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The purpose of this study is to examine the effects of leader mindfulness on employee safety behaviors by focusing on the mediating role of employee resilience and the moderating role of perceived environmental uncertainty.

The authors surveyed 248 employees in the high speed railway company of China in three waves with a two-week interval. Hierarchical regression analysis was used to test the hypotheses. The mediating effects and the moderated mediation effects are further tested with bias-corrected bootstrapping method.

Leader mindfulness positively affects employee safety compliance and safety participation, and these relationships were mediated by employee resilience. Perceived environmental uncertainty moderated the effects of leader mindfulness on employee resilience and the indirect effects of leader mindfulness on safety behaviors via employee resilience.

The findings elucidate the significance of leader mindfulness in promoting employee safety behaviors in the workplace.

This study aims to analyze the determinants influencing Chinese manufacturing companies in implementing lean manufacturing (LM).

The determinants to be explored in this study consist of technological, organizational and environmental (TOE) dimensions. A questionnaire survey was conducted on Chinese manufacturing companies, and 208 samples were analyzed.

The findings show that the relative advantage of LM and organizational support have significantly positive effects on Chinese manufacturing firms’ adoption of LM. The complexity of LM, quality of human resources, organizational readiness, customer pressure, international situation, governmental support and environmental uncertainty do not have significant effects.

This paper contributes to the literature by using the TOE model to explore the factors influencing LM adoption in the Chinese manufacturing industry.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

Growth optimism, which describes the expected future growth of a firm, is an important but underexplored construct in strategy. This paper aims to assess the planning antecedents of such growth optimism by using a large Australian sample of small enterprises.

The authors use a secondary data set, gathered among Australian small to medium enterprises (SMEs), by the Australian Bureau of Statistics (ABS). The analysis adopts a regression approach including a mediated and a non-mediated path to explore the direct and indirect effects of strategic planning and budgetary planning and management on expected future revenues.

This paper assesses the implications of concurrent strategic planning and financial management dynamic capabilities on anticipated future revenue growth, an important predisposition dynamic capability. The authors note that this configuration of actions and predisposition aligns closely with the necessary requirements for growth. The findings suggest that firms that use strategic planning and robust budget planning and monitoring processes exhibit higher optimism about future sales growth and firms that effectively configure these planning activities with market development tend to exhibit higher growth and more growth optimism.

In terms of theoretical contributions, the paper strongly supports the formality view in the formal/informal debates associated with effectuation strategies. The authors suggest that appropriate strategic and budgetary planning and control systems act as a counterbalance to organisational confusion and managerial capriciousness, leading to improved confidence among managers and their employees regarding future resource commitments and plans.

The findings of the paper are potentially important for both managers and policy makers. For managers seeking to grow their future sales, planning is shown to be an important antecedent activity. The presence of financial and strategic planning may predispose firms to make important investment decisions that drive future growth. Also, a better understanding of the firm’s current and future strategic and financial position may be evidence of effective firm management, a situation that, in turn, drives growth.

In terms of social and policy implications, the data gathered for the survey by the ABS forms a valuable collection of information in relation to business practices. Australian firms are required by law to regularly report budget plans and outcomes. The research suggests that this data can inform policy initiatives, particularly in relation to programmes that may assist small and young firms to undertake prospective strategic and budgetary planning.

To the best of the authors’ knowledge, this is the first paper to investigate the particular configuration of strategic and financial planning and anticipated sales growth in the SME context.

The primary aim of this research was to investigate the mediating effect of the decision-making structure on the relationship between perceived environmental uncertainty and hospital performance.

Online and manual survey questionnaires were used to collect data in this study. The target population of this study consists of all middle managers within 11 COVID-19 referral hospitals in Surabaya. A total of 189 responses were collected, however, 27 incomplete responses were excluded from the final dataset. Data was analyzed using SEM-PLS.

The study's findings indicate that decision-making structure plays a role in mediating the link between perceived environmental uncertainty and hospital performance assessed via the Balanced Scorecard, highlighting the significance of flexible decision-making processes during uncertain periods. Moreover, based on our supplementary test, respondents' demographic characteristics influence their perceptions of hospital performance.

Hospital administrators can consider the significance of decision-making structures in responding to environmental uncertainties like the COVID-19 pandemic. By fostering adaptable decision-making processes and empowering middle managers, hospitals may enhance their performance and resilience in challenging situations. Additionally, based on supplementary tests, it is found that differences in the perception of the three Balanced Scorecard perspectives imply that hospitals categorized as types A, B, C, and D should prioritize specific areas to improve their overall performance.

This research adds substantial originality and value to the existing body of knowledge by exploring the interplay between decision-making structures, environmental uncertainty, and hospital performance. It contributes to the literature by specifically focusing on the Covid-19 pandemic, a unique and unprecedented global crisis.

Purpose: This study examines the effect of uncertainties on the hospitality industry from different perspectives across the globe. The hospitality industry faces several contemporary issues and challenges that have the potential to impact its growth and development. This study aims to analyse the current problems and uncertainties in the hospitality sector.

Need for the Study: The hospitality industry plays a significant role in the global economy with various services, including accommodation, food and beverage, events, and tourism. However, the sector faces several contemporary issues and challenges that have the potential to impact its growth and development. This study provides an overview of the most significant problems and challenges facing the hospitality industry today.

Methodology: A systematic literature review was conducted to identify and synthesise relevant studies on the effect of uncertainties issues on the hospitality industry. A systematic search of the Web of Science and Scopus databases was conducted to determine relevant studies published between 2010 and 2021. Studies were screened and selected based on pre-defined inclusion and exclusion criteria. A thematic analysis was performed to categorise the uncertainties and issues in the hospitality industry.

Findings: The study identified several uncertainties and issues facing the hospitality industry, including the pandemic uncertainties, financial crisis, whether positive and negative impacts, terrorism attacks on hotels and tourist places, uncertainties in government policies, situational risks like uncertainties, ambiguity, cultural differences, changes in tourist preferences and changing habits of the tourist.

Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.

The problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.

For the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.

The proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.

This research aims to investigate how manufacturing flexibility can address the challenges of an ever-changing and unpredictable business environment in Bangladesh’s labor-intensive ready-made garment (RMG) industry, which is underserved and situated in a developing country.

Using Partial Least Square Structural Equation Modeling, this study empirically evaluated the relationships between manufacturing flexibility, environmental uncertainty and firm performance. The analysis utilized 320 survey responses from potential RMG experts, representing 95 organizations.

The study achieved a decision-making model for implementing manufacturing flexibility in the RMG industry of Bangladesh with acceptable model fit criterion. The research pinpointed that workforce flexibility plays the maximum mediating among different types of manufacturing in coping with demand and supply uncertainty in the RMG sector.

The study made valuable contributions to theoretical and practical knowledge in the context of manufacturing flexibility in Bangladesh’s RMG and other underserved labor-intensive sectors in developing economies. It suggests that managers should shift from defensive and risky business strategies to more aggressive and proactive approaches by utilizing workforce flexibility resources adaptively to enhance manufacturing capabilities and align with dynamic market demand. Additionally, the study offers recommendations for future research to build upon its findings.

This study is unique in its approach because it presents a decision model for implementing manufacturing flexibility in a labor-intensive industry in a developing economy, specifically the RMG industry in Bangladesh, whereas previous research has primarily focused on high-tech industries in developed economies.

The outbreak of COVID-19 has caused a slowdown of economic activity across the globe, which has resulted in high levels of disruption to labour markets. This study seeks to examine how the outbreak of COVID-19 has impacted the search strategies of students seeking for an internship, and whether these have changed since the start of the pandemic. The study utilises the strength of weak ties hypothesis, social capital theory and status attainment theory to explore the changes in securing a position since the outbreak of COVID-19.

This study draws on data from two cohorts of MBA students seeking to secure internships: one before the outbreak and one during. A multinomial regression is employed to examine how students have used network ties to secure internships and how this has changed since the outbreak of COVID-19.

The multinomial regression results indicate that there was little difference in the strategies employed by students before the crisis compared to those that secured them during, potentially indicating that students are unwilling to deviate from typical job search strategies, especially in times of uncertainty.

This study provides insights into how network ties are used by job seekers during a period of economic and environmental uncertainty.