Calculating the carbon footprint is fundamental to understand how an organization’s activities impact global sustainability. The main challenge is how to calculate it when environmental aspects are intangible assets. The present paper investigates in what ways the environmental effects of 13 aspects in relation with R&D activities in an applied research center could contribute to sustainable development. For this purpose, we described methodology to routinely measure greenhouse gas (GHG) emissions and calculate the carbon footprint (CF) of all research activities related to intangible assets (R&D projects, researchers’ knowledge and software libraries) with real-time data being provided. Selection of conversion factors to express all GHG emissions are described, in particular those related to air travel on account of its greatest contribution to CF. In addition, these data were used as a factor in assessing the environmental impact of the center, under ISO 14001. As a result, our center can manage its CF and make decisions about how to enhance sustainability awareness at all levels of the organization and gradually improve CF data, of which the main contributors were transportation and travel (66.4%) and electricity (33.1%) in 2018.

Purpose: This paper proposes defining a methodology of cultivation and integration of communities of practices (CoPs) and to create an evaluation model in organizations.Design/methodology/approach: This research project was based on a qualitative case study design, with main units of analysis being CoPs. The objective was achieved developing an analysis model of CoPs based on the key dimensions created by R. McDermott and studying actual experiences in CoPs integration with this model. The reported research project involves 15 organization actual experiences of CoPs in very different kinds of organizations. Although the study analyzed different kinds of companies, the evaluation methodology is unique.Findings: Based on the results of the study, a cultivation model of CoPs was created, which includes the detection analysis of CoPs in organization, the analysis of CoPs' necessity in organizations, the analysis of the appropriate CoPs in each organization and the evaluation model for the integrated CoPs.Research limitations/implications: All the actual experiences analyzed are documented cases. Therefore, it is difficult to find failure experiences and most of them are successful cases.Practical implications: The cultivation model can help managers of any organization in the integration process of CoPs.Originality/value: The main contribution of this project is the development of a valid and sustainable cultivation model of CoPs in any organization.

Purpose: The purpose of this paper is to develop a model to help RTC managers in the technological and R&D decisions and bets so as to change the perceived value of the R&D projects of the centres. To achieve this aim, the paper investigates the different models for the valuation of intangible assets. Design/methodology/approach: The paper presents a single case study and focusses on creating a useful IC valuation model for the centre, using existing methods and frameworks in IP and IC fields. Findings: The paper presents a new method for the calculation of IC applied to a RTC in ICT sector, in which the valuation of the IP is included (software libraries) and the KM and the peculiarities of these kinds of organisations are explained. The model is based on Edvinsson and Malone (1997) and Leitner (2005). Research limitations/implications: Although the use of a single case provides rich data, it is also limits the generalisability to other RTCs. Another limitation is that not all existing methods were explained. This new method constitutes a first proposal for the IP and IC valuation in RTCs and further discussion and development would be carried out in the future. Practical implications: The results suggest an IP and IC measurement model to improve the strategic and technological decisions making. Social implications: This paper may favour the competitiveness of companies engaged in intangible assets (knowledge, R&D) and the negotiation of the contracts since it arrives to determine a value for the intellectual property (software libraries) and intellectual capital. Originality/value: This paper proposes an IC Model orientated towards an RTC context and to provide a value perspective for them. The authors are practitioners and the model is in use.

This paper presents a machine-learning-based method for evaluating the internal value of talent in any organization and for evaluating the salary criteria. The study assumes the design and development of a salary predictor, based on artificial intelligence technologies, to help determine the internal value of employees and guarantee internal equity in the organization. The aim of the study is to achieve internal equity, which is a critical element a that directly affects employees’ motivation. We implemented and validated the method with 130 employees and more than 70 talent acquisition cases with a Basque technology research organization during the years 2021 and 2022. The proposed method is based on statistical data assessment and machine-learning-based regression. We found that while most organizations have established variables for job evaluation as well as salary increments for staff according to their contribution to the organization, only a few employ tools to support equitable internal compensation. This study presents a successful real case of artificial intelligence applications where machine learning techniques help managers make the most equitable and least biased salary decisions possible, based on data.

Overview: Performance measurement systems are a fundamental concern for R&D managers and executives. The main challenge is ensuring that R&D managers can match organizational key performance indicators with researchers’ interests. This article details a new approach to measuring the fuzzy parameter of researchers’ performance. It presents a case study on the implementation of a rating system in a research technology organization and reports the results the system achieved, including researcher satisfaction. We describe which researcher skills were selected for rating, the evaluation criteria developed, and the data collection system that supported the rating process. The rating system was developed to be objective and acceptable to researchers, and to support achievement of desired corporate results. We present lessons learned from implementation over four years.