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There are a plethora of putative influencing variables available in the literature for modelling real estate prices using AI. Their choice tends to differ from one researcher to the other, consequently leading to subjectivity in the selection process. Thus, there is a need to seek the viewpoint of practitioners on the applicability and level of significance of these academically established variables.

Using the Delphi technique, this study collated and structured the 35 underlying micro- and macroeconomic parameters derived from literature and eight variables suggested by 11 selected real estate experts. The experts ranked these variables in order of influence using a seven-point Likert scale with a reasonable consensus during the fourth round (Kendall's W = 0.7418).

The study discovered that 16 variables are very influential with seven being extremely influential. These extremely influential variables include flexibility, adaptability of design, accessibility to the building, the size of office spaces, quality of construction, state of repairs, expected capital growth and proximity to volatile areas.

The results of this study improve the quality of data available to valuers towards a fortified price prediction for investors, and thereby, restoring the valuers' credibility and integrity.

The “volatility level of an area”, which was revealed as a distinct factor in the survey is used to add to current knowledge concerning office price. Hence, this study offers real estate practitioners and researchers valuable knowledge on the critical variables that must be considered in AI-based price modelling.

This paper sets out to examine the factors influencing internet‐based e‐commerce in the electronic manufacturing companies in Malaysia.

The sample data are derived from a questionnaire survey of 194 companies selected from the Federation of Malaysian Manufacturer lists to investigate the study hypotheses. Roger's five innovation diffusion characteristics were considered as factors that affect EC adoption and security/confidentiality was taken as an additional factor for this study.

The multiple regression analysis results indicate that relative advantage, compatibility, complexity, observability and security appear significant. Relative advantage and compatibility have positive and significant influence on EC adoption whereas complexity and security have negative effects. This study also revealed a non‐significant relationship between trialability and e‐commerce adoption.

The results are limited within the sample of electronic manufacturing companies in Malaysia, so the results cannot be generalized.

This study provides a greater understanding of managers' perception of e‐commerce adoption in their manufacturing companies. Those interested in promoting their business online may find these results helpful in guiding their efforts.

The purpose of this paper is to identify the relationships between risk management committee characteristics and risk taking of the Malaysia's insurance companies, from 2003‐2011. The paper aims to examine three identified characteristics of a risk management committee, namely, size, independence, and number of meetings.

The sample comprises 329 observations throughout the nine years' time frame until 2011. Pearson's correlation, pooled ordinary least squares regression, and panel regression model are used in this study. Sensitivity testing with an alternative measure of underwriting risk is also performed.

Out of the three characteristics, size and committee independence appear to be negatively associated with underwriting risk. Meanwhile, the frequency of risk management committee meetings is insignificant in this study.

The sample of this study is limited to the Malaysia's insurance sector only.

A risk management committee is an influencing force for risk oversight and the internal control system. The empirical evidence enriches the understanding of corporate governance in the context of the role of a risk management committee.

The purpose of this paper is to investigate empirically the critical factors for the diffusion of web technologies in supply chain management (SCM) functions, based on the technology‐organizational‐environment model, and to identify the benefits resulting from diffusion.

Data were collected, via an internet survey, from 251 respondents, ranging from middle‐level to top‐level managers, from firms which currently utilize web technologies for their supply chain activities. Structural equation modelling was employed for five factors: relative advantage; competitive pressure; complexity; trialability; and top management support, which have been hypothesized to affect the diffusion of web technologies in SCM functions.

The results suggest that all the factors except trialability are significant predictors of web technologies' diffusion in supply chain functions. The results show also that by diffusing web technologies, organizations can enhance their supply chain activities.

The survey was conducted in a Malaysian context, using a limited set of variables, thus limiting the generalizability of the findings.

This study provides a greater understanding of managers' perception of web technology diffusion in their organizational SCM functions, and benefits realizing from diffusion of web technology, such as operational efficiency.

Those interested in adopting web technologies in their supply chain activities may find these results helpful in guiding their efforts.