A model for comparative analysis of inventory costs of JIT and EOQ purchasing in the ready mixed concrete industry

A model for comparing the inventory costs of purchasing under the economic order quantity (EOQ) system and the just-in-time (JIT) order purchasing system in existing literature concluded that JIT purchasing was virtually always the preferable inventory ordering system especially at high level of annual demand. By expanding the classical EOQ model, this paper shows that it is possible for the EOQ system to be more cost effective than the JIT system once the inventory demand approaches the EOQ-JIT cost indifference point. The case study conducted in the ready-mixed concrete industry in Singapore supported this proposition.

Development of a Mathematical Model for the Calculation of the Tool Appropriation Delay depending on the Tool Inventory

Compliance with punctual delivery under the high pressure of costs can be implemented through the optimization of the in-house tool supply. Within the Transfer Project 13 of the Collaborative Research Centre 489 using the example of the forging industry, a mathematical model was developed which determines the minimum inventory of forging tools required for production, considering the tool appropriation delay.

The choice of the model in inventory control and the cost of sophistication

This thesis is concerned with the inventory control of items that can be considered independent of one another. The decisions when to order and in what quantity, are the controllable or independent variables in cost expressions which are minimised. The four systems considered are referred to as (Q, R), (nQ,R,T), (M,T) and (M,R,T). Wiith ((Q,R) a fixed quantity Q is ordered each time the order cover (i.e. stock in hand plus on order ) equals or falls below R, the re-order level. With the other three systems reviews are made only at intervals of T. With (nQ,R,T) an order for nQ is placed if on review the inventory cover is less than or equal to R, where n, which is an integer, is chosen at the time so that the new order cover just exceeds R. In (M, T) each order increases the order cover to M. Fnally in (M, R, T) when on review, order cover does not exceed R, enough is ordered to increase it to M. The (Q, R) system is examined at several levels of complexity, so that the theoretical savings in inventory costs obtained with more exact models could be compared with the increases in computational costs. Since the exact model was preferable for the (Q,R) system only exact models were derived for theoretical systems for the other three. Several methods of optimization were tried, but most were found inappropriate for the exact models because of non-convergence. However one method did work for each of the exact models. Demand is considered continuous, and with one exception, the distribution assumed is the normal distribution truncated so that demand is never less than zero. Shortages are assumed to result in backorders, not lost sales. However, the shortage cost is a function of three items, one of which, the backorder cost, may be either a linear, quadratic or an exponential function of the length of time of a backorder, with or without period of grace. Lead times are assumed constant or gamma distributed. Lastly, the actual supply quantity is allowed to be distributed. All the sets of equations were programmed for a KDF 9 computer and the computed performances of the four inventory control procedures are compared under each assurnption.

Stability of the Inventory-Backorder Process in the (R; S) Inventory/Production Model

2000 Mathematics Subject Classification: 60G52, 90B30.

Fan motivation and loyalty : extending the Sport Interest Inventory (SII) to the Australian Football League

This study used the Sport Interest Inventory (SII) to examine the motivation of fans attending a game in the Australian Football League. This is the first study to use the SII for professional men’s team sport outside the United States. Confirmatory factor analysis showed the model provided a good fit for the data collected in Australia, and regression analysis revealed that team interest, vicarious achievement, excitement and player interest were the significant factors in predicting and explaining the level of attitudinal loyalty of fans toward their favourite team.

Development of a particle number and particle mass vehicle emissions inventory for an urban fleet

Motor vehicles are major emitters of gaseous and particulate pollution in urban areas, and exposure to particulate pollution can have serious health effects, ranging from respiratory and cardiovascular disease to mortality. Motor vehicle tailpipe particle emissions span a broad size range from 0.003-10µm, and are measured as different subsets of particle mass concentrations or particle number count. However, no comprehensive inventories currently exist in the international published literature covering this wide size range. This paper presents the first published comprehensive inventory of motor vehicle tailpipe particle emissions covering the full size range of particles emitted. The inventory was developed for urban South-East Queensland by combining two techniques from distinctly different disciplines, from aerosol science and transport modelling. A comprehensive set of particle emission factors were combined with traffic modelling, and tailpipe particle emissions were quantified for particle number (ultrafine particles), PM1, PM2.5 and PM10 for light and heavy duty vehicles and buses. A second aim of the paper involved using the data derived in this inventory for scenario analyses, to model the particle emission implications of different proportions of passengers travelling in light duty vehicles and buses in the study region, and to derive an estimate of fleet particle emissions in 2026. It was found that heavy duty vehicles (HDVs) in the study region were major emitters of particulate matter pollution, and although they contributed only around 6% of total regional vehicle kilometres travelled, they contributed more than 50% of the region’s particle number (ultrafine particles) and PM1 emissions. With the freight task in the region predicted to double over the next 20 years, this suggests that HDVs need to be a major focus of mitigation efforts. HDVs dominated particle number (ultrafine particles) and PM1 emissions; and LDV PM2.5 and PM10 emissions. Buses contributed approximately 1-2% of regional particle emissions.

Mechanisms of improvement in treatment for depression : test of a self-efficacy and performance model

Tested D. J. Kavanagh's (1983) depression model's explanation of response to cognitive-behavioral treatment among 19 20–60 yr old Ss who received treatment and 24 age-matched Ss who were assigned to a waiting list. Measures included the Beck Depression Inventory and self-efficacy (SE) and self-monitoring scales. Rises in SE and self-monitored performance of targeted skills were closely associated with the improved depression scores of treated Ss. Improvements in the depression of waiting list Ss occurred through random, uncontrolled events rather than via a systematic increase in specific skills targeted in treatment. SE regarding assertion also predicted depression scores over a 12-wk follow-up.

Developing the descriptions of landmark teaching styles : a spectrum inventory

Mosston & Ashworth‟s Spectrum of Teaching styles was first published in 1966 and is potentially the longest surviving model of teaching within the field of physical education. Its longevity and influence is surely testament to its value and influence. Many tools have also been developed through the years based on The Spectrum of Teaching Styles. In 2005 as part of a doctoral study, this tool was developed by the author, Dr Edwards and Dr Ashworth for researchers and teachers to identify which teaching styles were being utilised from The Spectrum when teaching physical education. It could also be utilised for self-assessment of the teaching styles and individual uses, or those who work with Physical Education Teacher Education courses. The development of this tool took approximately 4 months, numerous emails and meetings. This presentation will outline this process, along with the reasons why such a tool was developed and the differences between it and others like it.

University Student Depression Inventory (USDI) : confirmatory factor analysis and review of psychometric properties

Background: The 30-item USDI is a self-report measure that assesses depressive symptoms among university students. It consists of three correlated three factors: Lethargy, Cognitive-Emotional and Academic motivation. The current research used confirmatory factor analysis to asses construct validity and determine whether the original factor structure would be replicated in a different sample. Psychometric properties were also examined. Method: Participants were 1148 students (mean age 22.84 years, SD = 6.85) across all faculties from a large Australian metropolitan university. Students completed a questionnaire comprising of the USDI, the Depression Anxiety Stress Scale (DASS) and Life Satisfaction Scale (LSS). Results: The three correlated factor model was shown to be an acceptable fit to the data, indicating sound construct validity. Internal consistency of the scale was also demonstrated to be sound, with high Cronbach Alpha values. Temporal stability of the scale was also shown to be strong through test-retest analysis. Finally, concurrent and discriminant validity was examined with correlations between the USDI and DASS subscales as well as the LSS, with sound results contributing to further support the construct validity of the scale. Cut-off points were also developed to aid total score interpretation. Limitations: Response rates are unclear. In addition, the representativeness of the sample could be improved potentially through targeted recruitment (i.e. reviewing the online sample statistics during data collection, examining the representativeness trends and addressing particular faculties within the university that were underrepresented). Conclusions: The USDI provides a valid and reliable method of assessing depressive symptoms found among university students.

An examination of the factorial invariance and refinement of the multidimensional school anger inventory for five Pacific Rim countries

The validity of the Multidimensional School Anger Inventory (MSAI) was examined with adolescents from 5 Pacific Rim countries (N ¼ 3,181 adolescents; age, M ¼ 14.8 years; 52% females). Confirmatory factor analyses examined configural invariance for the MSAI’s anger experience, hostility, destructive expression, and anger coping subscales. The model did not converge for Peruvian students. Using the top 4 loaded items for anger experience, hostility, and destructive expression configural invariance and partial metric and scalar invariances were found. Latent means analysis compared mean responses on each subscale to the U.S. sample. Students from other countries showed higher mean responses on the anger experience subscale (ds ¼ .37–.73). Australian (d ¼ .40) and Japanese students (d ¼ .21) had significantly higher mean hostility subscale scores. Australian students had higher mean scores on the destructive expression subscale (d ¼ .30), whereas Japanese students had lower mean scores (d ¼ 2.17). The largest latent mean gender differences (females lower than males) were for destructive expression among Australian (d ¼ 2.67), Guatemalan (d ¼ 2.42), and U.S. (d ¼ 2.66) students. This study supported an abbreviated, 12-item MSAI with partial invariance. Implications for the use of the MSAI in comparative research are discussed.

Evaluating a model of parental influence on youth physical activity

Objective To test a conceptual model linking parental physical activity orientations, parental support for physical activity, and children's self-efficacy perceptions with physical activity participation. Participants and setting The sample consisted of 380 students in grades 7 through 12 (mean age, 14.0±1.6 years) and their parents. Data collection took place during the fall of 1996. Main outcome measures Parents completed a questionnaire assessing their physical activity habits, enjoyment of physical activity, beliefs regarding the importance of physical activity, and supportive behaviors for their child's physical activity. Students completed a 46-item inventory assessing physical activity during the previous 7 days and a 5-item physical activity self-efficacy scale. The model was tested via observed variable path analysis using structural equation modeling techniques (AMOS 4.0). Results An initial model, in which parent physical activity orientations predicted child physical activity via parental support and child self-efficacy, did not provide an acceptable fit to the data. Inclusion of a direct path from parental support to child physical activity and deletion of a nonsignificant path from parental physical activity to child physical activity significantly improved model fit. Standardized path coefficients for the revised model ranged from 0.17 to 0.24, and all were significant at the p<0.0001 level. Conclusions Parental support was an important correlate of youth physical activity, acting directly or indirectly through its influence on self-efficacy. Physical activity interventions targeted at youth should include and evaluate the efficacy of individual-level and community-level strategies to increase parents’ capacity to provide instrumental and motivational support for their children's physical activity.

Reliability of a wellness inventory for use among adolescent females aged 12-14 years

Background The wellness construct has application in a number of fields including education, healthcare and counseling, particularly with regard to female adolescents. The effective measurement of wellness in adolescents can assist researchers and practitioners in determining lifestyle behaviors in which they are lacking. Behavior change interventions can then be designed which directly aid in the promotion of these areas. Methods The 5-Factor Wellness Inventory (designed to measure the Indivisible Self model of wellness) is a popular instrument for measuring the broad aspects of wellness amongst adolescents. The instrument comprises 97 items contributing to 17 subscales, five dimension scores, four context scores, total wellness score, and a life satisfaction index. This investigation evaluated the test-retest (intra-rater) reliability of the 5 F-Wel instrument in repeated assessments (seven days apart) among adolescent females aged 12-14 years. Percentages of exact agreement for individual items, and the number of respondents who scored within +/-5, +/-7.5 and +/-10 points for total wellness and the five summary dimension scores were calculated. Results Overall, 46 (95.8%) participants responded with complete data and were included in the analysis. Item agreement ranged from 47.8% to 100% across the 97 items (median 69.9%, interquartile range 60.9%-73.9%). The percentage of respondents who scored within +/-5, +/-7.5 and +/-10 points for total wellness at the re-assessment was 87.0%, 97.8% and 97.8% respectively. The percentage of respondents who scored within +/-5, +/-7.5 and +/-10 for the domain scores at the reassessment ranged between 54.3-76.1%, 78.3-95.7% and 89.1-95.7% respectively across the five dimensions. Conclusions These findings suggest there was considerable variation in agreement between the two assessments on some individual items. However, the total wellness score and the five dimension summary scores remained comparatively stable between assessments.