Digitalization Strategies in ASEAN MSMEs Harnessing AI for Competitive Advantage in the Global Value Chain: A Model Conceptual

The implementation of artificial intelligence (AI) and digitalization in ASEAN MSMEs has garnered significant attention in optimizing their contributions to the global value chain. This study aims to develop a conceptual model that analyzes digitalization strategies in ASEAN MSMEs, harnessing AI to attain competitive advantage within the global value chain. This model integrates concepts from business strategy theory, information technology, and global economics. The primary contribution of this research lies in conceptualizing a comprehensive view of how ASEAN MSMEs can embrace AI as a primary driver in formulating effective digital strategies, thus enabling them to compete in an increasingly interconnected and competitive global marketplace. Keywords: Digitalization, Artificial Intelligence, ASEAN MSMEs, Global Value Chain, Business Strategy, Competitive Advantage, Information Technology, Global Economics

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

German and Israeli Innovation: The Best of Two Worlds

This study reviews – through desk research and expert interviews with Mittelstand companies, startups and ecosystem experts – the current status of the Israeli startup ecosystem and the Mittelstand region of North Rhine- Westphalia (NRW), Germany. As a case study, it highlights potential opportunities for collaboration and analyzes different engagement modes that might serve to connect the two regions. The potential synergies between the two economies are based on a high degree of complementarity. A comparison of NRW’s key verticals and Israel’s primary areas of innovation indicates that there is significant overlap in verticals, such as artificial intelligence (AI), the internet of things (IoT), sensors and cybersecurity. Israeli startups can offer speed, agility and new ideas, while German Mittelstand companies can contribute expertise in production and scaling, access to markets, capital and support. The differences between Mittelstand companies and startups are less pronounced than those between startups and big corporations. However, three current barriers to fruitful collaboration have been identified: 1) a lack of access, 2) a lack of transparency regarding relevant players in the market, and 3) a lack of the internal resources needed to select the right partners, often due to time constraints or a lack of internal expertise on this issue. To ensure that positive business opportunities ensue, Mittelstand companies and startups alike have to be proactive in their search for cooperation partners and draw on a range of existing engagement modes (e.g., events, communities, accelerators). The interviews and the research conducted for this study made clear that no single mode of engagement can address all the needs and challenges associated with German-Israeli collaboration

The Digitalisation of African Agriculture Report 2018-2019

An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains

Digital Analytics:Modeling for Insights and New Methods

Firms are increasingly turning towards new-age technologies such as artificial intelligence (AI), the internet of things (IoT), blockchain, and drones, among others, to assist in interacting with their customers. Further, with the prominence of personalization and customer engagement as the go-to customer management strategies, it is essential for firms to understand how to integrate the new-age technologies into their existing practices seamlessly to aid in the generation of actionable insights. Towards this end, this study proposes an organizing framework to understand how firms can use digital analytics, within the changing technology landscape, to generate consumer insights. The proposed framework begins by recognizing the forces that are external to the firm that then leads to the generation of specific capabilities by the firm. Further, the firm capabilities can lead to the generation of insights for decision making that can be data-driven and/or analytics-driven. Finally, the proposed framework identifies the creation of value-based outcomes for firms and customers, resulting from the insights generated. Additionally, we identify moderators that influence (a) the impact of external forces on the development of firm capabilities, and (b) the creation of insights and subsequent firm outcomes. This study also identifies questions for future research that combines the inclusion of new-age technologies, generation of strategic insights, and the achievement of established firm outcomes

The utilization of artificial intelligence in online advertising and its perceived effectiveness

This study explores the utilization of Artificial Intelligence in online advertising process and the impact of using AI each stage in that process with the overall perceived effectiveness. It also provides a better understanding of the magnitude of using AI in the four stages of advertising online: namely consumer insights, ad creation, media planning and buying, and finally ad evaluation. Process model of AI utilization in online advertising is the conceptual model of the study, which is developed from the previous literature. A triangulation methodology is implemented to enhance the credibility of the research study and leads to a more comprehensive understanding of the topic. Online survey is conducted with digital advertisers worldwide from both agency and client side. Nonrandom sampling (N=60) was implemented to test 5 constructs from the perspective of the respondents. Three in-depth interviews were also conducted before and after the online questionnaire to analyze the findings and results and demonstrate insights on the five proposed research questions. Findings of the study showed beyond doubt that AI is stepping strongly and progressively in the four stages of the data-based online advertising process. Moreover, it significantly showed that there is a relationship between AI utilization in each stage and the following one. Finally, results indicated that using AI in each advertising stage promotes the perceived effectiveness of the overall online ad process