Search results

The paper aims to describe and apply a commercially oriented method of forecast performance measurement (cost of forecast error – CFE) and to compare the results with commonly adopted statistical measures of forecast accuracy in an enterprise resource planning (ERP) environment.

The study adopts a quantitative methodology to evaluate the nine forecasting models (two moving average and seven exponential smoothing) of SAP^®'s ERP system. Event management adjustment and fitted smoothing parameters are also assessed. SAP^® is the largest European software enterprise and the third largest in the world, with headquarters in Walldorf, Germany.

The findings of the study support the adoption of CFE as a more relevant commercial decision‐making measure than commonly applied statistical forecast measures.

The findings of the study provide forecast model selection guidance to SAP^®'s 12+ million worldwide users. However, the CFE metric can be adopted in any commercial forecasting situation.

This study is the first published cost assessment of SAP^®'s forecasting models.

This paper aims to describe the development of a tailorable framework of practices for maintenance delivery (MD) and present a range of examples to demonstrate the tailoring process. The framework covers the entire scope of MD in detail, including several related subjects where significant business process interaction occurs. It offers a wide range of optional practices throughout, complete with expert guidance to enable tailoring based on the business context.

The framework was developed in two stages: firstly, via a review of existing MD processes from the literature to establish a preliminary version; this was then developed further via a Delphi study utilising the opinion of experts from industry to validate, critique and improve the initial framework design.

The completed framework was implemented and tested by the industrial sponsor of this research and was found to deliver significant improvement to their MD practices.

The tailorable nature of the framework means that it can be utilised by any business to design an MD process that is fully effective within their specific context. Alongside a tailored MD process, the framework will also generate a fully aligned implementation specification for the supporting computerised maintenance management system (CMMS), which is also tailored according to the same contextual requirements. This will enable the end user of the framework to procure, implement and configure a CMMS that has all of the functionality required to fully support their business requirements.

Innovation is delivered by combining a novel business process design tool with a software specification tool to solve a common industry problem (i.e. poor CMMS implementation).

The digital economy has significantly altered the way business is conducted and financial information is communicated. A rapidly growing number of organizations are conducting business and publishing business and financial reports online and in real-time. Real-time financial reporting is likely to necessitate continuous auditing to provide continuous assurance about the quality and credibility of the information presented. The audit process has, by necessity, evolved from a conventional manual audit to computer-based auditing and is now confronted with creating continuous electronic audits. Rapidly emerging information technology and demands for more timely communication of information to business stakeholders requires auditors to invent new ways to continuously monitor, gather, and analyze audit evidence. Continuous auditing is defined here as “a comprehensive electronic audit process that enables auditors to provide some degree of assurance on continuous information simultaneously with, or shortly after, the disclosure of the information.” This paper is based on a review of related literature, innovative continuous auditing applications, and the experiences of the authors. An approach for building continuous audit capacity is presented and audit data warehouses and data marts are described. Ever improving technology suggests that the real-time exchange of sensitive financial data will place constant pressure on auditors to update audit techniques. Most of the new techniques that will be required will involve creation of new software and audit models. Future research should focus on how continuous auditing could be constantly improved in various auditing domains including assurance, attestation, and audit services.

The purpose of this paper is two-fold. First, it explores the extent to which diversity of connectivity or the connection through multiple internet access points may facilitate online privacy behavior. Second, it explains the diversity of connectivity-online privacy behavior link in terms of information literacy.

Situated in the context of urban poor youth in the Philippines (n = 300), this paper used a quantitative approach, specifically an interview-administered survey technique. Respondents were from three cities in Metro Manila. To test for indirect relationship, survey data were analyzed using bootstrapping technique via SPSS macro PROCESS (Hayes, 2013).

Urban poor youth with diversified connection to the internet engaged in online privacy behavior. The more the youth are connected to the internet through diverse modalities, the more this fosters cautious online privacy behavior. In addition, information literacy explained how diversity of connectivity facilitated online privacy behavior. It suggests that differences in online privacy behavior may result from the extent of basic know-how of navigating online information. In the context of the urban poor in the Global South, the youth are constantly negotiating ways to not only connect to the internet but also acquire digital skills necessary for protective online behaviors.

To date, this is one of the few papers to contribute to conversations about online privacy among youth in the Global South. It broadens the literature on social determinants of online privacy behavior that is crucial for designing policy interventions for those in the margins.

The purpose of this article is to provide a critique of SAP's enterprise resource planning (ERP) (release ECC 6.0) forecasting functionality and offer guidance to SAP practitioners on overcoming some identified limitations.

The SAP ERP forecasting functionality is reviewed against prior seminal empirical business forecasting research.

The SAP ERP system contains robust forecasting methods (exponential smoothing), but could be substantially improved by incorporating simultaneous forecast comparisons, prediction intervals, seasonal plots and/or autocorrelation charts, linear regressions lines for trend analysis, and event management based on structured judgmental forecasting or intervention analysis.

The findings provide guidance to SAP forecasting practitioners for improving forecast accuracy via important forecasting steps outside of the system.

The paper contributes to the need for studies of widely adopted ERP systems to critique vendor claims and validate functionality through prior empirical research, while offering insights and guidance to SAP's 12 million+ worldwide enterprise system practitioners.

With a push toward inclusion of students with disabilities in the general education classroom, students who are d/Deaf or hard of hearing (DHH) are exposed to greater educational opportunities. Given the largely verbal nature of traditional classroom instruction, there has been a need for advancements in technology to provide more access to the material covered by teachers and in class discussions. In addition, the COVID-19 pandemic and the transition to virtual learning also brought to light many additional challenges for the DHH population, which can, in part, be lessened through technological advancements.

The purpose of this paper is a comparison of forecasting behaviour of small and large Austrian firms, analysing their forecast practices in a volatile business environment.

The empirical analysis of the paper, deductive by nature, was conducted by means of a quantitative online-survey (199 data sets). The relationship of perceived volatility and forecast predictability was evaluated by correlation analysis. t-Test and analysis of variances were used to examine significant differences in the forecast characteristics between small and large Austrian companies and different industries.

The study provides evidence that the surveyed companies have been hit by volatility, showing that Austrian SMEs are significantly more severely affected than large companies. The increasing volatility correlates with a reduced forecast predictability of sales quantities and commodity prices. Large Austrian companies primarily use a broad spectrum of qualitative forecasting methods. In contrast, Austrian SMEs utilize simple quantitative and qualitative forecast techniques, like the forward projection of historical data.

Relevant for the forecasting of small and large companies.

Although management requests a broad spectrum of forecast qualities, the current usage of less sophisticated methods reveals a gap between intention and reality. Companies that supplement their qualitative techniques by sophisticated quantitative ones should expect less forecast bias.

This paper initially compares forecast methods in large and small Austrian firms and additionally provides the impact of volatility on the forecast predictability.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.