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Sexual harassment on public transport puts women at risk of mental health problems, apart from disrupting their lives and the harmful social consequences. This is especially the case for Pakistani women, for whom sexual harassment has been on the rise for the past decade. This study aims to explore how Pakistani women use strategies to cope with sexual harassment when using public transport and its mediating role in their issues with mental health.

Given that the data collection task on such a culturally sensitive topic was crucial, a mobile application for anonymized data collection was used, which appeared to be an effective strategy. Using the mobile application, 1,054 women who use public transport submitted their responses; however, the analysis is based on 250 usable responses. Their experience of harassment was measured using the Sexual Harassment Experience Questionnaire, their mental health using the Depression Anxiety Stress Scales and their coping strategies by the Brief Cope Inventory.

The results indicate that adaptive coping is a significant negative mediator between sexual harassment and mental well-being, whereas maladaptive coping is non-significant. Adaptive coping, i.e. “Acceptance” to admit the reality that the problem exists with all, and “Religion” to seek help spiritually to deal with the problem. Unfortunately, the findings show no suitable coping means to deal with the impact of sexual harassment on women who travel on public transport. This study also illustrates that using the right technologies can encourage participants to submit responses for culturally sensitive topics.

This study provides insight into the experience of street harassment in Pakistani women and how it is related to mental health. This study also explores the role of adaptive and maladaptive coping as an intervening variable between street harassment and mental health.

The COVID-19 pandemic and recent disruptive events are affecting firms’ operations and supply chain networks on a large scale, causing disturbances in supply, demand, production and logistics activities. Although supply chain resilience (SCR) research has received large attention in recent years, the purpose of this paper is to offer an original contribution by exploring how complex configurations and interactions between SCR strategies and capacities can lead to resilience.

This study investigates the configurations of SCR strategies and capacities using a fuzzy-set qualitative comparative analysis.

First, the findings reveal different SCR strategy configurations through the lens of absorptive, reactive and restorative capacities to achieve resilience. Second, this study applies the contingent resource-based view (CRBV) perspective to interpret how organizations can achieve resilience before, during and after a disruptive event. Third, it offers an analysis of different groups of organizations, based on the adoption of different SCR strategies and capacities.

This study identifies a set of equifinal SCR strategies and capacity configurations that can be implemented to cope with a disruptive event and lead to resilience. It also enriches the research addressing the consecutive phases of SCR investments, developing the CRBV perspective. In our results, five solutions describe organizations that invest in absorptive capacities, representing an ex ante readiness.

Bayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been developed for adaptive experiment design of the integration points. However, those sequential design strategies also prevent BC from being implemented in a parallel scheme. Therefore, this paper aims at developing a parallelized adaptive BC method to further improve the computational efficiency.

By theoretically examining the multimodal behavior of the PVC function, it is concluded that the multiple local maxima all have important contribution to the integration accuracy as can be selected as design points, providing a practical way for parallelization of the adaptive BC. Inspired by the above finding, four multimodal optimization algorithms, including one newly developed in this work, are then introduced for finding multiple local maxima of the PVC function in one run, and further for parallel implementation of the adaptive BC.

The superiority of the parallel schemes and the performance of the four multimodal optimization algorithms are then demonstrated and compared with the k-means clustering method by using two numerical benchmarks and two engineering examples.

Multimodal behavior of acquisition function for BC is comprehensively investigated. All the local maxima of the acquisition function contribute to adaptive BC accuracy. Parallelization of adaptive BC is realized with four multimodal optimization methods.

The present paper aims to address challenges associated with path planning and obstacle avoidance in mobile robotics. It introduces a pioneering solution called the Bi-directional Adaptive Enhanced A* (BAEA*) algorithm, which uses a new bidirectional search strategy. This approach facilitates simultaneous exploration from both the starting and target nodes and improves the efficiency and effectiveness of the algorithm in navigation environments. By using the heuristic knowledge A*, the algorithm avoids unproductive blind exploration, helps to obtain more efficient data for identifying optimal solutions. The simulation results demonstrate the superior performance of the BAEA* algorithm in achieving rapid convergence towards an optimal action strategy compared to existing methods.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bidirectional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bi-directional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm.

The rigorous evaluation of our proposed BAEA* algorithm with the BAA* algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The originality of this paper lies in the introduction of the bidirectional adaptive enhancing A* algorithm (BAEA*) as a novel solution for path planning for mobile robots. This algorithm is characterized by its unique characteristics that distinguish it from others in this field. First, BAEA* uses a unique bidirectional search strategy, allowing to explore the same path from both the initial node and the target node. This approach significantly improves efficiency by quickly converging to the best paths and using A* heuristic knowledge. In particular, the algorithm shows remarkable capabilities to quickly recognize shorter and more stable paths while ensuring higher success rates, which is an important feature for time-sensitive applications. In addition, BAEA* shows adaptability and robustness in dynamically changing environments, not only avoiding obstacles but also respecting various constraints, ensuring safe path selection. Its scale further increases its versatility by seamlessly applying it to extensive and complex environments, making it a versatile solution for a wide range of practical applications. The rigorous assessment against established algorithms such as BAA* consistently shows the superior performance of BAEA* in planning shorter paths, achieving higher success rates in different environments and cementing its importance in complex and challenging environments. This originality marks BAEA* as a pioneering contribution, increasing the efficiency, adaptability and applicability of mobile robot path planning methods.

This study aims to analyze the perceptions of smallholder farmers on climate change and events and further explores climate change adaptation strategies and associated challenges. The findings provide useful information for enhancing the adaptive capacity of smallholder farmers to adjust to climate-related hazards and improve their resilience and disaster preparedness in northern Ghana.

This study uses a multistage sampling procedure and sample size of 150 farmers, the Binary Probit Model (BPM), to identify and examine the determinants of climate change adaptation strategies adopted by smallholder farmers. Also, the constraints of adaptation were analyzed using Kendall’s coefficient of concordance.

The results from the BPM and statistics of Kendall’s coefficient revealed that the farm risk level, ability to adapt, farmer’s income, age, farming experience, climate change awareness and extension visits were factors that significantly influenced the adaptation strategies of smallholder farmers (in order of importance). The majority (60%) of the farmers ranked farm risk level as the major constraint to adopting climate change strategies.

The findings of this study enhance understanding on access to relevant and timely climate change adaptation information such as an early warning to farmers during the start of the farming/rainy season to support their adaptive responses to climate change.

The purpose of this study was to investigate work-related adaptive performance from a longitudinal process perspective. This paper clustered specific behavioral patterns following the introduction of a change and related them to retentivity as an individual cognitive ability. In addition, this paper investigated whether the occurrence of adaptation errors varied depending on the type of change content.

Data from 35 participants collected in the simulated manufacturing environment of a Research and Application Center Industry 4.0 (RACI) were analyzed. The participants were required to learn and train a manufacturing process in the RACI and through an online training program. At a second measurement point in the RACI, specific manufacturing steps were subject to change and participants had to adapt their task execution. Adaptive performance was evaluated by counting the adaptation errors.

The participants showed one of the following behavioral patterns: (1) no adaptation errors, (2) few adaptation errors, (3) repeated adaptation errors regarding the same actions, or (4) many adaptation errors distributed over many different actions. The latter ones had a very low retentivity compared to the other groups. Most of the adaptation errors were made when new actions were added to the manufacturing process.

Our study adds empirical research on adaptive performance and its underlying processes. It contributes to a detailed understanding of different behaviors in change situations and derives implications for organizational change management.

Drawing on the conservation of resources theory, this study aims to identify the mediating effects of depersonalization and resilience on the relationship between customer incivility and organizational citizenship behavior (OCB). It further posits that these indirect effects vary depending on the caring climate and achievement orientation.

A field survey among 622 service employees (Study 1) and a three-wave field survey of 315 service employees and their managers (Study 2) from various service organizations were conducted.

This study confirms that depersonalization operates as a negative mediator in the relationship between customer incivility and OCB. Simultaneously, resilience emerges as a positive mediator, underscoring the contrasting pathways through which customer incivility affects OCB. Furthermore, a caring climate plays a pivotal role in mitigating the detrimental impact of depersonalization on OCB and weakening the positive impact of resilience on OCB. Additionally, this study identifies achievement orientation as a significant moderator between customer incivility and resilience.

This study advances theoretical foundations by investigating depersonalization and resilience as critical mediators in the intricate relationship between customer incivility and OCB. It goes beyond the conventional understanding of customer incivility’s impact by shedding light on the dual roles of a caring climate, demonstrating its potential to alleviate both positive and negative consequences of customer incivility. Moreover, its identification of achievement orientation as a moderator adds a novel dimension to the discourse, emphasizing the need for tailored strategies to harness employee resilience in the face of customer incivility.

This article focusses on the hybrid strategy, a simultaneous combination of cost leadership and differentiation strategy. The study aims to examine the impact of hybrid strategy on firm performance through its anticipated positive effects on process and product innovation. In addition, we study the moderating role of adaptive capacity in the direct relationships of hybrid strategy with process and product innovation.

Structural equation modelling was used to analyse 1,842 Spanish firms with fewer than 250 employees. We randomly selected small and medium-sized enterprises (SMEs) operating in Spain from the Spanish Central Business Directory (2021) database. The overall sample design was based on stratified sampling.

We found that hybrid strategy is positively related to firm performance and to process and product innovation. Additionally, in firms implementing hybrid strategies, process innovation fostered firm performance. Finally, adaptive capacity strengthened the relationships of hybrid strategy with process and product innovation. This sheds light on how and when hybrid strategy is most effective in fostering SME performance.

We highlight that SMEs need to establish strategies that use diverse resources and capabilities and not just generate competitive advantage using one strategy (cost leadership or differentiation strategy). This requires an agile and flexible systems and structures.

Our research provides novel results by proposing the adoption of hybrid strategies instead of pure strategies (cost leadership and differentiation strategy) as a way for SMEs to survive during crises. Unlike “stuck in the middle” strategies, our study demonstrates the importance of hybrid strategies in a comprehensive model that links them to innovation and firm performance, with adaptive capacity being a determining factor.

Pandemics are frequent events, and the impact of each pandemic makes a strong and long-term effect on companies and markets. Given the potential impact of the COVID-19 pandemic, it is important to investigate the crisis from a different perspective to know how companies have sustained growth in markets. The purpose of this paper is to understand how profit-oriented customer-centric companies (small, medium and large) have responded and adapted to COVID-19 crisis, using the complexity theory.

Drawing upon the complexity theory, a humble attempt is made to develop theoretical propositions by conceptualizing companies as complex adaptive systems. The paper examines companies from three dimensions (i.e. internal mechanism, environment and coevolution).

Companies self-organize, emerge into new states and become adaptive to the changing environment. Companies create knowledge to understand the dynamic anatomy and design survival and growth strategies during and post COVID-19 era. Complex adaptive systems perspective provides companies with insights to deal with complex issues raised due to COVID-19 pandemic. They can handle the impact of pandemic efficiently with complex adaptive systems by developing and implementing appropriate strategies post-COVID-19.

The study reveals how companies evolve and emerge into as complex adaptive systems to adapt themselves to the highly dynamic environment, which are uncertain, unpredictable, nonlinear and multifaceted, in the context of COVID-19. Implications for theory and practice of viewing companies as complex adaptive systems and coevolving structures in the COVID-19 context are discussed.

This study aims to investigate the adaptation strategies they practice and the factors that influence their use of adaptation strategies.

The mixed-method sequential explanatory design was used to triangulate the data collected. Multistage sampling was used to select 400 sampled households for household surveys. Eight focus groups, each with eight to ten participants, and 24 key informants, were specifically chosen based on their farming experiences. Chi-square tests, one-way ANOVA and a binary logit model were used to analyze the data.

The majority of farmers used simple and low-cost adaptation strategies like changing planting dates, selling livestock and off-farm and nonfarm work. A minority of farmers used advanced adaptation strategies like crop diversification and water harvesting for irrigation. The result further revealed that: the age of the household head, educational status of household heads, farm size, livestock ownership, farming experiences, household income, access to credit and access to climate information significantly influenced the adoption of the adaptation strategies. Public policy should provide water harvesting and irrigation technology, climate-related information and the provision of microcredit facilities to enhance the farmers’ resilience to climate change risks.

Although several studies on climate change adaptation strategies are available, this paper is one of the few studies focusing on a particular agro-ecological zone, an essential precursor to dealing with current and projected climate change in the area. It provides helpful insights for developing successful adaptation policies that improve adaptive capacity and agricultural sustainability in southern Ethiopia’s lowlands.