Search

The present study explores the effect of supply chain integration on the operational performance of an internet-based online business based in China. The study is based on primary data collected through a questionnaire distributed to supply chain professionals of the stated companies. After distributing the questionnaire and collecting the responses, an exploratory factor analysis is conducted to validate the instrument. Afterward, the confirmatory factor analysis (CFA) analysis is conducted, and finally, the structural equation modeling (SEM) technique is used to determine the validity of the research hypotheses. The results indicate that integrating different aspects of the supply chain positively impacts the operating performance, improving the financial performance of the companies involved in the integration process. [ABSTRACT FROM AUTHOR]

The discussion on employee burnout (BOT) has existed in academic literature for a long time. While BOT was identified as a personal issue, there is a lack of a system approach solution. In this regard, a milestone was achieved in 2019 when the World Health Organization (WHO) introduced a new definition of BOT, recognising it as an occupational phenomenon, thereby placing a greater responsibility on organisational leadership to manage it. Since then, different leadership models have been proposed by scholars to reduce the effect of BOT in an organisation. Humble leadership (HL), as a people-first approach, has recently gained importance in organisational management literature. Studies have indicated that HL significantly influences different employee outcomes. However, research on the significance of HL to mitigate BOT of employees was scarce—similarly, on the underlying mechanisms of how and why. While HL has the potential to reduce BOT in an organisation, little or no research has studied it. Acknowledging these knowledge gaps, the basic aim of this study is to enrich the existing body of knowledge by proposing HL as an effective organisational management strategy to reduce the effect of BOT in the healthcare sector. The study introduces two mediators, work engagement (WREN) and subjective wellbeing (SUBW), to explain the underlying mechanism between HL and BOT. The conditional indirect role of altruism (ALM) was also tested. The data were obtained from hospital employees by employing a survey method (questionnaire, n = 303). Structural equation model (SEM) was considered for testing the hypothesised model to study the interrelationships between variables. The results confirmed that the manifestation of HL in an organisation reduces BOT significantly, and WREN and SUBW mediate this relationship. The study also demonstrates the buffering effect of ALM in the above-proposed relationships. The empirical findings offer multiple contributions in theory and practice, among which the most important one was to realise the profound importance of HL in reducing the effect of BOT in healthcare management. [ABSTRACT FROM AUTHOR]

The hospitality sector, especially the hotel business, is at a crossroads. Dynamic business environments, rivalries, and isomorphisms in service operations are significant challenges for hotel enterprises. Fostering employee creativity is undoubtedly something that can well position a hotel in the face of competition. Research shows that corporate social responsibility (CSR) perceptions of employees for an enterprise can motivate them to be engaged in creativity. At the same time, it has also been mentioned that corporate leaders could significantly influence the behavior of employees. Nevertheless, employee creativity in a CSR framework has not been well-explored in a hospitality context. Moreover, the role of leadership, especially inclusive leadership styles, has been less discussed to spur employee creativity from a CSR perspective. To bridge the above knowledge gaps, this study investigates the relationship between CSR and employee creativity with the mediating effect of inclusive leadership in the hotel industry of a developing economy. Moreover, the conditional indirect effect of employee polychronicity was also tested in the proposed mediated relationship. For data collection, an adapted questionnaire was taken into consideration by employing a paper–pencil method (n = 427). A hypothetical model was refined and validated through structural equation modeling (SEM). The results confirmed that CSR can drive employee creativity significantly, and inclusive leadership partially mediates this relationship. It was also realized that polychronicity has a significant conditional indirect effect on the above-mediated relationship. These outcomes contribute to improvements in the hotel management, as well-designed CSR activities both improve the hotel's image as an ethical enterprise and increase creativity among employees. [ABSTRACT FROM AUTHOR]

Tourism and hospitality have been recognized as leading economic sectors globally. Before the outbreak of COVID-19, it was estimated that the tourism and hospitality sector was growing by around 4% each year. Although the economic-efficiency-led hypothesis of the tourism and hospitality sector is strong, there is another perspective related to tourism and hospitality. That is, tourism and hospitality are not as "green" as they were supposed to be. Indeed, this sector is known for its outsized carbon footprint. It is estimated that, if not managed efficiently, the GHG contribution of the tourism sector will grow in the future. Specifically, the hotel business accounts for 1% of total global greenhouse gas emissions (GHG), which is huge. Responding to these significant issues, this study investigates the relationship between the corporate social responsibility (CSR) activities of a hotel enterprise and employees' pro-environmental behavior (PEB). The mediating role of environmental-specific transformational leadership (ESTFL) and the moderating role of green perceived organizational support (GPOS) were also tested in the above relationship. The data were collected by the employees through a self-administered questionnaire. The hypothesized relations were statistically investigated by using structural equation modeling (SEM). The findings revealed that CSR activities of a hotel not only influence employees' PEB directly, but the mediating role of ESTFL was also significant. At the same time, the conditional indirect role of GPOS was also confirmed. This study offers different theoretical and practical insights, which have been discussed in detail. [ABSTRACT FROM AUTHOR]

Despite the growing academic interest in transformational leadership and employee creativity, the banking sector has not yet received enough consideration. Mostly, the banking sector was assumed to be an inappropriate setting for employee creativity as it is a tightly supervised and controlled segment of an economy. Nevertheless, some research studies in advanced nations emphasized the significance of employee creativity in a banking context. However, the case of developing countries (e.g., Pakistan) has remained an understudied area. Against this background, the objective of this study was to examine the relationships between transformational leadership (TL), perceived organizational support (POS), and employee creativity (EC) through work engagement (WE). Some private banks were selected, situated in a large metropolitan city, with data collected for the present research by a self-administered questionnaire. The structural equation modeling (SEM) technique was employed to analyze data. It was observed that TL and POS induce EC, whereas WE mediated these relationships. These findings may help policymakers of the banking industry to improve employee creativity through WE. [ABSTRACT FROM AUTHOR]

Agriculture is critical for meeting the needs of the world's population, in terms of food production. As a result, it has become a significant contributor to economic growth. According to various studies, agricultural production is one of the most widely recognized sources of greenhouse gas (GHG) emissions globally. This study explores the causal link between aggregate energy consumption resources, trade liberalization, CO2 emissions, and modern agriculture in selected ASEAN nations from 2000 to 2020, through the use of panel FMOLS data from the United Nations Development Program (fully modified ordinary least square). According to scientific research, the value addition of agricultural commodities helps to reduce CO2 emissions in polluted countries such as the United States. In addition, it was revealed that the quantity of CO2 released per unit of energy spent was positively associated with the amount of energy consumed. The reduction of CO2 emissions is possible in nations where environmental pollution is reducing due to trade liberalization. Although fossil fuels have increased CO2 emissions, research has shown that adopting renewable energy can help mitigate environmental damage. Revenues and productivity in agriculture are increased due to climate-smart agricultural-favored institutions, while greenhouse gas emissions are reduced. As an example of renewable energy, new energy resources may contribute to the preservation of a clean and healthy environment. The use of renewable energy in agriculture reduces the dependency on fossil fuels, which is beneficial for farmers. Trade policy, on the other hand, may stimulate the movement of money and technology, in order to specialize in economies of scale and manufacturing. It is imperative that ASEAN countries examine policies that will improve living standards, while also protecting the environment. This includes measures that will stimulate agricultural sector production and create active marketplaces for international trade [ABSTRACT FROM AUTHOR]

The phenomenon of corporate social responsibility (CSR) is an ever-evolving concept due to its multidimensionality. However, a plethora of studies have investigated CSR to achieve different organizational-related objectives, and its potential link to shape employee's extra-role behavior, especially employee pro-environmental behavior (EB) in the era of Industry 4.0, is underexplored in the literature. To bridge this gap, the current study aims to explain the relationship between CSR and EB with the mediating role of ethical leadership (EL) in the banking sector of Pakistan. The data of the current survey were collected (n = 459) from different banking employees within the city of Lahore through a self-administered questionnaire (paper–pencil technique). The hypotheses were validated through the structural equation modeling (SEM) technique in AMOS. The empirical results of the current study confirmed that CSR positively relates to EB, and EL partially mediates this relationship. These findings are helpful for professionals to realize the significance of CSR and EL to shape EB in order to mitigate the environmental footprint of an organization. [ABSTRACT FROM AUTHOR]

This study aims to develop a new approach based on machine learning techniques to assess sustainability performance. Two main dimensions of sustainability, ecological sustainability, and human sustainability, were considered in this study. A set of sustainability indicators was used, and the research method in this study was developed using cluster analysis and prediction learning techniques. A Self-Organizing Map (SOM) was applied for data clustering, while Classification and Regression Trees (CART) were applied to assess sustainability performance. The proposed method was evaluated through Sustainability Assessment by Fuzzy Evaluation (SAFE) dataset, which comprises various indicators of sustainability performance in 128 countries. Eight clusters from the data were found through the SOM clustering technique. A prediction model was found in each cluster through the CART technique. In addition, an ensemble of CART was constructed in each cluster of SOM to increase the prediction accuracy of CART. All prediction models were assessed through the adjusted coefficient of determination approach. The results demonstrated that the prediction accuracy values were high in all CART models. The results indicated that the method developed by ensembles of CART and clustering provide higher prediction accuracy than individual CART models. The main advantage of integrating the proposed method is its ability to automate decision rules from big data for prediction models. The method proposed in this study could be implemented as an effective tool for sustainability performance assessment. [ABSTRACT FROM AUTHOR]

The main purpose of the current study is to investigate if tourism affects economic growth of China. The data set has been acquired from the Beijing Municipal Bureau of Statistics, and the time span of the data set takes into account a 20-year time period, from 2000 to 2019. To determine the strength of the above-mentioned relationship previous models that have been used for this research are mainly VAR (vector auto-regression) and VECM (vector error correction) models. The VAR and VECM models have been conducted together with the Granger causality test. The internal revenue generated from tourism-related activities is taken as being the main indicator for the tourism industry, while economic growth is determined by GDP (gross domestic product). We support the above-mentioned notion, as we found that a strong relationship exists between the development of the tourism industry and economic growth. Moreover, our analysis also indicates that this industry has a major impact on long-term economic growth in the region as well. This study thus provides further support to the existing literature on the topic of tourism and the impact that tourism-related activities have upon economic development and growth. The existence and the impact of tourism-related activities upon long-term economic growth were confirmed by the results of the VAR models. At the same time, the unidirectional results of VECM models have confirmed the existence of economic growth in the short term. In our case, the cardinal relationship between the development of the tourism industry and the economic growth in the Beijing region of China have managed to provide strong empirical support to the earlier stated notions and to the literature alike. [ABSTRACT FROM AUTHOR]

Global warming is one of the most important challenges nowadays. Sustainability practices and technologies have been proven to significantly reduce the amount of energy consumed and incur economic savings. Sustainability assessment tools and methods have been developed to support decision makers in evaluating the developments in sustainable technology. Several sustainability assessment tools and methods have been developed by fuzzy logic and neural network machine learning techniques. However, a combination of neural network and fuzzy logic, neuro-fuzzy, and the ensemble learning of this technique has been rarely explored when developing sustainability assessment methods. In addition, most of the methods developed in the literature solely rely on fuzzy logic. The main shortcoming of solely using the fuzzy logic rule-based technique is that it cannot automatically learn from the data. This problem of fuzzy logic has been solved by the use of neural networks in many real-world problems. The combination of these two techniques will take the advantages of both to precisely predict the output of a system. In addition, combining the outputs of several predictors can result in an improved accuracy in complex systems. This study accordingly aims to propose an accurate method for measuring countries’ sustainability performance using a set of real-world data of the sustainability indicators. The adaptive neuro-fuzzy inference system (ANFIS) technique was used for discovering the fuzzy rules from data from 128 countries, and ensemble learning was used for measuring the countries’ sustainability performance. The proposed method aims to provide the country rankings in term of sustainability. The results of this research show that the method has potential to be effectively implemented as a decision-making tool for measuring countries’ sustainability performance. [ABSTRACT FROM AUTHOR]