature frequently overlooks the intricate interplay among cultural dimensions and other factors, limiting the formulation of comprehensive solutions. Our research breaks new ground in quantitative LH examination within education, delving into Hofstede’s cultural dimensions and suggesting strategies to mitigate uncertainty and power distance for student well-being and success.

This paper proposes a novel visual-inertial-ranging odometry (VIRO) algorithm that tightly incorporates bundled ultra-wideband (UWB) sensors into existing visual-inertial odometry (VIO), with the aim to provide fully observable robot state estimation. The VIRO estimator proposed in this paper is the first VIRO estimator to demonstrate full observability.

This paper proposes a tightly coupled fusion model of visual-inertial-ranging measurements based on extended Kalman filter (EKF), where UWB anchors are integrated into a cohesive sensor network. This paper modifies the Schmidt Kalman filter formulation to efficiently incorporate the robot’s poses into state vector, facilitating online UWB network initialization and consistent state augmentation.

Observability analysis proves that the proposed VIRO system has four unobservable directions in the VIO reference frame, and achieves fully observable estimation in the gravity-aligned UWB network frame. Extensive simulation and real-world experiments are conducted to validate the proposed method.

Most existing approaches treat UWB anchors as independent sensing sources, overlooking the potential of leveraging the relative poses between these cooperative targets to enhance localization accuracy. Or, the UWB network and other VIO components are loosely coupled, with the robot pose estimation being solved independently before fusion. However, this approach fails to account for UWB sensing errors, which is unestimable, leading to manual intervention in parameter settings. This work proposed the first proved fully observable VIRO estimator based on a tightly coupled EKF framework.