Conference Agenda

This article investigates how intrinsic and extrinsic factors related to bank management affect bank production in the short and long run. Currently, research on banking productivity tends to focus on identifying influencing variables; however, the literature does not discriminate between temporary and long-term effects, nor does it demonstrate the mechanisms by which these variables exercise their effects. An error correction model is used to determine how interest-related variables affect banking productivity. In addition, the Malmquist Index, as expanded in the context of Data Envelopment Analysis (DEA) is applied to calculate the productivity. The findings demonstrate that bank productivity is unaffected by levels of international uncertainty, either short or long term. The impact of exogenous variables on banking productivity in Ecuador was also investigated. The results revealed that risk management emerges as a critical element, with a detrimental impact in both the short and long term. A negative association was also found between the delinquency rate and bank productivity, the main mechanism of influence being the fall in technical efficiency. Finally, policy recommendations and strategies that could be implemented to improve banking productivity are presented.

The automotive industry in Peru is experiencing sustained growth, presenting a significant opportunity to implement Lean philosophy principles alongside advanced inventory management practices to improve operational efficiency. A critical challenge faced by organizations is the low order service level, which is primarily caused by inaccurate demand forecasting, poor time management, stock-outs, and inefficient warehouse distribution. This study focuses on high-demand products, such as shock absorbers, terminals, springs, and trapezoids, which currently have an average service level of 81.10%. This issue is particularly important as low service levels often lead to delivery failures, resulting in lost sales and reduced profitability. The objective of this research is to propose strategies based on Lean Warehousing, including Business Process Management (BPM), Economic Order Quantity (EOQ), and Demand Forecasting. In addition, the study will apply the Kaizen approach to improve the service level by at least 10%, targeting the root causes of the identified problems to drive more efficient and profitable operations.

The objective of this article is to analyze the MSMEs strengthening programs currently established in the south-central region of Honduras. The methodology implemented consisted of the evaluation of three research variables, with 12 dimensions and 25 indicators, analyzed through the implementation of a survey and in-depth interviews. Among various findings, a tendency to provide support to the informal sector stands out, with low levels of participation and a relatively high degree of dissatisfaction. Thus, recommending the implementation of programs adaptable to the size, sector and age of MSMEs. This study provides originality in the way it evaluates both actors involved in the programs, although it was limited by the low interest of the enterprise’s participation in the research. It is concluded that microenterprise and the economy oriented to the provision of services predominates in the region studied, with a low level of operational growth. Also, the strengthening programs established and implemented are mainly characterized by providing training or training in administrative management.

The present systematic review of the literature was carried out with the objective of analyzing the development of business resilience in times of economic crisis covering the period from 2023 to 2025. The search for information was carried out using the Scopus database, where 45 articles were identified and selected, using the Prisma method and the PICO model, specifically its PIO variant. Bibliometric analysis used the R programming language and the bibliometrix tool to graphically represent articles by country, the relationship between keywords, authors and sources, the most consulted sources and the most relevant affiliations, The VOSviewer was also used to visualize the distribution of publications by analysis of the media citations used. The bibliometric results detail the most relevant sources and affiliations around the articles consulted. The content results also show that adaptability and learning capacity are essential elements in overcoming economic crises, together with innovation and digitalization. Thus, if they are properly applied, they would enable companies to manage them better in order to reduce the effects of future crises.

This research analyzes the impact of energy efficiency on reducing data center electricity consumption through Power Purchase Agreements (PPAs), using Google as a case study. A mixed-method approach, combining qualitative and quantitative analysis, was applied to assess the strategic implementation of energy efficiency measures and their measurable effects on operational performance. The study relied on historical data, technical reports, and key energy efficiency metrics to evaluate Google’s integration of PPAs and their role in minimizing electricity consumption and carbon footprint. Power Usage Effectiveness (PUE) served as the primary metric to assess efficiency, with a detailed regional and temporal analysis revealing significant performance variations. The findings indicate that European data centers, such as those in Eemshaven (Netherlands) and Dublin (Ireland), consistently achieved lower PUE values, benefiting from favorable climate conditions and advanced energy management. In contrast, North American locations exhibited a broader range of efficiency levels, while Asian facilities, particularly in Singapore, faced greater cooling challenges due to warm climates. Additionally, the study highlights the effectiveness of AI-driven workload distribution, real-time monitoring, and advanced cooling technologies in optimizing energy consumption. The results demonstrate that the integration of PPAs with energy efficiency initiatives not only ensures a stable supply of renewable energy but also enhances operational sustainability and contributes to grid decarbonization. This research underscores the importance of continuous innovation in data center energy management, offering insights applicable to the broader industry.

Abstract- Artificial Intelligence (AI) and business management (BM) complement each other in the commercial development of SMEs, i.e. AI facilitates customer segmentation and drives the development of operations without the need to increase manpower, helping to make decisions based on data analysis. The problem sought to test the relationship between the use of artificial intelligence (AI), in terms of design, planning and implementation with business management, considering planning, organization and control in SMEs in Chota, Peru. The study was a quantitative, non-experimental, cross-sectional correlational design, with a sample of 203 collaborators, who answered two questionnaires; the results show that most SMEs use AI in a limited or partial way, business management is basic, regular and deficient, there is no influence of AI in organizational planning, nor is there evidence of the impact of AI planning on the structural and operational organization, the use of AI is not affecting organizational control and above all there are challenges and opportunities to integrate the use of AI with business management; The research concluded that there is a significant positive relationship between the use of AI, considering its design, planning and implementation dimensions, and organizational management in terms of planning, organization and control in SMEs in Chota, Peru; therefore, the hypothesis is accepted.

Key words: Artificial Intelligence, design, planning, implementation, business management, planning, organization and control.