Characteristics of the Multiple Attribute Decision Making Methodology in Enterprise Resource Planning Software Decisions

Realising information technology (IT) decisions and implementations are consistently seen as major challenges of business management faced with increasingly complex IT environments. This article seeks to increase the awareness of the multiple attributive decision making methodology (MADM) in the context of enterprise resource planning (ERP) projects and provides empirical insights based on 209 datasets originating from a primary, national and industry independent survey. The given MADM topics comprise strategic alignment, attributes with associated importance weightings, considered and chosen systems, methodical utilisation, follow-up controlling, andfinally MADM relevance in terms of a possible connection between MADM and ERP success. The results in particular show that while the ERP decision problem seems to be structured based on the MADM principle, the minority of decision makers rely on a formal MADM method. The empirically tested measurement model indicates that success according to expectations was achieved at a greater level of magnitude in firms supported by a formal MADM method, especially in terms offinancial firm level impact and service quality

Behavioural responses of pasture based dairy cows to short term management in tie-stalls

peer-reviewedDairy cows in experimental grazing herds are often confined for metabolic measurements. The objective of this study was to establish effects of transfer from pasture, to tie-stalls in a metabolism house, then back to pasture, on lying behaviour and locomotion score of lactating cows: Holstein-Friesian (H, n = 16), Jersey (J, n = 16) and H × J (HJ, n = 16). Cows were transferred to tie-stalls on d 1 for 12 days, and were offered freshly cut ryegrass according to herbage allowance (HERB) and genotype: J low = 14; J high = 17; H and HJ low = 16; and H and HJ high = 20 kg DM/d. Lying behaviour was recorded on four days: −2, −1 (Pre-confinement), 3 (Early confinement), 10, 11 (Late confinement), 13 and 14 (Post-confinement) relative to transfer (d 1) using dataloggers, and was also video-recorded during the first 15 h. Locomotion score was recorded on days −4, −3, 12 and 16. No effects of HERB on lying variables were observed during the first 15 h in confinement, but J cows made more lying intentions (21.0 vs. 12.2; P < 0.05) and tended (P = 0.07) to have a shorter latency to lie. Cows spent less (P < 0.001) time lying in early confinement (07:22:29 h/d) than on any of the other occasions (9:12:50 h/d). Cows had more (P < 0.001) and shorter (P < 0.001) lying bouts in confinement than while at pasture. Low HERB cows spent more time lying than high HERB cows (09:54:55 vs. 09:09:33 h/d; P < 0.01). J had higher locomotion scores than H (9.2 ± 0.2 vs.7.8 ± 0.2; P < 0.001), and tended (P = 0.09) to have higher scores than HJ (8.5 ± 0.2) cows. Locomotion scores were lowest pre confinement, highest at turnout (d 12), and intermediate after that at pasture (d 16) (7.6 ± 0.2, 9.3 ± 0.2 and 8.6 ± 0.3, respectively; P < 0.01). On transfer to the metabolism house cows showed disrupted patterns of lying although daily lying time returned to levels similar to pasture by late confinement. Confinement also resulted in a short-term deterioration in locomotory ability, which although improving, was still evident 4 days following the cows return to pasture with Jersey cows being more affected than the other genotypes. These findings suggest that longer adaptation periods and temporary release to loafing areas may improve both the validity of data collected and cow welfare

Movement Behaviour of Traditionally Managed Cattle in the Eastern Province of Zambia Captured Using Two-Dimensional Motion Sensors

Two-dimensional motion sensors use electronic accelerometers to record the lying, standing and walking activity of cattle. Movement behaviour data collected automatically using these sensors over prolonged periods of time could be of use to stakeholders making management and disease control decisions in rural sub-Saharan Africa leading to potential improvements in animal health and production. Motion sensors were used in this study with the aim of monitoring and quantifying the movement behaviour of traditionally managed Angoni cattle in Petauke District in the Eastern Province of Zambia. This study was designed to assess whether motion sensors were suitable for use on traditionally managed cattle in two veterinary camps in Petauke District in the Eastern Province of Zambia. In each veterinary camp, twenty cattle were selected for study. Each animal had a motion sensor placed on its hind leg to continuously measure and record its movement behaviour over a two week period. Analysing the sensor data using principal components analysis (PCA) revealed that the majority of variability in behaviour among studied cattle could be attributed to their behaviour at night and in the morning. The behaviour at night was markedly different between veterinary camps; while differences in the morning appeared to reflect varying behaviour across all animals. The study results validate the use of such motion sensors in the chosen setting and highlight the importance of appropriate data summarisation techniques to adequately describe and compare animal movement behaviours if association to other factors, such as location, breed or health status are to be assessed

Remote non-invasive assessment of pain and health status in cattle

Cattle behavior is frequently monitored to determine health and wellness state of the animal. The objective of this review is to describe potential benefits and challenges of remotely monitoring cattle behavior with available methodologies including clinical illness scores, visual monitoring, accelerometers, pedometers, feed intake and behavioral monitoring, global position systems, real time location systems, thermography images, and rumen telemetry temperature bolus. The behavior of interest, labor required, and monitoring expenses all need to be taken into consideration before deciding which remote behavioral monitoring device is most appropriate. Monitoring the feeding behavior of an animal over a period of time allows establishment of a baseline against which deviations in subsequent behavioral patterns can be evaluated. Interpretation of multiple behavioral responses as an aggregate indicator of animal wellness status rather than as individual outcomes may be a more accurate measure of true state of animal pain or wellness status