Structuring information work: Ferranti and Martins Bank, 1952-1968

The adoption of large-scale computers by the British retail banks in the 1960s required a first-time dislocation of customer accounting from its confines in the branches, where it had been dealt with by paper-based and mechanized information systems, to a new collective space: the bank computer center. While historians have rightly stressed the continuities between centralized office work, punched-card tabulation and computerization, the shift from decentralized to centralized information work by means of a computer has received little attention. In this article, I examine the case of Ferranti and Martins Bank and employ elements of Anthony Giddens’s structuration theory to highlight the difficulties of transposing old information practices directly onto new computerized information work

The Rise of Computerized High Frequency Trading: Use and Controversy

Over the last decade, there has been a dramatic shift in how securities are traded in the capital markets. Utilizing supercomputers and complex algorithms that pick up on breaking news, company/stock/economic information and price and volume movements, many institutions now make trades in a matter of microseconds, through a practice known as high frequency trading. Today, high frequency traders have virtually phased out the dinosaur floor-traders and average investors of the past. With the recent attempted robbery of one of these high frequency trading platforms from Goldman Sachs this past summer, this rise of the machines has become front page news, generating vast controversy and discourse over this largely secretive and ultra-lucrative practice. Because of this phenomenon, those of us on Main Street are faced with a variety of questions: What exactly is high frequency trading? How does it work? How long has this been going on for? Should it be banned or curtailed? What is the end-game, and how will this shape the future of securities trading and its regulation? This iBrief explores the answers to these questions

Entrepreneurs'' attitude towards the computer and its effect on e-business adoption

This paper presents research exploring further the concept that many SMEs do not adopt computer based technologies due to decision maker's negative attitudes towards computers generally. Importantly, by assessing the entrepreneur's belief structure, we provide quantitative evidence how SMEs, particularly micros, are affected. Earlier research that addresses technology acceptance model (TAM) suggests that TAM parameters are particularly influential factors of e-commerce adoption, as perceived by top managers of SMEs. The model we develop is tested using a sample of 655 enterprises. The information was gathered, via a telephone survey of UK SMEs, from decisions makers in the enterprise. Technically, the paper uses k-means cluster analysis to segment respondents using the TAM perceptions, ease of use, usefulness and enjoyment. Based on two determined segments we look at the differential rate of adoption of internet, and the potential adoption of new e-collaborative technologies like video conferencing and electronic whiteboards. The diffusion of internet for low IT utility (LIT) segments was considerably slower than in the high utility segment (HIT). Similarly, the anticipated adoption of e-collaboration technologies was much lower for LIT than HIT. Interestingly, we find that LIT is populated by more micro SMEs than HIT. The results we present are limited however as our sample is considerably underweight in micro SMEs, suggesting that the problem may be much larger in the economy than our model predicts. For policy makers, this research confirms the value of knowledge transfer programs to SMEs in the form of technology support. Our research shows that organisations which have dedicated IT support will tend to be more advanced technologically than those that do not. The implication for entrepreneurs is if they can be persuaded that a technological route is beneficial to them, and that suitable support can be provided via KT, then operational efficiency gains could be made. This paper contributes to knowle

Big Data in the Oil and Gas Industry: A Promising Courtship

The energy industry remains one of the highest money-producing and investment industries in the world. The United States’ own economic stability depends greatly on the stability of oil and gas prices. Various factors affect the amount of money that will continue to be invested in producing oil. A main disadvantage to the oil and gas industry is its lack of technological adaptation. This weakens the industry because the surest measures are not currently being taken to produce oil in optimally efficient, safe, and cost-effective ways. Big data has gained global recognition as an opportunity to gather large volumes of information in real-time and translate data sets into actionable insights. In a low commodity price environment, saving time, reducing costs, and improving safety are crucial outcomes that can be realized using machine learning in oil and gas operations. Big data provides the opportunity to use unsupervised learning. For example, with this approach, engineers can predict oil wells’ optimal barrels of production given the completion data in a specific area. However, a caveat to utilizing big data in the oil and gas industry is that there simply is neither enough physical data nor data velocity in the industry to be properly referred to as “big data.” Big data, as it develops, will nonetheless significantly change the energy business in the future, as it already has in various other industries.Petroleum and Geosystems Engineerin

Automation and Management Accounting in British Manufacturing and Retail Financial Services, 1945-1968

This article looks at the effects of office mechanisation in greater detail by describing data processing innovations in major building societies during the dawn of the computer era. Reference to similar developments in clearing banks, industrial and computer organisations provides evidence as to the common experience in the computerisation of firms in the post-war years. As a result, research in this article offers a comparison between widespread technological change and changes unique to service sector organisations. Moreover, research in this article ascertains the extent to which the adoption of computer-related innovations in financial services sought to satisfy financial, rather than management accounting, purposes.banks, building societies, manufacturing, computers

Global supply chains of high value low volume products

Imperial Users onl