Service of SURF
© 2025 SURF
From the article: "After 1993, the concept of strategic alignment is evaluated from the connection between IT and business to much broader definitions in which the connection between all business functions, horizontally and vertically, and later also with projects and stakeholders is mentioned. To achieve stategic alignment there must be a coordination between the strategy of organizations and those who contribute to the implementation of the strategy and the actual performance of an organization. This process is called Human Oriented Performance Management (HOPM). The HOPM model consists of four dimensions: strategy translation, information and visualization, dialogue and action orientation, and continues improvement and organizational learning. To measure the effect of strategic alignment a range of financial performance indicators are used. Based on a literature review this paper explores which financial performance indicators could be used to measure the effect of HOPM. The literature was selected over a period from 1996 – 2015. The research is not only focused on the top of the strategy map, but also on the cause-effect relationships in the strategy map. The underlying performance indicators in the strategy map can show on which figures the dialogue in the HOPM model about strategy implementation must be based. This dialogue is the input to action in which strategic alignment comes about. The goal of the research is to optimize this dialogue by looking for performance indicators that can show the effect of HOPM" The article is used for the course: 'corporate policy' minor MSMM (Masterclass Strategic Marketing Management).
From the article: With increasing investments in business rules management (BRM), organizations are searching for ways to value and benchmark their processes to elicitate, design, accept, deploy and execute business rules. To realize valuation and benchmarking of previously mentioned processes, organizations must be aware that performance measurement is essential, and of equal importance, which performance indicators to apply to the performance measurement processes. However, scientific research on BRM, in general, is limited and research that focuses on BRM in combination with performance indicators is nascent. The purpose of this paper is to define performance indicators for previously mentioned BRM processes. We conducted a three round focus group and three round Delphi Study which led to the identification of 14 performance indicators. Presented results provide a grounded basis from which further, empirical, research on performance indicators for BRM can be explored.
LINK
The Netherlands are one of the frontrunners in stimulating electric mobility in Europe when it comes to the charging infrastructure density and electric vehicle adoption. Municipalities play an instrumental role in the rollout of public charging infrastructure while they have little insight in the relevant key performance indicators of the charging infrastructure as a means to support effective decision making. This paper aims to contribute to providing a more thorough understanding of relevant key performance indicators for public charging infrastructure. An approach is presented that explores result and performance indicators to support policy makers optimizing the roll out of and improvement of the business case for charging infrastructure.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations