Forecast horizon aggregation in integer autoregressive moving average (INARMA) models

This paper addresses aggregation in integer autoregressive moving average (INARMA) models. Although aggregation in continuous-valued time series has been widely discussed, the same is not true for integer-valued time series. Forecast horizon aggregation is addressed in this paper. It is shown that the overlapping forecast horizon aggregation of an INARMA process results in an INARMA process. The conditional expected value of the aggregated process is also derived for use in forecasting. A simulation experiment is conducted to assess the accuracy of the forecasts produced by the aggregation method and to compare it to the accuracy of cumulative h-step ahead forecasts over the forecasting horizon. The results of an empirical analysis are also provided

Grocery omnichannel perishable inventories: performance measures and influencing factors

Purpose- Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures. Design/methodology/approach- The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation. Findings- Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects. Practical implications- To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products. Originality/value- This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors

Reproducibility in forecasting research

The importance of replication has been recognised across many scientific disciplines. Reproducibility is a necessary condition for replicability, because an inability to reproduce results implies that the methods have not been specified sufficiently, thus precluding replication. This paper describes how two independent teams of researchers attempted to reproduce the empirical findings of an important paper, ‘‘Shrinkage estimators of time series seasonal factors and their effect on forecasting accuracy’’ (Miller & Williams, 2003). The two teams proceeded systematically, reporting results both before and after receiving clarifications from the authors of the original study. The teams were able to approximately reproduce each other’s results, but not those of Miller and Williams. These discrepancies led to differences in the conclusions as to the conditions under which seasonal damping outperforms classical decomposition. The paper specifies the forecasting methods employed using a flowchart. It is argued that this approach to method documentation is complementary to the provision of computer code, as it is accessible to a broader audience of forecasting practitioners and researchers. The significance of this research lies not only in its lessons for seasonal forecasting but also, more generally, in its approach to the reproduction of forecasting research

Formation of seasonal groups and application of seasonal indices

Estimating seasonal variations in demand is a challenging task faced by many organisations. There may be many stock-keeping units (SKUs) to forecast, but often data histories are short, with very few complete seasonal cycles. It has been suggested in the literature that group seasonal indices (GSI) methods should be used to take advantage of information on similar SKUs. This paper addresses two research questions: (1) how should groups be formed in order to use the GSI methods? and (2) when should the GSI methods and the individual seasonal indices (ISI) method be used? Theoretical results are presented, showing that seasonal grouping and forecasting may be unified, based on a Mean Square Error criterion, and K-means clustering. A heuristic K-means method is presented, which is competitive with the Average Linkage method. It offers a viable alternative to a company’s own grouping method or may be used with confidence if a company lacks a grouping method. The paper gives empirical findings that confirm earlier theoretical results that greater accuracy may be obtained by employing a rule that assigns the GSI method to some SKUs and the ISI method to the remainder

Dengue viruses and promising envelope protein domain III-based vaccines

Abstract Dengue viruses are emerging mosquito-borne pathogens belonging to Flaviviridae family which are transmitted to humans via the bites of infected mosquitoes Aedes aegypti and Aedes albopictus. Because of the wide distribution of these mosquito vectors, more than 2.5 billion people are approximately at risk of dengue infection. Dengue viruses cause dengue fever and severe life-threatening illnesses as well as dengue hemorrhagic fever and dengue shock syndrome. All four serotypes of dengue virus can cause dengue diseases, but the manifestations are nearly different depending on type of the virus in consequent infections. Infection by any serotype creates life-long immunity against the corresponding serotype and temporary immunity to the others. This transient immunity declines after a while (6 months to 2 years) and is not protective against other serotypes, even may enhance the severity of a secondary heterotypic infection with a different serotype through a phenomenon known as antibody-depended enhancement (ADE). Although, it can be one of the possible explanations for more severe dengue diseases in individuals infected with a different serotype after primary infection. The envelope protein (E protein) of dengue virus is responsible for a wide range of biological activities, including binding to host cell receptors and fusion to and entry into host cells. The E protein, and especially its domain III (EDIII), stimulates host immunity responses by inducing protective and neutralizing antibodies. Therefore, the dengue E protein is an important antigen for vaccine development and diagnostic purposes. Here, we have provided a comprehensive review of dengue disease, vaccine design challenges, and various approaches in dengue vaccine development with emphasizing on newly developed envelope domain III-based dengue vaccine candidates. Keywords: Dengue virus Envelope protein Chimeric vaccine Disease Immunogenicit

Effects of nanoencapsulated formulation of Cuminum cyminum essential oil on Panonychus citri (Acari: Tetranychidae)

Citrus red mite, Panonychus citri McGregor is one of the most important pests of citrus orchards in the world. Due to excessive use of chemical pesticides and development of resistance plus their increasing environmental hazards, the use of essential oils has been highly studied. But the low solubility of essential oils in water, oxidation, in addition to their instability in presence of light, humidity and high temperature has diminished their application. Formulation technology is one of the main strategies that can modify the physical properties and the viability of the essential oils in agricultural pest management programs. In this research, the essential oil of Cuminum cyminum L. was encapsulated by in situ polymerization of oil/water emulsion in nano scale and then the effects of nanoencapsulated essential oil (NEO) were analyzed against P. citri. The results showed that LC50 of NEO's contact toxicity was 743.17 ppm over 24 hours. NEO also affected mortality and decreased oviposition rate in P. citri. NEO had deterrence capacity at 300, 500 and 700 ppm. Moreover, NOE had oviposition deterrence, lowering the number of eggs per female compared to the control. Our finding suggests that high-tech formulations including nanoencapsulation technology can be used as botanical pesticides and as alternatives to chemical pesticides