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Se estudian los determinantes y la evolución de la actividad bursátil mensual en el mercado accionario colombiano de 2007 a 2016.

Para ello se emplean modelos de series de tiempo tipo ARIMAX y GARCH, incluyendo variables exógenas, recomendadas por la literatura previa.

Encontramos que la actividad bursátil puede ser pronosticada en buena parte por el valor rezagado a un mes y las innovaciones de cinco y 12 meses. También contribuyen a predecirla, como variables exógenas, una dummy de rendimientos positivos en los últimos tres meses, la presencia de emisiones primarias y el índice VIX de volatilidad del SP500. Estos resultados se mantienen en un alto grado al emplear medidas alternativas de actividad bursátil, el número total de operaciones y la rotación.

Se propone un modelo de predicción de la actividad bursátil que puede servir de modelo para otros mercados accionarios de Latinoamérica. El modelo obtenido es altamente predictivo del valor transado total del mercado al siguiente mes. La estimación de la actividad bursátil es de utilidad para instituciones como la Bolsa de Valores de Colombia, reguladores de los mercados financieros, así como para grandes inversionistas institucionales.

El propósito central de los mercados financieros secundarios consiste en facilitar la transacción de activos financieros, lo que debe reflejarse en alta actividad bursátil, tanto en número de operaciones como en valor transado total. La posibilidad de transar altos montos es una medida importante del desarrollo de un mercado financiero. De esta manera, el modelo aquí propuesto puede usarse para monitorizar y explicar el desarrollo del mercado. En particular, se evidencia el nocivo efecto de la debacle de Interbolsa a finales de 2012 y el positivo efecto de las emisiones primarias.

Este es el primer paper en estudiar la actividad bursátil del mercado accionario colombiano en años recientes. Sirve como modelo para el estudio y seguimiento de esta variable en otros mercados accionarios latinoamericanos.

To study the determinants and evolution of the trading activity in the Colombian Stock Market from 2007 to 2016.

ARMA time series models were used, including several explanatory variables recommended by previous literature.

We find that stock market activity can be predicted to a large extent by its lags, and that positive returns in the last three months, emissions and the VIX index are also explicative variables, as suggested by empirical studies in other countries and theoretical models of market microstructure. These results are robust by using alternative measures of trading activity, total number of trades and turnover.

The main contribution of this study is the analysis of the trading activity of the Colombian Stock Market, a critical variable for monitoring the development of any financial market.

The purpose of this paper are twofold. First, to disclose whether accounting students who participate more in online activities proposed by the teacher achieve better learning outcomes. Second, to identify which virtual learning activities achieve improved outcomes.

Data mining is a computer-based tool devoted to analyzing massive data sources, generating information and discovering deeper knowledge and links among variables.

There were differences between universities and subjects in the association of level of activity and learning outcomes. These findings will help teachers adjust their teaching guide, schedule and explanations.

Further developments should include the level of online compromise of the lecturers, and the correspondence of the online activity with the designed activities in the teaching guide. In order to identify the value-added activities performed by the students to achieve better deep learning outcomes.

Higher Education should provide students with cognitive and transversal skills for successful incorporation into the labor market. In this sense, teaching methodology combined with online tools facilitates the process of teaching and learning with the implementation of different multimedia resources.

Recently, the impact of virtual platform usage on students’ learning outcomes has started to be analyzed using “data mining” techniques. Educational data mining is a new focus to disclose existing links among students, lecturers and its activity.

This study analyzes how technological changes in the context of Industry 4.0 influence buyer-supplier relationships (BSRs).

The study is explorative in nature; hence, an empirical qualitative research design is applied. It bases on 45 expert interviews with managers from German and Austrian industrial companies as empirical data. A qualitative content analysis is conducted to inductively analyze the empirical material and to identify common patterns, themes and categories.

The paper finds that future transactions are mainly based on digitized, automated procedures, transferring various value creation processes to platforms. BSRs become more intense in nature. Companies consolidate their supplier base by focusing on important strategic suppliers.

As the paper is of exploratory nature, it can only present first qualitative insights. Further studies can extend the results by analyzing and contrasting BSRs in various industries or value chain stages and map differences and similarities, respectively.

The paper's results provide implications for management and corporate practice alike. These help companies to raise Industry 4.0's full potential as for BSRs creating and securing long-term and sustainable competitive advantages.

This paper is among the first to empirically investigate BSRs in the context of Industry 4.0. Providing implications for research and corporate practice, it contributes to tapping Industry 4.0's full potential complementing an extra-organizational perspective.

The main purpose of this paper is to assess the technological view of apparel new product development (NPD) process through a framework for improving the efficiency of NPD process in Sri Lankan apparel industry.

The study uses literature review, a survey and in-depth interviews of industry experts for data collection. Descriptive analysis and correlation analysis are used to identify the relationship between NPD process performance and Industry 4.0 (I4) technology components.

All technology components are enablers of NPD process, yet the relative importance of technology components varies within the NPD life cycle. Technoware is identified as the most significant, while Humanware component is the least significant for the advancement of I4 technologies in the NPD process.

Despite the novelty of research investigation into NPD process using I4 technologies in apparel industry, it is limited to one geographical location and a small segment of the industry.

This paper assists apparel industry practitioners to better understand and prioritize I4 technology components in the NPD life cycle for their successful adoption and for reaping the benefits.

This research generates new knowledge on the adoption of I4 technologies using industry insights into technology components mapped/aligned with key stages of NPD life cycle.

The purpose of this paper is to develop an effective treatment to analyze and diagnose urban rail transit (URT) vehicle maintenance strategy.

In this paper, the technique of Failure Mode and Effects Analysis (FMEA) is introduced into the examination of URT trains, first. Then the method of fuzzy-set-based assessment for FMEA is presented, which is the quantitative tool of Fuzzy-Set-based treatment for FMEA in analysis and diagnoses to URT maintenance strategy. Moreover, recommendations for further improvement of the proposed approach are also provided. Initial application into the vehicle maintenance of Shanghai URT System shows, that the proposed approach has a good performance and consequently is worth further development.

The paper presents a FMEA and fuzzy-set-based theoretical approach for analyzing and diagnosing current methods in URT vehicle maintenance strategy.

With rapid development of URT systems in the world especially in those highly populated areas, much more attentions are turning to researches on URT maintenance, nevertheless, few quantitative research achievement are mentioned or applied. This paper is a tentative attempt at introducing fuzzy-set theory into quantitative analysis and diagnoses of URT maintenance strategy.

The study in this paper is helpful in theory and practice of URT maintenance and its methodology could be further applied into a broad family of facility group or system in other engineering fields.

The purpose of this study is to analyse the mediating and moderating effects of relational flexibility norms on relationship building capacities and export performance.

The study followed a quantitative and cross-sectional approach. The analysis was applied to 95 Peruvian Exporting SMEs which were examined through structural equation modelling (SEM) using AMOS 24.0 statistical package. The responses were gathered through telephone and personal interviews which were tested using the Mann–Whitney U test, finding no statistically significant differences.

The main finding of the study is to demonstrate the indirect effect of relational flexibility norms on the export performance of SMEs through relationship-building capabilities. In this way, these capabilities become very important variables in the export management of SMEs, since they directly affect the relationship of the Exporter–Importer dyad.

One of the limitations is the cross-sectional type study that applies to the short-term effects of relational norms. Organizational characteristics and other factors that may affect export performance should also be considered in future research, as well as longitudinal studies should be developed.

The study allows SMEs to focus management efforts on strengthening the relationship – building capabilities, which are very important given SMEs' resource constraints. Therefore, an adequate management of relations with importers can contribute to the reduction of control and coordination costs; and have a positive impact on export performance. Similarly, the study contributes to the management of export promotion by suggesting that one area to be prioritized is the strengthening of the relationship capacities of exporting SMEs.

The study provides the analysis of the mediating effect of the relationship-building capability between relational flexibility and export performance. In this way, it enriches the theoretical analysis and contributes with the empirical evidence of an emerging country like the case of Peru.