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1 – 10 of 41Mohammad Shahin Alam, Kelly Williams-Whitt, DuckJung Shin and Mahfooz Ansari
This study develops and tests a comprehensive model that examines whether dimensions of supervisors’ job demands and resources influence their work motivation through their job…
Abstract
Purpose
This study develops and tests a comprehensive model that examines whether dimensions of supervisors’ job demands and resources influence their work motivation through their job strain levels while managing disability accommodation (DA).
Design/methodology/approach
The proposed model leverages the assumptions of established job demand and resources theories, including demand-ability fit, job demand-control, job demand-control-support, and effort-reward balance models. Then, we tested with the quantitative data from 335 British, Canadian, American, Australian, Dutch, and German supervisors with recent DA experience.
Findings
This study found support for the proposed model. Job control and social support directly affected work motivation, while job strain did not mediate the relationship between job control and social support and work motivation. The results suggest that employers looking to improve the likelihood of DA success should focus on providing adequate job control, social support, and rewards to supervisors responsible for accommodating employees with disabilities.
Practical implications
This research enhances our understanding of how additional DA responsibilities impact supervisors and aids in the development of effective DA management policies and interventions, providing robust support for practitioners.
Originality/value
This study contributes to extending the DA literature by testing the applicability of different theoretical models to explain the effect of the additional DA responsibility on supervisors’ job demand, strain, and motivation levels and identify the resources to mitigate them.
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Chyi Yann Chong, Chin Xuan Tan, Meng-Che Tsai, Seok Shin Tan, Hariyono Hariyono and Seok Tyug Tan
Malaysia transitions from a pandemic to an endemic state, beginning on April 1, 2022. The dietary intake and physical activity of university students were altered during the…
Abstract
Purpose
Malaysia transitions from a pandemic to an endemic state, beginning on April 1, 2022. The dietary intake and physical activity of university students were altered during the COVID-19 pandemic confinement period, but there is limited information on this topic in the post-COVID-19 period. This cross-sectional study aims to understand gender differences in dietary intake and physical activity among university students and investigate the factors influencing their body mass index (BMI) in the post-COVID-19 period.
Design/methodology/approach
The questionnaire used in this study comprised three main segments: sociodemographic information, a semiquantitative food frequency questionnaire and the International Physical Activity Questionnaire.
Findings
Results indicated that males exhibited significantly higher (p < 0.05) mean intakes of total dietary energy and macronutrients compared to females. Compared to the Malaysian Recommended Nutrient Intakes 2017, 76.4% of males and 68.8% of females had a sufficient daily energy intake. The majority of males (52.7%) and females (46.4%) were moderately physically active. Regression analysis revealed that male university students with lower fiber intake (ß = −0.309, p = 0.002) were significantly associated with higher BMI reading after confounding adjustment. However, a similar trend was not observed in female university students.
Practical implications
Understanding the gender differences in dietary intake and physical activity can provide insights into the development of effective gender-specific health promotion strategies and the formulation of policies aimed at promoting healthier lifestyles among university students in the post-COVID-19 pandemic era.
Originality/value
This study provides insights into the gender differences in the dietary and physical activity habits of university students, as well as the factors influencing their BMI in the post-COVID-19 pandemic era.
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Kai Hänninen, Jouni Juntunen and Harri Haapasalo
The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive…
Abstract
Purpose
The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.
Design/methodology/approach
Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.
Findings
Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.
Research limitations/implications
The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.
Practical implications
This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.
Originality/value
This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.
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Hongfei Liu, Yue Meng-Lewis and Wentong Liu
Social media played an irreplaceable role in young people’s online social life and information consumption during the COVID-19 pandemic. This research focuses on the impact of…
Abstract
Purpose
Social media played an irreplaceable role in young people’s online social life and information consumption during the COVID-19 pandemic. This research focuses on the impact of excessive information on social media about COVID-19 vaccines on Generation Z's (Gen Z) associated psychological states and long-term vaccine advocacy.
Design/methodology/approach
The research conducted structural equation modeling analysis with online survey data from 409 Gen Z citizens in the UK.
Findings
The findings suggest that excessive information increased Gen Z social media users' ambivalence and conspiracy beliefs around COVID-19 vaccines, which, in turn, reduced their long-term vaccine advocacy in terms of vaccine acceptance, vaccination intention and vaccine promotion. Importantly, Gen Z’s confidence in government and in the healthcare systems during COVID-19 was effective in helping them overcome the detrimental effects of conspiracy beliefs and ambivalence about long-term vaccine advocacy, respectively.
Originality/value
This research reveals the “dark side” of social media use in the post-pandemic period and highlights the significant roles played by social institutions in mitigating the detrimental effects of Gen Z’s support in social decisions. Beyond the context of COVID-19, this research has important implications for facilitating the civic engagement of Gen Z and boosting their confidence in social institutions in terms of social cohesion.
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Luan Thanh Le and Trang Xuan-Thi-Thu
To achieve the Sustainable Development Goals (SDGs) in the era of Logistics 4.0, machine learning (ML) techniques and simulations have emerged as highly optimized tools. This…
Abstract
Purpose
To achieve the Sustainable Development Goals (SDGs) in the era of Logistics 4.0, machine learning (ML) techniques and simulations have emerged as highly optimized tools. This study examines the operational dynamics of a supply chain (SC) in Vietnam as a case study utilizing an ML simulation approach.
Design/methodology/approach
A robust fuel consumption estimation model is constructed by leveraging multiple linear regression (MLR) and artificial neural network (ANN). Subsequently, the proposed model is seamlessly integrated into a cutting-edge SC simulation framework.
Findings
This paper provides valuable insights and actionable recommendations, empowering SC practitioners to optimize operational efficiencies and fostering an avenue for further scholarly investigations and advancements in this field.
Originality/value
This study introduces a novel approach assessing sustainable SC performance by utilizing both traditional regression and ML models to estimate transportation costs, which are then inputted into the discrete event simulation (DES) model.
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Abstract
Purpose
This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.
Design/methodology/approach
The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.
Findings
The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.
Originality/value
This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.
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Thi Ngan Pham, Minh Tu Tran Hoang, Yen Ngan Nguyen Tran and Binh An Nguyen Phan
This study aims to comprehensively assess how digital maturity degree (DMD) impacts sustainable supply chain management (SSCM) performance through the mediating role of SSCM…
Abstract
Purpose
This study aims to comprehensively assess how digital maturity degree (DMD) impacts sustainable supply chain management (SSCM) performance through the mediating role of SSCM practices in businesses in Vietnam.
Design/methodology/approach
The hypotheses were performed using partial least square-structural equation modeling (PLS-SEM) with data collected from a survey of over 234 managers having responsibility in the supply chain field in Vietnam. Qualitative data were collected through semistructured interviews with 6 experts to deepen understanding of the relationship between DMD and SSCM.
Findings
The results show the mix-results in the relationship between SSCM practices and SSCM performance dimensions while DMD strongly impacts SSCM practices. Also, this study finds the mediating role of SSCM practices on the relationship between DMD and SSCM performance.
Originality/value
This is the first study to investigate the role of DMD on SSCM practices and SSCM performance, using empirical evidence. Moreover, the authors integrate both qualitative and quantitative for understanding complex SSCM phenomena. The present study also helps businesses improve their SSCM performance by leveraging SSCM practices and developing their digital technologies in the long-term view.
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Inzamam Ul Haq, Chunhui Huo and Irum Saba
This paper aims to examine the dynamic relationship between economic growth and sustainable development, integrating the Environmental Kuznets Curve (EKC) in 22 Organization of…
Abstract
Purpose
This paper aims to examine the dynamic relationship between economic growth and sustainable development, integrating the Environmental Kuznets Curve (EKC) in 22 Organization of Islamic Cooperation (OIC) member countries across income groups.
Design/methodology/approach
Using annual data between 1990 and 2022, the authors apply the cross-correlation coefficient (CCC) approach of Narayan et al. (Economic Modeling, 2016, 53, 388–397) to examine the lead/lag relationship between GDP per capita and sustainable development. This study further validates the findings through a panel Granger causality test and a fixed panel regression model.
Findings
This research provides evidence of a U-shaped EKC for only 1 out of 22 (5%) OIC countries. For 13 out of the 22 (59%) OIC countries, increasing income growth is expected to enhance sustainable development in the future. The results show that as income levels rise, there will be a more significant decline in sustainable development for high-income OIC countries in the future than for both middle-income groups, contradicting the EKC hypothesis. The findings from the panel Granger causality and panel regression models also support the CCC results.
Originality/value
This study proposes a reverse version of the EKC hypothesis and contributes to the literature on economic growth and environmental sustainability. With increasing economic growth, the results can assist OIC member governments and policy-makers in designing tailored policies and practical measures for future sustainable development.
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Xueguo Xu and Hetong Yuan
Breakthrough technological innovation is of vital significance for firms to acquire and maintain sustainable competitive advantages. The construction of an innovation ecosystem…
Abstract
Purpose
Breakthrough technological innovation is of vital significance for firms to acquire and maintain sustainable competitive advantages. The construction of an innovation ecosystem and the interaction with heterogeneous participants have emerged as a new dominant model for driving sustained breakthrough technological innovation in firms. This study aims to explore the effects of collaborative modes within the innovation ecosystem on firms’ breakthrough technological innovation and the ecological legitimacy mechanisms involved.
Design/methodology/approach
The research employs data from 212 innovative firms and conducts empirical research using a two-stage structural equation modeling (SEM) and artificial neural network (ANN) analysis.
Findings
The results indicate that firm-firm collaboration (FF), firm-user collaboration (FU), firm-government collaboration (FG), firm-university-institute collaboration (FUI) and firm-intermediary collaboration (FI) all have significant positive effects on breakthrough technological innovation (BTI), with FU being particularly crucial. Furthermore, the results confirm the positive moderating effects of ecological legitimacy (EL) on the relationships between FF and BTI, as well as between FU and BTI. Conversely, EL has a negative moderating effect on the relationship between FUI and BTI, as well as between FI and breakthrough technological innovation. Additionally, EL does not have a significant influence on the relationship between FG and BTI.
Originality/value
Through resource dependence theory (RDT), this study unveils the black box of how collaboration modes within innovation ecosystems impact breakthrough technological innovation. By introducing ecological legitimacy as a contextual factor, a new research perspective is provided for collaboration innovation within innovation ecosystems. The study employs a combination of SEM and ANN for modeling, complementing nonlinear relationships and obtaining robust results in complex mechanisms.
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Adarsh Chandra Nigam and Ruby Soni Chanda
The utilization of mobile fitness applications (apps) is on the rise, making user retention and engagement critical factors in the commercial success of these apps. However…
Abstract
The utilization of mobile fitness applications (apps) is on the rise, making user retention and engagement critical factors in the commercial success of these apps. However, research in this area is limited and fragmented. The objective of this study is to conduct a thorough review of the available literature on the effects of digital innovations, gamification, artificial intelligence (AI) and machine learning (ML) on user engagement with fitness mobile apps. The findings reveal the relationships between gamification, the use of AI/ML and technology adoption on user engagement, interaction and intent to use. Additionally, the study highlights the importance of understanding how user experience, customer experience and brand experience impact customer retention and contribute to the overall success of mobile fitness apps. Furthermore, the study also identifies the gaps in the current research and recommends further studies to be conducted in these areas. Future research is encouraged to incorporate elements from the experience domains to provide consumers with engaging interactions and improve retention and commercial success for mobile fitness apps.
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