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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.

This study aims to uncover marketing strategies to restore a positive image in times of pandemic crisis to bring tourists back to a popularly affected tourism city in China, Wuhan in Hubei Province. The paper argues that the process of restoring city image requires understanding the perceptions of Generation Z, a segment of the population who have a high propensity to travel after COVID-19.

This study employed a constructivist grounded theory approach to explore the perspectives of China’s Generation Z consumers of Wuhan’s future image to restart tourism. The data is collected through semi-structured interview of 29 respondents and analyzed with the initial, focused and theoretical coding process.

Start by narrowing the gap between projected and perceived image, the findings suggest that Generation Z could be pulled to visit Wuhan city through four core products such as dark tourism activities, special-interest leisure, heroism and storytelling.

The destination image restoration framework after health-related crisis is creatively proposed. It combines the analysis of crisis and urban characteristics from the perspective of the target audience (Generation Z) and provides specific strategies to restore the tourism city image from cognitive, affective and conative dimensions. Significantly, two novel characteristics of Generation Z (i.e. lighthearted and patriotic) emerge in addition to the typical features of this generational cohort. This study also found a high preference for a technologically oriented type of attraction that reverses the morbid COVID-19 memories into an entertainment tool.

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

This study examined the factors influencing willingness-to-repurchase for each class of airline service, and integrate the constructs of service quality, satisfaction and willingness-to-repurchase which were rooted on Engel-Kollat-Blackwell (EKB) model. The study focuses on the domestic and international arrival of passengers at Murtala Muhammed International Airport in Lagos and Nnamdi Azikwe International Airport in Abuja. Information was gathered from domestic and foreign passengers who had post-purchase experience and had used the airline's services more than once. The survey data were obtained concurrently from arrival passengers at two major international airports using an electronic questionnaire through random and purposive sampling techniques. The data was analysed using the ordinal logit model and structural equation model. From the 606 respondents, 524 responses were received but 489 responses were valid for data analysis and reporting and were obtained mostly from economy and business class passengers. The study found that the quality of seat pitch, allowance of 30 kg luggage permission, availability of online check-in 24 hours before the departing flight, quality of space for legroom between seats, and the quality of seats that can be converted into a fully flatbed are the major service factors influencing willingness-to-repurchase economy and business class tickets. Also, it was found that passengers' willingness to repurchase is influenced majorly by service quality, but not necessarily influenced by satisfaction. These results reflect the passengers' consciousness of COVID-19 because the study was conducted during the heat of COVID-19 pandemic. Recommendations were suggested for airline management based on each class.

This paper highlights the opportunities and challenges for family firms in managing Generation Z (Gen-Z) employees. This perspective article explores several considerations for family firms in managing their Gen-Z employees and the potential implications for their socioemotional wealth (SEW).

The authors provide a brief review of what is known about the values/work habits of Gen-Z employees and attracting, retaining and managing nonfamily employees in family firms.

The unique values, motivations and working styles of Gen-Z employees suggest the need for family business leaders to adopt a different approach to managing these employees. A focus on Gen-Z’s psychological contract, technological savviness and entrepreneurial orientation is provided with respect to how they can be managed.

The authors suggest the importance of approaching NFEs as a heterogenous group and offer avenues for future research with prospective research questions to better understand nonfamily Generation Z employees’ place in the family firm.

The purpose of this paper is to demonstrate the impact of the welding sequence on the substrate plate distortion during the wire and arc additive manufacturing (WAAM) process. This paper also aims to show the capability of finite element simulations in the prediction of those thermally induced distortions.

An experiment was conducted in which solid aluminum blocks were manufactured using two different welding sequences. The distortion of the substrates was measured at predefined positions and converted into bending and torsion values. Subsequently, a weakly coupled thermo-mechanical finite element model was created using the Abaqus simulation software. The model was calibrated and validated with data gathered from the experiments.

The results of this paper showed that the welding sequence of a part significantly affects the formation of thermally induced distortions of the final part. The calibrated simulation model was able to capture the different distortion behavior attributed to the welding sequences.

Within this work, a simulation model was developed capable of predicting the distortion of WAAM parts in advance. The findings of this paper can be used to improve the design of WAAM welding sequences while avoiding high experimental efforts.

This paper examines the influence of different types of political connections and political uncertainty on earnings credibility in Pakistan. Based on discernible differences, connected firms are grouped into civil connected and military connected firms.

The authors provide evidence concerning the earnings credibility incentives of groups of political connected firms and report that their incentives are significantly different. The findings remain robust to alternate methods of earnings credibility.

The findings evidence that civil (military) connected firms report less (more) credible earnings than the control group. High political uncertainty reduces the credibility of earnings. Results for the interaction of political connections and political uncertainty variables are not significant.

The paper investigates just one aspect of Pakistan's political economy, i.e. credibility of earnings; thus, it requires to be cautious on part of readers and policymakers. To reach a clearer conclusion, earnings credibility should be ex amined in the larger context, i.e. in conjunction with rent extractions, etc. A possible extension of the paper can be to investigate the channels of rent extractions used by the two types of connected firms.

The paper has contribution for policymakers as well as users of general purpose financial reports. The findings indicate that the users of general purpose financial reports should be more careful in the use of financial information during political uncertain periods and also of politically connected firms. Furthermore, policymakers should keep the larger context at the forefront while attempting to strengthen the enforcemnet regime.

This paper adds to extant political connections literature by identifying two types of politically connected firms and report that both groups have divergent financial reporting incentives. Furthermore, political uncertainty reduces the credibility of earnings.

The purpose of this paper is to examine the antecedents of organizational ambidexterity of foreign ventures in an emerging market. Organizational ambidexterity, the simultaneous pursuit of exploration and exploitation, represents a key innovation strategy. Yet, the driving factors of such innovation strategies for foreign ventures competing in emerging markets have been underresearched. In this study, unpacking the construct of organizational ambidexterity into two dimensions (i.e. the combined dimension [CD] and the balance dimension [BD]), the authors aim to investigate how firm-level and industry-level factors drive foreign ventures in pursuing exploration and exploitation and maximizing the benefits of both.

This study adopts the hierarchical multiple regression approach using a sample of foreign ventures operating in high-tech manufacturing industries in China.

The authors find that the firm-level factor of strategic flexibility leads positively to the CD of organizational ambidexterity, whereas the industry-level factor of technological turbulence has a significantly positive impact on the BD.

This study provides important insights into the driving factors of organizational ambidexterity for foreign ventures competing in emerging markets.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.