Pervasive Computing, Firm Characteristics, and Environmental Factors Conducive to the Adoption of Activity-Based Costing: Evidence from Bahrain
Sayel Ramadhan (Ahlia University, Kingdom of Bahrain)
Copyright © 2010.
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The main purpose of this study is to provide evidence on the contextual featutres of firms adopting Activity-Based Costing (ABC) compared to those not adopting ABC. The study examines certain organisational and business environment variables which appear to have influenced the adoption of ABC. Based on a review of the relevant literature, it is hypothesised that firm size, the amount of overhead costs, the level of product variety, production complexity, the degree of competition, and the degree of computer usage are factors which encourage firms to adopt ABC. A list of manufacturing companies operating in Bahrain (332 firms) was obtained from the Ministry of Industry. Firms with (50) workers or more were selected for the study. The reason for limiting the study to firms with this number of workers is that small firms are less likely to be able to afford the cost of adopting and implementing an ABC system and its required changes. Total of (111) firms met this size criterion and a questionnaire was developed and distributed to the entire sample. Fifty seven questionnaires were returned completed; a response rate of (51.4%). The results of the study show that a small percentage of Bahraini manufacturing companies are adopting or planning to adopt ABC systems (26.3%). There were significant relationships between the adoption of ABC and the variables selected for the study except production complexity and the degree of computer usage. The results are consistent with previous research. However, further research using a case study approach with semi-structured interviews could be conducted in those firms which claim to have adopted ABC. This approach might be fruitful and would provide more insight in identifying the characteristics of ABC companies in the Bahraini context.
The futures trading became electronic business when widespread use of internet technologies occurred. There exist many electronic markets since 90’s and at present day they are equal in both size (quantity) and importance to the traditional trading. When the electronic trading became possible, the computing power of computers allowed many tasks to be automated. It is possible to automatically process market data and to perform the analysis very quickly, automating part of the decision-making process and leaving only small part of the work to be handled by trader.
From the point of view of electronic trading, it is trading of stocks that are in the centre of interest of scientific community. There are several differences between stock trading and futures trading. Discussion about the differences can be found in e.g. (Williams, 1979, pp. 17-20). But there is much in common for both types of trading and we will not be strictly separating stock trading from commodities (futures) trading. In the following text whenever the notion “trading” is mentioned, it is a futures trading that we have in mind. Many (not all) indicators useful for the futures markets are useful for trading stocks as well and vice versa. The principle is usually similar.
This chapter is focused on lifecycle of design of automatic trading system. Its purpose is to present and summarize rules of design, important notes on the topic and discussion of typical issues. No specific automatic trading system will be presented in this text. However, as we hope, it may bring some interesting insights into this problem area.
The investment decision-making process consists basically of two parts. First part of this process is fundamental analysis, second part is technical analysis. For the purpose of automatic trading it is a technical analysis that is more important for us. But best outcome is archived when both parts takes place in the decision-making process. Because this matter will be discussed in the following text for the moment it could be said that fundamental analysis represents the “what”, while technical analysis is the “when”. The concept of fundamental analysis in commodity trading is covered in (Dunsby, 2008). Dunsby (2008) is focused on selected categories of commodities only – energies, grains and oilseeds, livestock, industrial materials, softs. However, this publication gives reader the right perspective of fundamental analysis importance and application on real-life situations.
The cycle of steps of system design is usually done during the mentioned investment decision-making process (IDMP), allowing some part of this process to be automated. It is not necessary to have automated the whole IDMP. An automatic trading system (ATS) may cover only the technical analysis part and provide the best outcome of the applied indicators to the user in order to allow him to make the final decision. It is also possible to leave whole process to the ATS itself, but the former solution is usually preferred by traders.
In the following text, we would refer to trader as to “him”, instead of “him or her”, as it would be more appropriate. By this, we do not mean any disrespect to female traders. This simplification is used in order to make reading easier.
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