Structural equation modeling for three aspects of green business practices: a case study of Bangladeshi RMG's industry

Impact of corporate social responsibility on sustainable competitive advantages: The mediating role of corporate reputation

This study investigates the relationship between corporate social responsibility (CSR) and sustainable competitive advantage (SCA). Moreover, building on the stakeholder theory, this study investigates the mediating effects of corporate reputation (CR) between the relationship of corporate social responsibility and sustainable competitive advantage. We used a questionnaire survey to collect data from the employees working in the construction industry of Pakistan. Using the sample of 239 respondents, a structural equation modeling technique was used to verify the hypothesis relationship. The findings indicated that CSR directly and positively influences sustainable competitive advantages. Moreover, corporate reputation positively mediates the connection between corporate social responsibility and sustainable competitive advantage. This research fills knowledge gaps and highlights the significance of CSR in fostering sustainable competitive advantages within the construction industry.

Exploring Factors Affecting Crash Injury Severity with Consideration of Secondary Collisions in Freeway Tunnels

Although there have been several studies conducted exploring the factors affecting injury severity in tunnel crashes, most studies have focused on identifying factors that directly influence injury severity. In particular, variables related to crash characteristics and tunnel characteristics affect the injury severity, but the inconvenient driving environment in a tunnel space, characterized by narrow space and dark lighting, can affect crash characteristics such as secondary collisions, which in turn can affect the injury severity. Moreover, studies on secondary collisions in freeway tunnels are very limited. The objective of this study was to explore factors affecting injury severity with the consideration of secondary collisions in freeway tunnel crashes. To account for complex relationships between multiple exogenous variables and endogenous variables by considering the direct and indirect relationships between them, this study used a structural equation modeling with tunnel crash data obtained from Korean freeway tunnels from 2013 to 2017. Moreover, based on high-definition closed-circuit televisions installed every 250 m to monitor incidents in Korean freeway tunnels, this study utilized unique crash characteristics such as secondary collisions. As a result, we found that tunnel characteristics indirectly affected injury severity through crash characteristics. In addition, one variable regarding crashes involving drivers younger than 40 years old was associated with decreased injury severity. By contrast, ten variables exhibited a higher likelihood of severe injuries: crashes by male drivers, crashes by trucks, crashes in March, crashes under sunny weather conditions, crashes on dry surface conditions, crashes in interior zones, crashes in wider tunnels, crashes in longer tunnels, rear-end collisions, and secondary collisions with other vehicles.

Influence of diverse kinds of persuasive messages on intention to stay home during COVID-19 pandemic: Moderating role of media type

This study highlights the influence of diverse kinds of persuasive messages on intention to stay home during COVID-19 pandemic. The COVID-19 pandemic is believed to be the top modern societal challenge necessitating extensive collective action and collaboration. The statistical population included Iranian individuals by answering our online survey questionnaires at diverse phases of the COVID-19 pandemic. 406 completed questionnaires were gathered and analyzed. Note that, according to the official reports, Iran encountered COVID-19 disease since February 19, 2020. Data collection was started on July 18, 2020 (at the beginning of second wave of COVID-19 in Iran) and lasted until October 30, 2020. Various social network platforms including Instagram, WhatsApp, Facebook and Telegram were used for distribution of the questionnaires. According to the results, perceived severity and perceived self-efficacy had an insignificant direct influence on intention to stay home. From another perspective, perceived vulnerability (β = 0.261, CI = 0.059; 0.242]) and perceived response efficacy (β = 0.502, CI = 0.347; 0.656]) positively and significantly affected the intention to stay home. Moreover, no significant difference was found between these two kinds of media messages in research sample. Our findings showed that “perceived response efficacy” has the highest importance score of 0.502; if the perceived response efficacy performance is boosted by one unit point by individuals during COVID-19 pandemic, its overall intention to stay home will increase by 0.502. Besides, our results showed that lowest performance (78.104) is associated with perceived vulnerability highlighting an excellent opportunity for improvement in this area.

Evaluation of the determinants of food security within the COVID-19 pandemic circumstances- a particular case of Shaanxi, China

BACKGROUND

Agricultural food production and distribution industries may play a vital role in determining the current conditions of any country's food security and sustainable development goals. This paper examined the determinants of food security within three distinct aspects (effective utilization of food, food availability, and food access) within the COVID-19 epidemic situation.

METHODS

The qualitative set-up of the study comprised with the identification of drivers by critical analysis of published papers and discussion held with some practitioners. The quantitative data used in this research were collected from a survey covering the agricultural food supply industry in China (Shaanxi Province). The survey was conducted from November to December 2020 and we mainly focus on three aspects of food security (effective utilization of food, food availability, and food access). The core analytical assumptions were made by employing exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM).

RESULTS

After analyzing the data collected from 257 agricultural food productions and distribution personnel along with the hypothesis testing, it found that the determinants of the effective utilization of food were positively related to the determinants of food access (β = 0.291, p = 0.029) and food availability (β = 0.298, p = 0.011), and the determinants of food availability were positively related to the food access determinants (β = 0.128, p = 0.002). The association and variance values between food availability and food access were 0.659 and 0.407; the association and variance values between for effective utilization of food and food availability aspects were 0.465 and 0.298, and between effective utilization of food and economy were 0.508 and 0.475.

CONCLUSION

The study critically evaluated the interconnection among the crucial determinants within the banner of three dimensions, which will act as a major contribution to existing literature. This research will help the government and industry to develop policies and strategies for the successful implementation of all the associated determinants of food security in terms of the epidemic situation.

Behavioral intention model for green information technology adoption in Nigerian manufacturing industries

Purpose

Greenhouse effects and the need for cost savings necessitate that an organization's information technology (IT) managers design IT equipment acquisition and service provisioning policies to reduce carbon footprint and cost. Analyzing the influencing factors that influence stakeholders' attitudes toward adopting green information technology (Green-IT) is an important input in designing these policies. In essence, the research aims to investigate into the relationship between these factors and how they influence policy-makers' behavior in Nigerian manufacturing industries.

Design/methodology/approach

The study develops a model based on the norm activation model (NAM) and the theory of planned behavior (TBP) to investigate the factors that influence decision-makers' intention in adopting Green-IT. A quantitative approach using a survey method is carried out to gather opinions of IT decision-makers using a random sampling technique. Partial least squares structural equation modeling (PLS-SEM) technique is applied to test the structural model and measurement model.

Findings

The study's findings support the use of the behavior model for Green-IT adoption. The study's finding indicates that subjective norms, perceived behavior control (PBC), manager's attitude, personal norm (PN), awareness of adverse consequences and the ascription of responsibility (AR) positively influence intention to adopt Green-IT.

Research limitations/implications

The development and validation of the model are the study's theoretical contributions. The study reviewed the existing literature on the utilization of Green-IT to better understand the intention to adopt Green-IT in Nigeria. It added to the literature by identifying factors that can influence it as well as theoretical underpinnings that can fit the intentions of decision-makers. The scientific community and the industrial companies would have the chance to investigate how this integrated behavioral intention model promotes the use of Green-IT. The research predictors explained about 70.20% of the variance in the behavioral intention to adopt Green-IT.

Practical implications

Research offers practical implications and recommendations for top management practitioners of the manufacturing industries. Business leaders can use the results of this study to develop an effective strategic IT policy for the successful adoption of Green-IT practices for enhanced productivity. The study found that decision-makers' Green-IT attitudes had a substantial impact on their behavioral intention to adopt Green-IT. The study highlighted the importance of the top management attitude toward green products to facilitate the adoption of Green-IT practices in manufacturing industries in Nigeria. Thus, the positive and significant attitude of policy-makers is a necessary tool toward the successful adoption of Green-IT. Therefore, to foster an environmentally sustainability friendly atmosphere, Nigeria's manufacturing industries shall strive to strengthen the decision-makers' attitude toward practicing Green-IT in their respective domains. The findings showed that AR, AQ, environmental concern (EC), perceived behavior and perceived behavior are critical factors to be considered in an organization.

Social implications

According to the findings, an individual's Green-IT attitude has a substantial impact on the environment as social behavior. As a result, the positive and essential attitude of the social sector is a key tool for efficient Green-IT implementation. Nigeria's social activists must try to create awareness campaigns to boost decision-makers' attitudes toward implementing Green-IT in their various regions to develop a friendlier environment. Thus, the identified factors can be of great help to the social sector in designing and implementing successful environmental-friendly policies that could support the adoption of Green-IT practices.

Originality/value

The current research look at Green-IT adoption in manufacturing industries of West African countries. The study offers practical implications and recommendations for top management practitioners of the manufacturing industries, government policy-makers and organizations to enhance the use of Green-IT for mitigating environmental degradation. Recommendations for future research are stated as concluding remarks.

Consumer Knowledge Sharing Behavior and Consumer Purchase Behavior: Evidence from E-Commerce and Online Retail in Hungary

The twenty-first century has been full of fundamental changes in consumers’ behavior patterns, especially with the use of diverse social media knowledge-sharing platforms. Therefore, companies have highlighted the significance of knowledge sharing and the importance of social network use in purchasing processes. Accordingly, his paper tries to reveal how consumer purchase behavior (CPB) can be affected by consumer knowledge sharing behavior (CKSB) and the moderating role played by value co-creation dimensions, which are citizenship behavior (CB) and participation behavior (PB), within a sustainable e-commerce field. To test our hypotheses deducted from the literature review, we opted for the PLS-SEM method. We also employed other innovative approaches, such as the IPMA matrix, MAICOM test, FIMIX approach, and CTA analysis, to evaluate the outer and inner model. Our statistical population covered individuals living in Hungary with at least one online purchase involvement. We distributed the questionnaire via various online platforms and, finally, 433 completed questionnaires were prepared for analysis. The results showed that CPB, CB, and PB are positively influenced by the CKSB. However, the link between CPB and CB was not confirmed. As for the moderating role of gender, the permutation test was applied to compare male and female groups and see the difference between them. With a focus on CKSB, this study contributes to the success of international marketing strategies to attain higher competitive advantages.

The Assessment of Big Data Adoption Readiness with a Technology–Organization–Environment Framework: A Perspective towards Healthcare Employees

Big data is rapidly being seen as a new frontier for improving organizational performance. However, it is still in its early phases of implementation in developing countries’ healthcare organizations. As data-driven insights become critical competitive advantages, it is critical to ascertain which elements influence an organization’s decision to adopt big data. The aim of this study is to propose and empirically test a theoretical framework based on technology–organization–environment (TOE) factors to identify the level of readiness of big data adoption in developing countries’ healthcare organizations. The framework empirically tested 302 Malaysian healthcare employees. The structural equation modeling was used to analyze the collected data. The results of the study demonstrated that technology, organization, and environment factors can significantly contribute towards big data adoption in healthcare organizations. However, the complexity of technology factors has shown less support for the notion. For technology practitioners, this study showed how to enhance big data adoption in healthcare organizations through TOE factors.

Evaluation of preventive, supportive and awareness building measures among international students in China in response to COVID-19: a structural equation modeling approach

BACKGROUND

Education institutions promptly implemented a set of steps to prevent the spread of COVID-19 among international Chinese students, such as restrictive physical exercise, mask wear, daily health reporting, etc. Success of such behavioral change campaigns largely depends on awareness building, satisfaction and trust on the authorities. The purpose of this current study is to assess the preventive, supportive and awareness-building steps taken during the COVID-19 pandemic for international students in China, that will be useful for planning such a behavioral change campaign in the potential pandemic situation in other parts of the world.

METHODS

We conducted an online-based e-questionnaire survey among 467 international students in China through WeChat. The data collection duration was from February 20, 2020 to March 10, 2020 and we focused on their level of awareness, satisfaction, and trust in authorities regarding pandemic measures. Simple bivariate statistics was used to describe the background characteristics of the respondents along with adoption of the partial least squares-structural equation modeling (PLS-SEM) as the final model to demonstrate the relationship between the variables.

RESULTS

In our study, the leading group of the respondents were within 31 to 35 years' age group (39.82%), male (61.88%), living single (58.24%) and doctoral level students (39.8%). The preventive and supportive measures taken by students and/or provided by the respective institution or authorities were positively related to students' satisfaction and had an acceptable strength (β = 0.611, t = 9.679, p < 0.001). The trust gained in authorities also showed an acceptable strength (β = 0.381, t = 5.653, p < 0.001) with a positive direction. Again, the personnel awareness building related to both students' satisfaction (β = 0.295, t = 2.719, p < 0.001) and trust gain (β = 0.131, t = 1.986, p < 0.05) in authorities had a positive and acceptable intensity. Therefore, our study clearly demonstrates the great impact of preventive and supportive measures in the development of students' satisfaction (R2 = 0.507 indicating moderate relationship). The satisfied students possessed a strong influence which eventually helped in building sufficient trust on their institutions (R2 = 0.797 indicating above substantial relationship).

CONCLUSIONS

The worldwide student group is one of the most affected and vulnerable communities in this situation. So, there is a profound ground of research on how different states or authorities handle such situation. In this study, we have depicted the types and magnitude of care taken by Chinese government and educational institutions towards international students to relieve the panic of pandemic situation. Further research and such initiatives should be taken in to consideration for future emerging conditions.

Evaluations of the Roles of Organizational Support, Organizational Norms and Organizational Learning for Adopting Environmentally Friendly Technologies: A Case of Kiwifruit Farmers’ Cooperatives of Meixian, China

Environmentally friendly technologies have long been recognized as a widespread phenomenon working within the functions and performance of farms. Farmer’s cooperative organization might profoundly foster the environmentally friendly technologies (EFT) and availing competitive advantage to the farmer. Illustrated by the natural-resource-based view of the farm (NRBV), this study examined the influence of organizational support, organizational norms, and organizational learning on adopting EFT and proposed a model quantifying the impacts of these approaches towards availing competitive capabilities (i.e., cost, quality, flexibility, and delivery). The framework is empirically endorsed by employing the partial least squares approach to structural equation modeling (PLS-SEM) with the help of a household survey from a spectrum of 292 farmers of 38 kiwifruit cooperatives of Meixian County, China, from August to September 2020. The findings demonstrate that organizational support, organizational norms, and organizational learning positively influence EFT. Moreover, the study found EFT positively impacts product cost, product quality, product delivery, and production flexibility. Interestingly, the relationship between the adoption of environmentally friendly technologies and the competitive capabilities of kiwifruit farmers of Meixian is positively significant. The study proposes several policy recommendations emphasizing the role of organizations in the form of farmer’s cooperatives in boosting farmers to engage in proenvironmental behavior and, therefore, shifting the trends of future research directions on the adoption of environmentally friendly technologies.

Analyzing the green innovation practices based on sustainability performance indicators: a Chinese manufacturing industry case

In the wake of the Paris agreement, the adoption of green innovation practices has received substantial attention throughout the world. The consumers, manufacturers, governments, and communities have started realizing the severity and intensity of environmental hazards and climate change. The manufacturing sector is one of the leading industrial waste producers and contributors to environmental pollution, posing a threat to environmental sustainability. The adoption of green innovation practices in the manufacturing sector is indispensable to ensure environmental sustainability. However, it is pivotal to identify, assess, and evaluate the green innovation aspects and sub-aspects with the perspective of sustainability performance indicators in the manufacturing industry. This study services this purpose and proposes a hybrid multi-criteria decision-making (MCDM) by combining the fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) to analyze the effects of green innovation aspects with sustainability performance of the manufacturing industry. The authors identify six green innovation aspects (criteria), twenty-four sub-aspects (sub-criteria), and three sustainability performance indicators (alternatives) for the manufacturing industry in China. The FAHP method indicates that green managerial innovation, green product innovation, and green technological innovation are the most influential aspects of implementing green innovation practices. Further, the FTOPSIS technique reveals that environmental performance is the most suitable sustainability performance indicator in adopting green innovation practices in the garment manufacturing industry of China. This research provides support to the managers and policymakers in understanding the green innovation practices in promoting sustainable development in the manufacturing industry.