Proceedings of London International Conferences

Strategies of transnational companies in the technological sector

Olga Nosova — Sun, 06 Jul 2025 00:00:00 +0000

Purpose. This study examines transnational corporations in the technological sector. Transnational companies minimize costs by transferring R&D results to affiliates and maximize profits.

Design. This study lists the benefits and drawbacks of the fundamental business methods used by multinational corporations. Analysis was based on R&D data, the cutting-edge technology application, and the dissemination of new management organizational forms. A model for developing a strategy for transnational companies to promote innovative products was considered.

Findings. The ability of transnational corporations to use a flexible mechanism of investment activity and organizational methods analyzed in global economic change. Artificial intelligence, digital technology, and digital platforms were also identified. The key factors for achieving technological leadership in transnational corporations through global production systems are grounded.

Originality. The proposed decision-making model illustrates the author’s approach to monitoring and assessing the effectiveness of the TNCs' selected innovation strategies. A transnational business strategy combines elements and features of innovation strategies. The use of innovative strategies stimulates technological development and increases competitiveness.

Future-proof entrepreneurship in SMEs: The OK!-Method

Jan Jansen, Rob Westerdijk — Sun, 06 Jul 2025 00:00:00 +0000

The OK!-method is based on a sound base of management/business administration theories, like Systems Theory and Business Administration method (In 't Veld, Slatius, & In 't Veld, 2023) (Veeke, Ottjes, & Lodewijks, 2008) (Simons, 2014), Multiple value model (Gleeson-White, 2014), Systems Thinking (Meadows, Meadows, Randers, & Behrens, 1972), Dialogue & Communication (Scharmer, 2009) (Scharmer, 2018) and Kepner and Tregoe Method (1981). These bases of the OK!-Method are further developed by an input-throughput-output model of the international <IR> framework of the International Integrated Reporting Council (IIRC, 2022). Besides the input-throughput-output structure, the IIRC model is linked to the external environment (including the creation, preservation, and erosion of value in time), as well as (new) business models in the context of purpose, mission and vision of the company. The outcomes can be positive and negative in time (including long-term orientation) regarding finance, social and environment (so, in fact, the well-known triple Ps in sustainability: People, Planet and Profit). New business models (Jonker, 2015) introduces business models that are not always based on ownership (but on usage) and profit maximisation. So, the orientation of new business models is more circular and sustainable ( within the Rhineland business framework (Van Aken, Riepma, & Westerdijk, 2019).

The base of management/business administration follows the mainstream literature (Bateman & Snell, 2004), and topics like External environment analyses instruments for stakeholders analyses and social factors developments, and Internal organisational analyses instruments for Strategy, Organisational culture, Leadership, Structuring, Processes, Staff, Company assets, Governance and Finance. Another essential layer in the OK!-Method is the Kepner-Tregoe method (1981). The method is based on four processes: Situation appraisal, Problem analysis, Decision analysis and Potential problem analysis.

What are the reasons for a company to draw attention to circularity and sustainability besides the traditional goal of generating profit? In the business environment (Van Aken, Riepma, & Westerdijk, 2019), there is a shift from the Anglo-Saxon business model (based on maximising shareholder value and profit maximisation) to the Rhineland business model (based on long-term stakeholder value). This is not only observed in annual reports of large companies (with a quotation at the stock exchanges) but also for Small and Medium-sized enterprises (SMEs). In the DOSIT method (Berendsen, Van Liere, Venselaar, Ansems, & Appelman, 2006) there are three main reasons SMEs are focusing on sustainable/circular approaches: Requirements from their clients (the market), (expected future) legislation from the government (national or international), and internal motives of the entrepreneur (often based on stewardship-related philosophies). In a recent contribution to this topic (Schoenmaker & Schramade, 2023) the long-term value of an enterprise is the integrated value (IV), and it consists of three components: Financial Value (FV), Social Value (SV) and Environmental Value (EV). Or in an equation: IV=FV+SV+EV.

The OK!-Method uses seven sequential stages to contribute to a future-proof and sustainable organisation: Sensing, Assessing, Root cause analysis, Structured decision research, Setting up implementations, Implementation, and Evaluation.

Unlocking the power of Artificial Intelligence to develop people’s empathetic skills

Christina Schabasser — Thu, 10 Jul 2025 00:00:00 +0000

Empathy shapes our interactions and is an important foundation for our relationships, be they private or professional. The fact that there are people who lack empathy raises the question of whether empathy can be learned. This research focuses on exploring how AI-based empathy training can help promote human empathy. It employs three methodological approaches: (1) an expert interview with a specialist in empathy, (2) expert questionnaires, and (3) scenario-based questionnaires answered by both humans and ChatGPT, with results compared using the IRI assessment. This study concludes that AI-supported training, provided it meets certain requirements, must be fundamentally human-centered. Successful AI-supported empathy training enables realistic yet harm-free emotional experiences and incorporates diversity considerations directly into algorithm design. Both ethical and psychological prerequisites such as trust, emotional security, and cultural sensitivity as well as design requirements for AI interaction, need to be met. While AI-supported training can never replace human interaction, it may complement it. Furthermore, ChatGPT already demonstrates empathetic responses to the scenario-based questionnaires without being explicitly prompted to do so.