World globalisation drives companies to undertake international expansion with the aim of retaining or growing their businesses. When companies globalize, managers encounter new challenges in making international marketing strategy (IMS) decisions, which are influenced by perceived cultural and business distance between their home- and foreign country. Telkom Indonesia International (Telin) was formed by Telkom Indonesia (i.e. the state-owned company in the telecommunication industry in Indonesia) to engage in international business within a global market. The central question in this study is to what extent do managers’ perceived cultural and business distance between home- and foreign country influence their IMS decisions? A mixed research strategy will be employed by applying qualitative and quantitative methods concurrently. The data collection will involve interviews with CEOs and managers, alongside a web survey to 55 managers of Telkom's. Results suggest important consequences for IMS decisions and emphasizes the need for dialogue on perceptions of cultural and business characteristics of countries.
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In sports, inertial measurement units are often used to measure the orientation of human body segments. A Madgwick (MW) filter can be used to obtain accurate inertial measurement unit (IMU) orientation estimates. This filter combines two different orientation estimates by applying a correction of the (1) gyroscope-based estimate in the direction of the (2) earth frame-based estimate. However, in sports situations that are characterized by relatively large linear accelerations and/or close magnetic sources, such as wheelchair sports, obtaining accurate IMU orientation estimates is challenging. In these situations, applying the MW filter in the regular way, i.e., with the same magnitude of correction at all time frames, may lead to estimation errors. Therefore, in this study, the MW filter was extended with machine learning to distinguish instances in which a small correction magnitude is beneficial from instances in which a large correction magnitude is beneficial, to eventually arrive at accurate body segment orientations in IMU-challenging sports situations. A machine learning algorithm was trained to make this distinction based on raw IMU data. Experiments on wheelchair sports were performed to assess the validity of the extended MW filter, and to compare the extended MW filter with the original MW filter based on comparisons with a motion capture-based reference system. Results indicate that the extended MW filter performs better than the original MW filter in assessing instantaneous trunk inclination (7.6 vs. 11.7◦ root-mean-squared error, RMSE), especially during the dynamic, IMU-challenging situations with moving athlete and wheelchair. Improvements of up to 45% RMSE were obtained for the extended MW filter compared with the original MW filter. To conclude, the machine learning-based extended MW filter has an acceptable accuracy and performs better than the original MW filter for the assessment of body segment orientation in IMU-challenging sports situations.
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The purpose of this paper is to gain deeper insight into the practical judgements we are making together in ongoing organizational life when realizing a complex innovative technical project for a customer and so enrich the understanding of how customer orientation emerges in an organization. The outcome contributes to the knowledge of implementing customer orientation in an organization as according to literature (Saarijärvi, Neilimo, Närvänen, 2014 and Van Raaij and Stoelhorst, 2008) the actual implementation process of customer orientation is not that well understood. Saarijärvi, Neilimo and Närvänen (2014) noticed a shift from measuring the antecedents of customer orientation and impact on company performance, towards a better understanding how customer orientation is becoming in organizations. A different way of putting the customer at the center of attention can be found in taking our day-to-day commercial experience seriously, according to the complex responsive process approach, a theory developed by Stacey, Griffin and Shaw (2000). The complex responsive processes approach differs from a systems thinking approach, because it focuses on human behavior and interaction. This means that the only agents in a process are people and they are not thought of as constituting a system (Groot, 2007). Based on a narrative inquiry, the objective is to convey an understanding of how customer orientation is emerging in daily organizational life. Patterns of interaction between people are investigated, who work in different departments of an organization and who have to fulfill customer requirements. This implies that attention is focused towards an understanding in action, which is quite distinct from the kind of cognitive and intellectual understanding that dominates organisational thought. The reflection process resulting from this analysis is located in a broader discourse of management theory.
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Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
