Organisational learning, strategic rigidity and technology adoption: Implications for electric utilities and renewable energy firms

This paper examines the implications of strategic rigidness for technology adoption behaviours among electric utilities. Such behaviours lead to heterogeneity in firm performance and consequently affect the electric utility industry. The paper's central aim is to identify and describe the implications of strategic rigidness for a utility firm's decision making in adopting newer renewable energy technologies. The findings indicate that not all utility firms are keen to adopt these new technologies, as these firms have traditionally been operating efficiently with a more conventional and mature technological arrangement that has become embedded in the organisational routine. Case studies of Iberdrola S.A. and Enel S.p.A. as major electric utilities are detailed to document mergers and acquisitions and technology adoption decisions. The results indicate that technology adoption behaviours vary widely across utility firms with different organisational learning processes and core capabilities.

Multiple proportion case-basing driven CBRE and its application in the evaluation of possible failure of firms

Case-based reasoning (CBR) is a unique tool for the evaluation of possible failure of firms (EOPFOF) for its eases of interpretation and implementation. Ensemble computing, a variation of group decision in society, provides a potential means of improving predictive performance of CBR-based EOPFOF. This research aims to integrate bagging and proportion case-basing with CBR to generate a method of proportion bagging CBR for EOPFOF. Diverse multiple case bases are first produced by multiple case-basing, in which a volume parameter is introduced to control the size of each case base. Then, the classic case retrieval algorithm is implemented to generate diverse member CBR predictors. Majority voting, the most frequently used mechanism in ensemble computing, is finally used to aggregate outputs of member CBR predictors in order to produce final prediction of the CBR ensemble. In an empirical experiment, we statistically validated the results of the CBR ensemble from multiple case bases by comparing them with those of multivariate discriminant analysis, logistic regression, classic CBR, the best member CBR predictor and bagging CBR ensemble. The results from Chinese EOPFOF prior to 3 years indicate that the new CBR ensemble, which significantly improved CBRs predictive ability, outperformed all the comparative methods.

Exploring the economic value of personal information from firms' financial statements

Currently personal data gathering in online markets is done on a far larger scale and much cheaper and faster than ever before. Within this scenario, a number of highly relevant companies for whom personal data is the key factor of production have emerged. However, up to now, the corresponding economic analysis has been restricted primarily to a qualitative perspective linked to privacy issues. Precisely, this paper seeks to shed light on the quantitative perspective, approximating the value of personal information for those companies that base their business model on this new type of asset. In the absence of any systematic research or methodology on the subject, an ad hoc procedure is developed in this paper. It starts with the examination of the accounts of a number of key players in online markets. This inspection first aims to determine whether the value of personal information databases is somehow reflected in the firms’ books, and second to define performance measures able to capture this value. After discussing the strengths and weaknesses of possible approaches, the method that performs best under several criteria (revenue per data record) is selected. From here, an estimation of the net present value of personal data is derived, as well as a slight digression into regional differences in the economic value of personal information.

Innovation in consulting firms: an area to explore

Services are the most representative sector in developed economies due to their contribution to GDP and employment. Consulting firms are classified as part of the Knowledge Intensive Business Services (KIBS) and provide professional services to all types of organizations. Consulting firms usually innovate with their customers and suppliers in a nurturing environment for value co-creation. This environment is project-based, process-oriented and with intensive knowledge exchange among all stakeholders. Based on literature review, it has been found that despite the existence of frameworks for service innovation, none of them have specifically focused on consulting firms. Further implications on this issue are addressed for both academics and practitioners.

Comparative Analysis of Firms’ Participation in National and International Programmes to Support Innovation

Innovation is a process that faces several market failure situations. For this reason and for being considered one of the main drivers of economic growth, a large number of governmental and supranational policies are designed to foster technological progress. Along with these policies, there is an increasing concern with their continuous evaluation aiming at providing valuable feedback for these program?s adaptation and adequacy to the firm?s needs. The paper develops an evaluation of the influence of innovation-focused programs in firm¿s innovation and economic performance by means of a comparative analysis of the results obtained by Spanish firms that have participated in R&D national programmes and those achieved by Spanish firms participating in EUREKA international program. Findings show that the programmes were effective in achieving their objective of promoting technological innovation but, as regards the economic effects, the results were less conclusive since some differences were observed depending on the programme. The EUREKA companies displayed better behaviour, with positive differences in their returns on assets and labour productivity. The results also confirm the importance of designing more detailed and rigorous evaluation processes, taking into account the risk variable, in order to draw a more realistic picture of the impact of national and international programmes.