Developing Intellectual Capital in Professional Service Firms Using High Performance Work Practices as Toolkit

The role of Professional Service Firms (PSFs) has always been crucial in the development of knowledge economies. The effectiveness of these firms is highly attributed to the knowledge capabilities and skills embedded in its human resources and how effectively these resources are utilized in the optimal benefit of the firm. Owing to the ever-increasing growth of the services sector globally, it’s critical for the PSFs to gain in-depth awareness on the application of High-Performance-Work-Practices (HPWPs) so as to continually maintain quality of their services to the clients. However, the mechanism for systematically managing and implementing these practices in intellectual capital context is still not fully developed. This research, therefore, theoretically investigates and suggests a linkage mechanism on how Strategic HR practices (HPWPs) via (Ability, Motivation and Opportunity)-enhancing bundles stimulate intellectual capital development in professional service firms. By presenting a conceptual framework, this study offers practically meaningful insights to the managers in the service firms on how to implement these practices for effectively meeting client needs and sustaining a competitive advantage

Proceso analítico jerárquico difuso extendido para análisis comparativo de metodologías de ciencia de datos

En entornos cambiantes y altamente competitivos, la correcta toma de decisiones es clave en las organizaciones, quienes basan sus decisiones en gran parte a partir de los datos disponibles. El objetivo del presente trabajo presentar un modelo extendido que involucra el Proceso Analítico Jerárquico Difuso y la técnica de Teoría de la Construcción Personal para realizar un análisis comparativo de las metodologías de Ciencia de Datos CRISP-DM, Catalyst y MoProPEI. Siguiendo los pasos del modelo, se definieron los criterios y subcriterios a partir de la pericia de los expertos y estudios previos. Las metodologías fueron evaluadas a partir de dos casos de validación reales según el grado de completitud de los criterios y sub-criterios involucrados; donde se puedo identificar a MoProPEI como la metodología más robusta. Demostrando así la utilidad del modelo propuesto.Sociedad Argentina de Informática e Investigación Operativ

Modelo para la escritura de artículos científicos a distancia mediante tareas colaborativas

There has been a lot of research on improving the process of scientific writing collaboratively, for example, indicators have been elaborated to measure the success of this type of activities, also, computer tools have been developed to facilitate this exercise, among other proposals. These research works have become relevant and pertinent due to the current conditions of pandemic (COVID-19), because, general isolation measures have been established that make it impossible to meet and interact with other people, which are important values to succeed in any collaborative activity. For this reason, the process of scientific research and writing has become extremely difficult in recent times; specifically, the lack of a structured process to organize and systematize scientific research at a distance through virtual means has been identified. Considering the above-mentioned problems, a model based on the contributions of collaborative engineering is presented, which allows the design of joint tasks from virtuality, adding elements of the SECI model, which seeks to manage knowledge and make it uniform among authors. To this end, the abstraction of common tasks when writing scientific articles was carried out and a model was proposed to improve this process. The validation of this was done through a case study where a group of researchers use the proposal and develop the writing of a research paper. Subsequently, promising results were obtained about the proposed model, with high levels of satisfaction among participants. Finally, it was found that this is an area of research in which contributions can be made, where the development of specific tools to evaluate collaborative activities is a latent need.Para mejorar el proceso de escritura científica de forma colaborativa se han realizado múltiples investigaciones, como la elaboración de indicadores para medir el éxito de estas actividades y el desarrollo de herramientas informáticas que faciliten la ejecución de dicho ejercicio. Estos trabajos de investigación han tomado relevancia y pertinencia por las condiciones actuales de pandemia (COVID-19), debido a que las medidas de aislamiento general que se han establecido imposibilitan el encuentro y la interacción con otras personas, lo cual son valores importantes para tener éxito en cualquier actividad colaborativa. Por esta razón, en tiempos recientes, el proceso de investigación y escritura científica se ha dificultado, identificándose la falta de un proceso estructurado para organizar y sistematizar la investigación científica a distancia mediante medios virtuales. Teniendo en cuenta la problemática mencionada, se presenta un modelo basado en los aportes de la ingeniería de la colaboración que permite diseñar tareas conjuntas desde la virtualidad, añadiendo elementos del modelo Socialización, Externalización, Combinación e Internalización (SECI), el cual busca gestionar el conocimiento y hacerlo uniforme entre los autores. Para esto, se realizó una encuesta que permitió la abstracción de tareas comunes al escribir artículos científicos y se planteó un modelo para mejorar este proceso. Su validación se realizó mediante un caso de estudio donde un grupo de investigadores utilizan la propuesta y desarrollan la escritura de un documento de investigación. Posteriormente, se obtuvieron resultados prometedores acerca del modelo propuesto, con niveles altos de satisfacción entre los participantes. Finalmente, se constató que es un área de investigación en la que se pueden hacer aportes significativos al proceso de escritura científica en épocas de aislamiento a causa de la pandemia, donde el desarrollo de herramientas específicas para evaluar actividades colaborativas es una necesidad latente

Social media data analytics to improve supply chain management in food industries

© 2017 Elsevier Ltd This paper proposes a big-data analytics-based approach that considers social media (Twitter) data for the identification of supply chain management issues in food industries. In particular, the proposed approach includes text analysis using a support vector machine (SVM) and hierarchical clustering with multiscale bootstrap resampling. The result of this approach included a cluster of words which could inform supply-chain (SC) decision makers about customer feedback and issues in the flow/quality of food products. A case study in the beef supply chain was analysed using the proposed approach, where three weeks of data from Twitter were used

Knowledge Management Practice Strategies in Project-Based Organizations

Companies globally have lost profit each year because of the lack of intra-organizational knowledge sharing. The purpose of this descriptive, multiple case study was to explore the knowledge management practice strategies that project management business leaders use to improve knowledge sharing in project-based organizations. Nine project management business leaders from 4 project-based organizations in metro Atlanta, Georgia completed individual Skype/phone semistructured interviews, and 5 project team members completed an in-person focus group discussion and an interview questionnaire. Knowledge management was the conceptual framework for this study, the basis for understanding the world around project management business leaders, and the implementation of knowledge management practice strategies for knowledge sharing. The individual interviews, focus group discussion, and interview questionnaire yielded the lived experiences of project management business leaders and the perceptions of project team members regarding knowledge sharing in their project-based organizations. The data were analyzed through data source triangulation and cross-case synthesis, which resulted in various themes such as communication, practices to overcome barriers, and a centralized resource center. The findings of this study may effect positive social change and the improvement of knowledge sharing by promoting the worth, dignity, and development of individuals, communities, organizations, cultures, or societies

Exploring Strategies for Capturing Requirements for Developing ICT4D Applications

Some software engineers make decisions using applications designed from poorly captured user requirements. The quality of user requirements is crucial in the requirements engineering process, costing 50 times more to remedy the defects of using poorly captured user requirements. Grounded in the socialization, externalization, combination and internalization model of Nonaka theoretical framework, the purpose of this qualitative multiple case study was to explore strategies software engineers in Southern African software houses and IT departments use for capturing information and communication technology for development (ICT4D) requirements. The participants consisted of software 12 engineers who were working in Southern Africa, capturing ICT4D requirements. The data were collected using semistructured interviews. Thematic analysis was used, and four themes emerged: (a) interacting with stakeholders—socialization, (b) transforming interactive knowledge into user requirements—externalization, (c) sharing documented knowledge about user requirements—combination, and (d) applying assimilated knowledge from documented knowledge—internalization. A recommendation is for software engineers to capture their users’ needs and experiences to develop reliable ICT4D software that can assist in delivering interventions to marginalized societies. The implications for positive social change include improving the socioeconomic status of marginalized citizens with ICT4D software applications due to potentially improved requirements engineering practices

Improving efficiency and reducing waste for sustainable beef supply chain

In this thesis, novel methodologies were developed to improve the sustainability of beef supply chain by reducing their environmental and physical waste. These methodologies would assist stakeholders of beef supply chain viz. farmers, abattoir, processor, logistics and retailer in identification of the root causes of waste and hotspots of greenhouse emissions and their consequent mitigation. Numerous quantitative and qualitative research methods were used to develop these methodologies such as current reality tree method, big data analytics, interpretive structural modelling, toposis and cloud computing technology. Real data set from social media and interviews of stakeholders of Indian beef supply chain were used. Numerous issues associated with waste minimisation and reducing carbon footprint of beef supply chain are addressed including: (a) Identification of root causes of waste generated in the beef supply chain using Current Reality Tree method and their consequent mitigation (b) Application of social media data for waste minimisation in beef supply chain. (c) Developing consumer centric beef supply chain by amalgamation of big data technique and interpretive structural modeling (c) Reducing carbon footprint of beef supply chain using Information and Communication Technology (ICT) (d) Developing cloud computing framework for sustainable supplier selection in beef supply chain (e) Updating the existing literature on improving sustainability of beef supply chain. The efficacy of the proposed methodologies was demonstrated using case studies. These frameworks may play a crucial role to assist the decision makers of all stakeholders of beef supply chain in waste minimization and reducing carbon footprint thereby improving the sustainability of beef supply chain. The proposed methodologies are generic in nature and can be applied to other domains of red meat industry or to any other food supply chain