Search results

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

As the most disruptive technologies, Artificial Intelligence (AI) has been considered as a reliable tool in processing data to enhance business performance. Along with the increasing amount of data generated through online activities by customers, various hospitality companies have been investing in AI-powered solutions to be able to have better understanding about their customers and provide the relevant service to them accordingly. Despite knowing the impact on the customer service orientation, little is known about the impact of AI on the business process of a hospitality company. This paper explores the impact of the adoption of the AI on the business process of a hospitality company to have a better understanding of the extent of particular part of the business process that would benefit from the adoption of AI. It is apparent that Revenue Management and Marketing are the parts of business process within the hospitality industry that would have more positive impact on the adoption of AI. While AI-based marketing would be able to identify and target effectively high-value consumers, revenue management would be able to determine the right pricing strategy in real time due to the vast amount of available data and subsequently would have positive impact on the financial performance of the hospitality company.

The objective of this chapter is to identify the key characteristics of Global Services businesses that will thrive and achieve success in the future. These factors are integrated into three main pillars, which we refer to as the Triple-Win. The first and most obvious pillar is technology as a tool. The second pillar is the design and sustainability of the business model, without which the previous factor would be merely a cost and not an investment. And last but not the least, there is the purpose which gives meaning to the proposal, focusing on the human being and their environment. The DIDPAGA business model sits at the intersection of these three elements.

Introduction: Artificial intelligence (AI) has progressed significantly over the past few years, evolving into a collection of innovative tools that provide a competitive advantage to businesses. The acceptance and investment in AI are skyrocketing over the globe. The entry of AI in the workplace automates tasks and impacts making a timely decisions. At the same time, the workforce is not ready to welcome the new technology due to the skill gap. The organisation has to face many challenges in reskilling and convincing the workforce to incorporate AI in their work.

Purpose: With this study, the authors aim to analyse and highlight the introduction of AI in the organisation and the call for the reskilling of the workforce. To figure out what skills are most important for employees to learn to advance their careers.

Methodology: Given the deductive nature of the study, the researchers used secondary data collected and compiled from research papers, publications, websites, HR blogs, survey reports, etc. Research papers from reputed journals, reports of consultancies and agencies have been considered to synthesise the information and present it in a systematic manner and to derive the conclusion.

Findings: The findings indicate AI’s capabilities and applications have grown considerably, which shows the importance of AI in a growing number of fields, yet several hurdles need to be overcome, the most prominent one being the issues concerning upskilling the workforce for the future of AI. This study reveals the change in the perceived importance of the skills in the present and future times. Reskilling and upskilling the workforce and creating new talent to meet the changing employment demands is becoming increasingly important.

In this chapter, a general introduction on artificial intelligence (AI) is given as well as an overview of the advances of AI in different engineering disciplines, including its effectiveness in driving the United Nations Sustainable Development Goals (UN SDGs). This chapter begins with some fundamental definitions and concepts on AI and machine learning (ML) followed by a classification of the different categories of ML algorithms. After that, a general overview of the impact which different engineering disciplines such as Civil, Chemical, Mechanical, Electrical and Telecommunications Engineering have on the UN SDGs is given. The application of AI and ML to enhance the processes in these different engineering disciplines is also briefly explained. This chapter concludes with a brief description of the UN SDGs and how AI can positively impact the attainment of these goals by the target year of 2030.