The making of information nations

Purpose The purpose of this paper is to identify the main characteristics of what have come to be called information nations, and to identify some of the determinants of success in becoming an information nation. Design/methodology/approach The paper is based on a critical review of the literature and of secondary data on information technology and services from studies of the innovativeness of nations. Findings Success in becoming an information nation is not necessarily closely connected with investments in information technology and services by firms and policies supporting these investments by governments, or with education policies designed to support the development of science, technology, engineering and mathematics. Other factors, such as the vibrancy of capitalism, particularly the funding of new ventures, the culture of the nation, and its focus on non-scientific determinants of innovation, such as design, are also important. Governments should be careful not to take credit for achievements when their policies are merely coincident with those achievements. Research limitations/implications The main limitations relate to the focus of this article on two sets of nations, South East/East Asia and two Western nations. The review of their performance is relatively high level and needs to be deepened, while the number of nations included in the research needs to be increased. Practical implications This article has substantial practical implications for government policy makers, in terms of whether and how they should make policy at all in this area, and for companies trying to establish a long-term position in the global economy, in terms of being careful not to go against the very strong economic forces which favour certain kinds of activities in certain countries. Social implications This article has significant social implications, because much of the thinking about developing information societies relies on generalisations about the creation of information nations that may not hold. Governments and social commentators are encouraged to approach the idea of making “big policies” in this area with some scepticism. Originality/value The content of this article is not original, but the challenge to policy makers is relatively original, as too often the work of academics is sponsored by governments that are trying to legitimate the value of their own efforts

The evolution of business models of information and communication technology suppliers

Purpose: The purpose of this paper is to show how the business model of the information and communications technology (ICT) industry has evolved and the general differences that evolution has made to information management. Design/methodology/approach: Literature review was carried out accompanied by conceptual analysis. Findings: It shows that changes in the business model of the ICT industry have been quite dramatic and have led to significant changes in the structure of the industry. Research limitations/implications: This research is based on analysis of the ICT industry. The analysis could be broadened to include other industries. Research into business model change should consider adopting the evolutionary approach taken in this paper. Practical implications: Managers in the ICT industry should factor the likely evolution of business models in their industry into their planning. Social implications: Government policymakers considering how to stimulate the development of the ICT industry in their country should be aware of the moving nature of their target. Originality/value: This is one of the first papers to apply the evolutionary approach to business model change

Reciprocating Business Model Innovation – How Client and Supplier Models Interact

Purpose. The purpose of this article is to show the relationship between changes of industry business model on the supplier side and changes in business model on the client side, using the information technology industry as an example. This is the first paper to investigate supplier-side industry-wide business models and identify their consequences for client-side industry-wide business models. Methodology. The methodology is a review of academic and gray literature and conceptual analysis, applied particularly to three client-side industry case studies – financial services, airlines and online video streaming services Findings. Changes in the business model on the client side may be contingent on the products and services that emerge from the information and communications technology industry as it changes its business models. Practical implications. Client-side companies formulating their business strategies in industries which are highly dependent on successful information management should factor developments in the information and communications technology industry business models into account in their planning. They should also consider how they can influence business model change on the supplier side by changes they make to their information management strategies and processes. Research implications. The implications for research are that researching investigating changes in business models, particularly in relation to clients of the IT industry, should consider whether there have been changes in business models on the supplier or client side, and whether and how they have interacted

The evolution of business models of information and communication technology suppliers

Abstract Purpose ? The purpose of this paper is to show how the business model of the information and communications technology (ICT) industry has evolved and the general differences that evolution has made to information management. Design/methodology/approach ? Literature review was carried out accompanied by conceptual analysis. Findings ? It shows that changes in the business model of the ICT industry have been quite dramatic and have led to significant changes in the structure of the industry. Research limitations/implications ? This research is based on analysis of the ICT industry. The analysis could be broadened to include other industries. Research into business model change should consider adopting the evolutionary approach taken in this paper. Practical implications ? Managers in the ICT industry should factor the likely evolution of business models in their industry into their planning. Social implications ? Government policymakers considering how to stimulate the development of the ICT industry in their country should be aware of the moving nature of their target. Originality/value ? This is one of the first papers to apply the evolutionary approach to business model change

Artificial Intelligence (AI) in Strategic Marketing Decision-Making: A research agenda

Purpose The purpose of this article is to review literature and thinking about the application of AI in strategic situations and to identify the research that is needed in the area of applying AI to strategic marketing decisions. Design/methodology/approach Review of literature and consultation with marketing experts who were invited to contribute to the article. Findings There is little research into applying AI to strategic marketing decision-making. This is needed as the frontier of AI application to decision-making is moving in many management areas from operational to strategic. Given the competitive nature of such decisions and the insights from applying AI to defence and similar areas, it is time to focus on applying AI to strategic marketing decisions. Research limitations/implications Applying AI to strategic marketing decision-making is known to be taking place, but the it is commercially sensitive, so data is not available to the authors. Practical implications There are strong implications for all businesses, particularly large businesses in competitive industries, where failure to deploy AI in the face of competition from firms who have deployed AI to improve their decision-making could be dangerous. Social implications The public sector is a very important marketing decision-maker. Although in most cases it does not operate competitively, it must still make decisions about making different services available to different citizens and identify the risks of not providing services to certain citizens, so this article is relevant to the public sector. Originality/value This is one of the first articles to probe deployment of AI in strategic marketing decision-making. Keywords Artificial intelligence, marketing, decision-making, strategy, planning, operations

Artificial intelligence (AI) in strategic marketing decision-making : a research agenda

Purpose The purpose of this article is to review literature and thinking about the application of AI in strategic situations and to identify the research that is needed in the area of applying AI to strategic marketing decisions. Design/methodology/approach Review of literature and consultation with marketing experts who were invited to contribute to the article. Findings There is little research into applying AI to strategic marketing decision-making. This is needed as the frontier of AI application to decision-making is moving in many management areas from operational to strategic. Given the competitive nature of such decisions and the insights from applying AI to defence and similar areas, it is time to focus on applying AI to strategic marketing decisions. Research limitations/implications Applying AI to strategic marketing decision-making is known to be taking place, but the it is commercially sensitive, so data is not available to the authors. Practical implications There are strong implications for all businesses, particularly large businesses in competitive industries, where failure to deploy AI in the face of competition from firms who have deployed AI to improve their decision-making could be dangerous. Social implications The public sector is a very important marketing decision-maker. Although in most cases it does not operate competitively, it must still make decisions about making different services available to different citizens and identify the risks of not providing services to certain citizens, so this article is relevant to the public sector. Originality/value This is one of the first articles to probe deployment of AI in strategic marketing decision-making. Keywords Artificial intelligence, marketing, decision-making, strategy, planning, operations