Corporate social responsibility before CSR: Practices at Aluminium du Cameroun (Alucam) from the 1950s to the 1980s

Abstract

Aluminium du Cameroun (Alucam) was set up in 1957 as a subsidiary of the French aluminium group Pechiney. Since its creation, the Alucam plant has systematically applied policies that simultaneously integrate economic, social and environmental aspects. The originality of our contribution is that we describe a case where the three elements that make up corporate social responsibility (economic, social and environmental) are intertwined. Although this combination of elements had not formally materialised at the time, the case examined shows early awareness – comparatively ahead of its time and relatively well combined between the 1950s and the 1980s – of the three dimensions of corporate social responsibility.     

Radicalness of blockchain: an assessment based on its impact on the payments industry

Blockchain is receiving considerable attention among practitioners and academics. However, a detailed analysis investigating how the impact of blockchain is going to unfold is still missing. Our article sets out to assess the radicalness of blockchain at an early stage of its development and substantiates the analysis with evidence from the payments industry. We start by distilling five key aspects of radical innovation from extant literature. Our analysis of blockchain then focuses on the payments industry, which represents a major business field of banking and the cradle of this technology. The results of a Delphi study provide 17 statements about the current development of blockchain. The statements deliver insights into the impact of blockchain on the payments industry and reveal the radicalness of the technology. Based on these insights, we investigate how blockchain affects the five key aspects of radical innovation and develop contributions from an innovation management’s perspective.     

Accuracy of German federal election forecasts, 2013 & 2017

The present study reviews the accuracy of four methods (polls, prediction markets, expert judgment, and quantitative models) for forecasting the two German federal elections in 2013 and 2017. On average across both elections, polls and prediction markets were most accurate, while experts and quantitative models were least accurate. However, the accuracy of individual forecasts did not correlate across elections. That is, the methods that were most accurate in 2013 did not perform particularly well in 2017. A combined forecast, calculated by averaging forecasts within and across methods, was more accurate than three of the four component forecasts. The results conform to prior research on US presidential elections in showing that combining is effective in generating accurate forecasts and avoiding large errors.     

Operational solar forecasting for the real-time market

Despite the significant progress made in solar forecasting over the last decade, most of the proposed models cannot be readily used by independent system operators (ISOs). This article proposes an operational solar forecasting algorithm that is closely aligned with the real-time market (RTM) forecasting requirements of the California ISO (CAISO). The algorithm first uses the North American Mesoscale (NAM) forecast system to generate hourly forecasts for a 5-h period that are issued 12 h before the actual operating hour, satisfying the lead-time requirement. Subsequently, the world’s fastest similarity search algorithm is adopted to downscale the hourly forecasts generated by NAM to a 15-min resolution, satisfying the forecast-resolution requirement. The 5-h-ahead forecasts are repeated every hour, following the actual rolling update rate of CAISO. Both deterministic and probabilistic forecasts generated using the proposed algorithm are empirically evaluated over a period of 2 years at 7 locations in 5 climate zones.     

Improving collaboration between large and small-medium enterprises in automobile production

ABSTRACT

Inter-organisational collaboration is important for achieving qualitative and quantitative performance improvement in the global competitive environment. In particular, the extent of collaboration between the mother company and its suppliers is important for the profitability and sustainability of a company in the automobile industry, which is carried out using a customisation and order production system. As a result of the empirical analysis in this study, the collaborative information sharing cycle is shortened and the collaborative information sharing scope is widened. Therefore, the level of collaboration is improved by constructing an IT collaboration system.     

Comparing the forecasting performances of linear models for electricity prices with high RES penetration

We compare alternative univariate versus multivariate models and frequentist versus Bayesian autoregressive and vector autoregressive specifications for hourly day-ahead electricity prices, both with and without renewable energy sources. The accuracy of point and density forecasts is inspected in four main European markets (Germany, Denmark, Italy, and Spain) characterized by different levels of renewable energy power generation. Our results show that the Bayesian vector autoregressive specifications with exogenous variables dominate other multivariate and univariate specifications in terms of both point forecasting and density forecasting.     

Towards a maturity model for big data analytics in airline network planning

The evaluation, acquisition and use of newly available big data sources has become a major strategic and organizational challenge for airline network planners. We address this challenge by developing a maturity model for big data readiness for airline network planning. The development of the maturity model is grounded in literature, expert interviews and case study research involving nine airlines. Four airline business models are represented, namely full-service carriers, low-cost airlines, scheduled charter airlines and cargo airlines. The maturity model has been well received with seven change requests in the model development phase. The revised version has been evaluated as exhaustive and useful by airline network planners. The self-assessment of airlines revealed low to medium maturity for most domains. Organizational factors show the lowest average maturity, IT architecture the highest. Full-service carriers seem to be more mature than airlines with different business models.     

Considerations of a retail forecasting practitioner

Forecasts can be used in an extraordinarily diverse range of ways across many domains in which forecasting practitioners work continuously towards improving their forecasts. Each of these domains may require the analysis of different kinds of inputs and special considerations. Even within a given domain, such as retail, there may be many similar use cases of the same kind of forecast, which can lead to practitioners making different decisions. This paper discusses several of the important decision points that practitioners must work through and uses item-level sales forecasting in the retail domain as leveraged by pricing and inventory management as examples of the different paths that may be taken. It considers how each use can lead to a different forecasting objective, and a corresponding focus on different error metrics. In addition, there are several tradeoffs in the forecasting methods that are used to meet each of the objectives best, including the kinds of models used, the running time speed, and forecast accuracy requirements.     

Bringing the past to life: Co-creating tourism experiences in historic house tourist attractions

This ethnographic study concentrates on the co-creation of experiential value between the tourist and tour guide in a single historic tourism site; Huntingdon Castle, Ireland. Built upon the principles of service dominant logic, the research explores how storytelling acts as an engagement platform and value enhancing strategic resource. In doing so, it impels the value co-creation journey and shapes the tourist's experience. Observation is coupled with qualitative interviews to capture the dual perspective of both guides and tourists. Findings exhibit the co-creation process through the performance of stories; how and when people derive pleasure (value); the influencing aspects of the environment or place; and guide/tourist perspectives on how they feel and think during the experience. The research contributes by taking a practical operational view of how co-creation occurs. It goes beyond the guide's perspective and exhibits the importance of co-creation of lived experience in the story enhanced tourism experience framework.