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Examines energy usage in buildings. Discusses how simple design can be used to good effect. Discusses control systems, installation and maintenance. Stresses that simplicity of design, installation and maintenance should be considered at the outset. Concludes that consideration of capital cost alone is a mistake.

Building developments are often capital intensive, have a long payback period and many associated risks and uncertainties. This makes investments in building projects to be a big challenge. This study aims to develop a computerized simulation-based binomial model (CSBBM) for building investment appraisal with a view to improving the economic sustainability of proposed building projects.

Mathematical equations and algorithms were developed based on the binomial method (BM) of real options analysis and then implemented on a computer system. A hybrid algorithm that integrates Monte Carlo simulation (MCS) and BM was also developed. A real-life project was used to test the model. Sensitivity analysis was also conducted to explore the influence of input variables on development option value (DOV).

The test result shows that the model developed provides a better estimate of the value of an investment when compared with traditional net present value technique, which underestimate the value. Moreover, inflation rate (i) and rental value (Ri) are the most sensitive variables for DOV. An increase in i and Ri by just 5% causes a corresponding increase in DOV by 202% and 132%, respectively. While the least sensitive variable is the discount rate (r), as an increase in r by 5% causes a corresponding decrease in DOV by just 9%. The CSBBM is capable of determining the optimal time of development of buildings with an accuracy of 80.77%.

The hybrid model produces higher DOV than that of only the BM because MCS considers randomness in uncontrollable variables. Thus, building investment decision-makers should always use MCS to complement the BM in an investment analysis.

There is limited evidence on the use of this kind of hybrid model for determining DOV in practice.

The purpose of this paper is to highlight the views of Professor George Arnold Wood, a leading Australian scholar at the University of Sydney, concerning the involvement of the British Empire in the Great War of 1914-1918.

The author has examined all of Professor Wood’s extant commentaries on the Great War which are held in the archives of the University of Sydney as well as the biographical material on Professor Wood by leading Australian scholars. The methodology and approach is purely empirical.

The sources consulted revealed Professor Wood’s deeply held conviction about the importance of Christian values in the formation of political will and his belief that the vocation of politics is a most serious one demanding from statesmen the utmost integrity in striving to ensure justice and freedom, respect for the rights of others and the duty of the strong to protect the weak against unprincipled and ruthless states.

The paper highlights Professor Wood’s values as derived from the core statements of Jesus of Nazareth such as in the Sermon on the Mount. And as these contrasted greatly with the Machiavellian practice of the imperial German Chancellors from Bismarck onwards, and of the Kaiser Wilhelm II. It was necessary for the British Empire to oppose German war aims with all the force at its disposal. The paper illustrates the ideological basis from which Wood derived his values.

As the increase in manufacturing competitiveness forces organizations to use more sophisticated and complex software, system performance depends on clever systems design, efficient planning and scheduling of the related processes. For these advanced manufacturing systems the dependence on human competence is greater. However, previous studies indicate that the human aspects for successfully implementing such systems have been neglected. The objective here is to test the hypotheses that system complexity is inversely related to performance, and that training of system operators, and the quality of the man/machine interface reduces the negative impact of system complexity. A sample of discreet manufacturing systems from 128 organizations was used to test these hypotheses empirically. Moderated multivariate regression indicates that man/machine interfaces are significant contributors to reducing the negative effect of systems complexity. With a lower level of significance, operator training has a similar impact. For complex manufacturing systems software, it behoves managers to insure that the man/machine interface provides the desirable features outlined in this study.

The literature prescribing important determinants of innovation success is grouped into four main areas encompassing strategic leadership, competitive intelligence, management of technology, and specific characteristics of the company's innovation process. Further, industry clockspeed has been considered to be a possible moderator for these determinants of innovation success. While these major areas of study may indeed be important to enhance company innovation and competitiveness, the existing literature on each area is not being shared by researchers in the other areas. That has led until now to the study of models relatively narrow in scope and primarily focused on the particular research area. This study aims to test these constructs as a set of determinants of innovation success and the possible moderating effect of industry clockspeed.

A field test using a mailed questionnaire to collect a relatively large sample has been used to test the proposed model. To eliminate possible multicollinearity among the independent variables, a multivariate regression analysis was used.

The results provide clear evidence about the importance of industry clockspeed as a moderator of the relationships between strategic leadership, competitive intelligence, management of technology, and specific characteristics of the company's innovation process with company success in business innovation. Also, the company's change process as defined here is equally important to low and high clockspeed industries for successfully implementing business innovations.

Despite the relatively broad scope of the proposed model, other factors may also be important and should be included in future studies.

The items used for measuring the main constructs provide further and more specific insights into how managers should go about developing these areas within their organizations.

While the study is grounded in the literature of what until now have been four separate areas of knowledge, it proposed an integrated model for these areas important to business innovation, and empirically tested the model.

Presents a framework of manufacturing competence, and tests its theoretical validity using empirical data from a large‐scale survey. Interesting findings include: the regression analysis shows that manufacturing competence is better represented when low‐priority capabilities are not explicitly considered; the manufacturing competence index appears to have more significant statistical relationships with some performance measures (such as the return on assets and return on sales) than with others – manufacturing matters, but not equally to all the financial and market performance; the concept of manufacturing competence is found to be more influential in determining the business performance in the electronics sector than in the machinery industry. Does manufacturing competence matter equally in all industries, or does it matter more in a specific industry? If so, what makes manufacturing competence so important? Advocates further study to answer these questions and to complete the theory of manufacturing competence.

This study aims to test the moderating impact of competition intensity on the relationships between the new product development (NPD) success factors and company success in NPD.

A mailed questionnaire collected information from 311 manufacturing companies to test the proposed model with moderated multivariate regression analysis.

The results corroborate the impact of competition intensity on the relationships between the success factors individually and company success performing NPD.

Despite the relatively broad scope of the proposed model, other success factors and/or moderating and mediating variables may also be important. As such, these variables should be identified and tested in future studies.

In practice, competition is viewed as an unavoidable factor beyond the control of managers within a company. Undeniably, competition is a great stimulant for business innovation. Thus, it is important for managers to understand the need, to focus attention managing the success factors most important to increase the likelihood of long-term success for NPD projects, particularly in markets under intense competition.

While the study is grounded on well-established literature, its major constructs originated from relatively isolated areas of knowledge. The major contribution is empirically testing an integrated model for variables considered important for success in NPD and the moderating effect of intense competition.

The prayer against the Poultry (Hygiene) Regulations which we briefly mentioned in the editorial of our last issue, was lodged as a result of activity by the Environmental Health Officers' Association. Incidentally it is the first occasion as far as we can recall that a prayer has been lodged against any of the rash of food regulations of recent years, and reflects the strong feelings of the public health inspectorate.

Reports that over the past several years, the concept of manufacturing strategy has been at the forefront of both managerial and academic thought, and that studies in the field lack a cohesive foundation that can guide researchers’ efforts in building a testing theory ‐ the research gap. States that an inability to relate specific programmes to long‐term objectives demonstrates the difficulty in bringing manufacturing strategy to the factory floor ‐ the practice gap. Believes that the unsatisfactory progress observed in research and practice is because of the failure to study rigorously the process of operationalizing manufacturing strategy. Builds a process model of manufacturing strategy and presents the results. Describes the model which focuses on three constructs of manufacturing strategy: competitive priorities, manufacturing objectives and action programmes for investment. Using data from a large‐scale survey, explores how manufacturing managers attempt to link their decisions in those three components of manufacturing strategy.