Crew pairing is the primary cost checkpoint in airline crew scheduling. Because the crew cost comes second after the fuel cost, a substantial cost saving can be gained from effective crew pairing. In this paper, the cockpit crew pairing problem (CCPP) of a budget airline was studied. Unlike the conventional CCPP that focuses solely on the cost component, many more objectives deemed to be no less important than cost minimisation were also taken into consideration. The adaptive non-dominated sorting differential algorithm III (ANSDE III) was proposed to optimise the CCPP against many objectives simultaneously. The performance of ANSDE III was compared against the NSGA III, MOEA/D, and MODE algorithms under several Pareto optimal measurements, where ANSDE III outperformed the others in every metric.

The proliferation of artificial intelligence (AI) has emerged as a critical metric for assessing a country's technological advancement, but also for regional economic coordination and high-quality development in China. Based on panel data collected from 31 provinces between 2006 and 2021, this study employs the DEA-Malmquist index model and panel Tobit model to examine the scale, distributional attributes, and influencing factors of AI resource allocation. Results indicate that China's AI resource allocation efficiency has generally increased, with technical efficiency generating a “pull effect” that propels total factor productivity growth rates higher than those attributable to technological progress. Furthermore, AI efficiency in non-coastal regions outstrips that in coastal areas, with total factor productivity growth arising from a substantial increase in technological progress rates. Regional economic development, labor demand, openness to foreign participation, and human capital level exert pivotal roles in enhancing AI resource allocation efficiency. Based on these findings, we suggest a set of strategies aimed at enhancing China's AI resource allocation efficiency, including amplifying government guidance, increasing R&D investments, upgrading economic development levels, fostering the development and strengthening of tangible economy, and attracting and nurturing high-quality scientific research talent.

This study investigates the impact of entrepreneurial intentions and competitive factors on sustainable business performance in the exhibition industry. Analyzing recent literature, the research examines how strong entrepreneurial intentions drive the adoption of sustainable practices, innovation, and value creation, while considering the long-term effects of actions. The study also explores the influence of competitive factors, such as innovation capability, market orientation, networking ability, entrepreneurial orientation, and competitive strategies, on an entrepreneur's ability to achieve sustainable performance. The findings suggest that entrepreneurs committed to starting and growing their businesses are more likely to achieve superior financial and non-financial results while contributing to industry sustainability. The study emphasizes the importance of aligning strategies with sustainability goals, developing dynamic capabilities, utilizing competitive intelligence, and leveraging big data analytics to navigate challenges and create value. The research concludes that cultivating strong entrepreneurial intentions and effectively managing competitive factors are crucial for achieving long-term success and sustainable performance in the exhibition industry and beyond.

There is increased adoption of renewable energy, particularly photovoltaic (PV), as a major source of clean and environmentally friendly energy. With the wide application of PV technologies, commonly called solar panels, their appropriate maintenance and cleaning are vital for optimum PV energy generation. The research focuses on exploring the various factors attributed to influence the want, intention and need to use PV panel cleaning robots in Thailand from an institutional management perspective. The study adopted the extended C-TAM-TPB by adding three more variables - Trust in technology, awareness of renewable energy, and environmental concern. A quantitative approach was used, where primary data was collected from PV institutional users. A population sample of 411 respondents was used. The confirmatory factor analysis (CFA) came in handy in evaluating the performance model, with the study's hypotheses being evaluated by the structural equation modeling (SEM). Results indicated that most of the subjective behaviors, perceived behavioral controls, and trust in technology played a key role in determining the intention and need to use solar panel cleaning robots. Perceived usefulness was found to have significant influence towards PV panel adoption. The influence of attitude was mediated by several factors – environmental concern, renewable energy awareness, trust in technology. The study recommended that the institutional users of solar panels should consider investing in knowledge regarding perceived behavioral control, developing confidence in the use of renewable and sustainable energy, and developing trust of the renewable and sustainable energy technologies. This could be achieved through programs such as public awareness, sharing accurate information regarding solar panel cleaning robots, and providing support and after sales support. Educational initiatives to change users' attitudes toward renewable energy technologies were recommended.

This research proposes a heuristic to solve the problem of the location selection of incinerators and the vehicle routing of infectious waste collection for hospitals in the Northeast of Thailand. The developed heuristic is called the Greedy Randomized Adaptive Large Neighborhood Search Procedure (GRALNSP)and applies the principles of the Greedy Randomized Adaptive Search Procedure (GRASP) and Adaptive Large Neighborhood Search (ALNS) in the local search. The results from GRALNSP are compared with those from the exact method processed by the A Mathematical Programming Language (AMPL) program. For small-sized problems, experiments showed that both methods provided no different results with the global optimal solution, but GRALNSP required less computational time. When the problems were larger-scale and more complicated, AMPL could not find the optimal solution within the limited period of computational time while GRALNSP provided better results with much less computational time. In solving the case study with GRALNSP, the result shows that the suitable locations for opening infectious waste incinerators are the locations of Pathum Ratwongsa district, Amnat Charoen province and Nam Phong district, Khonkaen province. An incinerator with a burning capacity of 600 kilogram/hour is used at both locations. The monthly total distances for infectious waste collection are 24,055.24 and 38,401.88 kilometers, respectively, and the lowest total cost is 6,268,970.40 baht per month.

The genetic algorithm (GA) is a natural selection-inspired optimization algorithm. It is a population-based search algorithm that utilizes the concept of survival of the fittest. This study creates a new crossover operator called “Stas Crossover” that is a combination of four crossover operators, including Single point crossover, Two points crossover, Arithmetic crossover, and Scattered crossover, and then presents the performance of this crossover operator. The area size and probability of Stas crossover can be adjusted.GA is used to find the optimal solution for this multi-product and multi-period aggregate production planning (APP) problem, which was used to test the algorithm, which provides optimal levels of inventory, backorders, overtime and regular production rates, and other controllable variables. According to the findings of this study, the benefit of stable crossover is that it allows for more variety in the way offspring are created and increases the opportunity for offspring to obtain good genetic information directly.

This study explores the factors that drive the adoption of live streaming commerce and its effects on business performance. The research finds that relative advantage, streamer expertise, interactivity, consumer pressure, and competitive pressure are key drivers of live streaming commerce adoption, while compatibility and cost-effectiveness are less significant. The study also reveals that live streaming commerce positively impacts both non-financial aspects, such as customer engagement and loyalty, and financial metrics, including sales volume and profitability. The findings offer valuable insights for businesses considering the implementation of live streaming commerce to enhance customer relationships and drive financial success.

This research aims to study the factors influencing customer retention of E-Marketplace businesses by applying the SOR theory and the mediating effect by examining the relationship between value perception, customer engagement, brand loyalty, and customer retention variables by creating a model based on the SOR theory to study the influence of environmental factors that will lead to customer retention mechanisms. The study focused on a sample group of 426 people who have used E-Marketplace services using an online questionnaire as a research tool. The model was analyzed using the CFA and the hypothesis was tested using the SEM analysis. The results showed that stimuli (S), such as customer value perception, had a strong positive influence and a crucial role in the development and creation of a mechanism for assessing individuals' internal feelings (O) on two variables, customer engagement, brand loyalty, and directly influence customer retention. Furthermore, significant evidence also showed that brand loyalty has an important role as a mediator between customer value perception and customer retention, which is the outcome factor (R) of this study. This structural model can explain customer engagement and retention up to 86.50 percent. Therefore, this research has value as a theory and guideline in formulating an operational strategy for E-Marketplace businesses.

A study has been conducted to examine an array of factors such as the factors affecting integrated marketing communication (IMC), entrepreneurship factors, process factors, and basic competitive pressure factors. Based on the perspective of the advertising film production industry, we will examine the service supply chain within the industry. The study is based on the observation and analysis of 310 people working in fields related to the production of advertising films. The research found that all the factors listed above have an immediate impact on the advertising production industry and are significant. There is a strong influence of entrepreneurs on the commercial film production industry.

The research aims to examine the effect of sustainable report disclosure on investor confidence. The conceptual framework comprises 3 dimensions 30 indicators of the conceptual Global Reporting Standard (GRI). The data were collected from the annual report and sustainable report disclosure of energy groups in Thai Listed Companies from 46 companies between 2019 and 2021. The researchers used multiple regression statistics to test hypotheses. The result of the study is obviously seen that the more sustainable report disclosures are produced, the greater investor confidence has increased. With corporate governance score as a mediator variable to support investor confidence, an increase in the disclosure of sustainable report information can be attributed, in part, to factors including the size of the board of directors and the size of independent board of directors. In brief, this research contributes to corporate social responsibility through stakeholder theory, legitimacy theory and signally theory.