Mobile learning application now is considered a powerful application for learning and was adopted in universities in the period of Covid-19. After Covid-19 pandemic, university students have been allowed to use mobile learning systems, it is needed to ensure students’ intention to continuously use mobile learning for their learning activities or not. Thus, the purpose of this paper is to understand the main determinants that encourage the continuous use of mobile learning. To achieve that, we used the UTAUT-2 model to predict the main determinants of mobile learning acceptance. In our study, a quantitative technique was employed to collect the data. A hybrid approach SEM-ANN was applied to validate the research model. The findings indicated that performance expectancy and effort expectancy had a strong effect on students' attitudes towards mobile learning platforms. In addition, the results showed that performance expectancy and effort expectancy have a significant impact on students' continuous intention to use mobile learning platforms after Covid-19. In addition, hedonic motivation and habit had a positive effect on both students' attitudes and continuous intention to use mobile learning platforms. Moreover, Social influence factor and facilitating conditions had a significant effect on students' continuous intention to use mobile learning platforms after Covid-19.

The editors of Uncertain Supply Chain Management retract this article [1] based on the request made by authors since they had found some significant issues about the results which could mislead the readers.

This study aims to find empirical evidence regarding the factors that affect the quality of information systems and the quality of supply chain management as seen from the environmental uncertainty of the organizational structure and the distribution network competence in manufacturing companies in Medan, Indonesia. The research method used is quantitative and verification that aims to determine the relationship between variables through a hypothesis testing. The data used are primary data using a questionnaire aimed at functional managers of marketing managers and production managers with a Likert scale. The study uses a sampling technique through a census of the entire population as a unit of analysis as many as 206 managers spread across 103 manufacturing companies in the city of Medan. Data analysis was performed through multiple linear regression analysis. The results showed that environmental uncertainty, organizational structure, and distribution network competence partially and simultaneously affected the quality of supply chain management information systems in manufacturing companies.

Human resource productivity is one of the vital notions in the management of modern organizations. Many studies concerned with this notion have tried to identify the factors affecting productivity and its improvement. One of these important factors is organizational spirituality. The present study investigated the impact of organizational spirituality, from an Islamic perspective, on human resources productivity in BELFA Co., Iran, as a manufacturing organization. The study relied on a descriptive survey method and used structural equation modeling to analyze data in Smart-PLS software to fit the measurement model and the structural model. Results revealed that spirituality could predict 26% of the variance of Human resources productivity in the company, proving to be an effective factor.

In this paper, the Multi-Depot Electric Vehicle Location Routing Problem with Time Windows (MDVLRP) is addressed. This problem is an extension of the MDVLRP, where electric vehicles are used instead of internal combustion engine vehicles. The recent development of this model is explained by the advantages of this technology, such as the diminution of carbon dioxide emissions, and the support that they can provide to the design of the logistic and energy-support structure of electric vehicle fleets. There are many models that extend the classical VRP model to take electric vehicles into consideration, but the multi-depot case for location-routing models has not been worked out yet. Moreover, we consider the availability of two energy supply technologies: the “Plug-in” Conventional Charge technology, and Battery Swapping Stations; options in which the recharging time is a function of the amount of energy to charge and a fixed time, respectively. Three models are proposed: one for each of the technologies mentioned above, and another in which both options are taken in consideration. The models were solved for small scale instances using C++ and Cplex 12.5. The results show that the models can be used to design logistic and energy-support structures, and compare the performance of the different options of energy supply, as well as measure the impact of these decisions on the overall distance traveled or other optimization objectives that could be worked on in the future.

The rapid digitalization in recent years has opened up many technological possibilities, gradually transforming various sectors and society as a whole. This digital shift has enabled advancements in a number of fields, leading to improved resource efficiency, systems and processes. The Internet of Things (IoT) refers to a system of interconnected devices that share information that exchange information with one another via the internet. IoT devices are now everywhere, found in applications ranging from unmanned aerial vehicles to smart home environments, from the Industrial Internet of Things to the Internet of Medical Things. The core concept of IoT revolves around establishing a seamless and intelligent communication ecosystem, facilitating interactions between devices over the internet. This is anticipated to create new opportunities for enhancing services in various societal sectors, such as transportation, farming and smart cities. However, IoT-based networks face limitations and challenges that hinder the realization of their full potential. This paper outlines these challenges and proposes solutions, emphasizing the importance of collaboration and innovation. The paper also anticipates future trends in IoT, particularly the integration of 5G connectivity, cloud computing and AI, and identifies areas for future research to address current challenges and explore new applications.

This study aimed to explain the role of supply chain practices on operational performance, and supply chain practices on company competitiveness and to analyze the impact of company competitiveness on operational performance. In addition, we also investigate the impact of supply chain practices on operational performance through role of company competitiveness as mediation variable. The study was conducted in South Sulawesi Province, Indonesia. Primary data were collected by questionnaire instrument from 108 food and beverage companies. Method of analysis was both descriptive statistical analysis, and Structural Equation Modelling (SEM). The study also used Sobel test to determine significance level of mediation role in the model. The results show that supply chain practices could give a positive impact on operational performance. Supply chain practices also gave a positive impact and significant on company competitiveness. Then, company competitiveness had a positive impact and significant on operational performance. Additionally, supply chain practices also had a positive impact on operational performance indirectly through the role of company competitiveness as mediation variable. Hence, supply chain practice was the most important variable to increase both company competitiveness and operational performance. Each company is recommended to implement this variable as competitive weapon in order to get a better operational performance and competitiveness as well.

Green management and its implementation and practices attracted the attention of both practitioners and academicians alike, which in part is due to its positive impact on the environment and sustainability, however, little is known about what really measures the effect of green management practices on business performance. Conventional measures of financial performance cannot reflect the proposed effect since green management is long-term oriented and not limited to financial performance only. This research explores the potentials of using balanced scorecard to measure the effect of green marketing, green supply chain and green human resources on the performance of the firms. Simple random sampling technique was followed in this research, and data were collected from 113 managers from different companies in service and manufacturing sectors in UAE. The findings indicate that green marketing was the major determinant of customers’ performance, green human resources was the major factor affecting learning and growth, and that green supply chain was the main influencer on financial performance and internal processes.

This paper presents an empirical investigation to study the effect of financial flexibility on capital structure decisions on selected firms listed in Tehran Stock Exchange over the period 2006-2018. The results indicate that the cash value of the previous years had no meaningful relationship with the current year's financial leverage, which suggests that flexibility in previous years could not explain the financial leverage of the coming years and financial leverage of companies changes did not occur based on the past years performance. When the ultimate value of financial flexibility is high, the impact of different variables, for example, profits, depreciation, and depreciation costs, fixed assets, etc., on leverage is of little importance, with a slight change in leverage. Companies with a high final value of financial flexibility are willing to maintain their current debt capacities, but it is significantly possible that they target deliberate or temporary deviations from their leverage ratios.

This article investigates the effect of cutting parameters on the surface roughness and flank wear during machining of titanium alloy Ti-6Al-4V ELI( Extra Low Interstitial) in minimum quantity lubrication environment by using PVD TiAlN insert. Full factorial design of experiment was used for the machining 2 factors 3 levels and 2 factors 2 levels. Turning parameters studied were cutting speed (50, 65, 80 m/min), feed (0.08, 0.15, 0.2 mm/rev) and depth of cut 0.5 mm constant. The results show that 44.61 % contribution of feed and 43.57 % contribution of cutting speed on surface roughness also 53.16 % contribution of cutting tool and 26.47 % contribution of cutting speed on tool flank wear. Grey relational analysis and TOPSIS method suggest the optimum combinations of machining parameters as cutting speed: 50 m/min, feed: 0.8 mm/rev., cutting tool: PVD TiAlN, cutting fluid: Palm oil.