This empirical inquiry adopts the AutoRegressive Distributed Lag (ARDL) model to meticulously examine the multifaceted interconnections among innovation, globalization, and productivity across a diverse set of 76 nations, encompassing both developed and developing economies. The research employs rigorous econometric techniques within the ARDL framework to discern the short- and long-term effects of innovation and globalization on productivity levels. The findings underscore a robust and statistically significant association between innovation and productivity, as well as a constructive impact of globalization on enhancing productivity. The outcomes underscore the transformative potential of innovation and the facilitating role of globalization in fostering productivity growth. This empirical evidence contributes to the empirical literature by offering a refined understanding of the intricate relationships shaping productivity patterns on a global scale, emphasizing the joint influence of innovation and globalization in driving economic efficiency.

Aiming at the problem of incompatibility of biomass models of forest organs, taking Chinese fir in Fujian Jiangle State-owned Forest Farm as the research object, based on selecting the optimal independent model of each organ, the biomass compatibility model of Chinese fir was established with a three-level joint control scheme. The results show that the compatibility equation system based on the whole plant biomass can effectively solve the problem of incompatibility in the whole plant biomass, each sub-biomass and between sub-biomass. Besides, except for the leaf biomass model, all other biomass models have good fitting effect, which is of great significance to the guidance of the analysis of local Chinese fir biomass.

Competition in the telecommunications market has significant benefits and impacts in various fields of society such as education, health and the economy. Therefore, it is key not only to monitor the behavior of the concentration of the telecommunications market but also to forecast it to guarantee an adequate level of competition. This work aims to forecast the Linda index of the telecommunications market based on an ARIMA time series model. To achieve this, we obtain data on traffic, revenue, and access from companies in the telecommunications market over a decade and use them to construct the Linda index. The Linda index allows us to measure the possible existence of oligopoly and the inequality between different market shares. The data is modeled through an ARIMA time series to finally predict the future values of the Linda index. The results show that the Colombian telecommunications market has a slight concentration that can affect the level of competition.

This research investigates the safety status of water transport in Lake Towuti, South Sulawesi, employing the MICMAC and MACTOR methodologies to discern the factors that affect navigation safety and the interactions among the relevant stakeholders. The MICMAC analysis reveals that the effectiveness of sustainable transportation in Lake Towuti is significantly dependent on technical elements such as vessel certification, maintenance practices, and safety monitoring, alongside robust relationships among key entities like The South Sulawesi Class II Land Transportation Management Center (BPTD), The East Luwu District Transportation Office (Dishub), and the Timampu Port Service Unit (Satpel). When implementing the MICMAC-MACTOR model, it is essential to consider the technical implications of the proposed recommendations from the perspectives of social justice, environmental sustainability, and economic feasibility. The outcomes derived from the MICMAC and MACTOR assessments in Lake Towuti provide critical insights that can be utilized in other lakes across Indonesia, especially those that exhibit deficiencies in safety measures and adherence to inland water transport safety regulations.

This financial modelling case study describes the development of the 3-statement financial model for a large-scale transportation infrastructure business dealing with truck (and some rail) modalities. The financial modelling challenges in this area, especially for large-scale transport infrastructure operators, lie in automatically linking the operating activity volumes with the investment volumes. The aim of the paper is to address these challenges: The proposed model has an innovative retirement/reinvestment schedule that automates the estimation of the investment needs for the Business based on the designated age-cohort matrix analysis and controlling for the maximum service ceiling for trucks as well as the possibility of truck retirements due to the reduced scope of tracking operations in the future. The investment schedule thus automated has a few calibrating parameters that help match it to the current stock of trucks/rolling stock in the fleet, making it to be a flexible tool in financial modelling for diverse transport infrastructure enterprises employing truck, bus and/or rail fleets for the carriage of bulk cargo quantifiable by weight (or fare-paying passengers) on a network of set, but modifiable, routes.