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This paper aims to explore methods of defining ejecting zones (EZs) used in automatic picking systems (APSs), particularly in A-frame APSs. An A-frame APS automatically ejects products onto a conveyor, which then brings the products to their destination. EZs are moving zones on a conveyor, and each EZ corresponds to one picking order. Products are ejected as a zone passes channels in which the products are stored.

First, three EZ types are defined, and their operations are explained. Second, picking orders are analyzed and categorized by considering the structure and the picking mechanism of an A-frame APS. In addition, picking-order instances reflecting actual data are randomly generated according to each category. Finally, the performance of the EZs is evaluated using the picking-order instances and computer simulations.

The results from the computer simulations suggest the EZ types suitable for use with various picking order types considering order fulfilment speed and energy usage.

In this paper, the authors only adopt a triangular distribution which is considered most practical distribution in the industry.

It is believed that these results can provide managers and operators with useful guides to facilitate the effective operation of an A-frame APS. The provided ideas have been implemented at the pharmaceutical warehouse of the largest logistics company in Korea.

The result shows that the proposed idea could save energy consumption and the APS have potential to save labor involvement in picking.

It is essential to define the EZs when operating an A-frame APS efficiently, but there is almost no research in this area. This paper focuses on defining EZs, as well as methods to utilize these zones.

The weapon system of The Navy is the small quantity producing system on multiple kinds. It is consisted of various equipment and the subordinate parts of those which can repair the damaged part. The operating procedure concerning warship's repair parts managed under these systems is as follows. Firstly, if demand of repair parts occurs from warship which is the operating unit of weapon, then the Fleet(the repair & supply support battalion) is in charge of dealing with these requests. If certain request from warship is beyond the battalion's capability, it is delivered directly to the Logistic Command. In short, the repair and supply support system of repair parts can be described as the multi-level support system. The various theoretical researches on inventory management of Navy's repair parts and simulation study that reflects reality in detail have been carried out simultaneously. However, the majority of existing research has been conducted on aircraft and tank's repairable items, in that, the studies is woefully deficient in the area concerning Navy's inventory management. For that reason, this paper firstly constructs the model of consumable items that is frequently damaged reflecting characteristics of navy's repair parts inventory management using ARENA simulation. After that, this paper is trying to propose methodology to analyze optimal inventory level of each supply unit through OptQuest, the optimization program of ARENA simulation.

Malicious attackers frequently breach information systems by exploiting disclosed software vulnerabilities. Knowledge of these vulnerabilities over time is essential to decide the use of software products by organisations. The purpose of this paper is to propose a novel G-RAM framework for business organisations to assess and mitigate risks arising out of software vulnerabilities.

The G-RAM risk assessment module uses GARCH to model vulnerability growth. Using 16-year data across 1999-2016 from the National Vulnerability Database, the authors estimate the model parameters and validate the prediction accuracy. Next, the G-RAM risk mitigation module designs optimal software portfolio using Markowitz’s mean-variance optimisation for a given IT budget and preference.

Based on an empirical analysis, this study establishes that vulnerability follows a non-linear, time-dependent, heteroskedastic growth pattern. Further, efficient software combinations are proposed that optimise correlated risk. The study also reports the empirical evidence of a shift in efficient frontier of software configurations with time.

Existing assumption of independent and identically distributed residuals after vulnerability function fitting is incorrect. This study applies GARCH technique to measure volatility clustering and mean reversal. The risk (or volatility) represented by the instantaneous variance is dependent on the immediately previous one, as well as on the unconditional variance of the entire vulnerability growth process.

The volatility-based estimation of vulnerability growth is a risk assessment mechanism. Next, the portfolio analysis acts as a risk mitigation activity. Results from this study can decide patch management cycle needed for each software – individual or group patching. G-RAM also ranks them into a 2×2 risk-return matrix to ensure that the correlated risk is diversified. Finally the paper helps the business firms to decide what to purchase and what to avoid.

Contrary to the existing techniques which either analyse with statistical distributions or linear econometric methods, this study establishes that vulnerability growth follows a non-linear, time-dependent, heteroskedastic pattern. The paper also links software risk assessment to IT governance and strategic business objectives. To the authors’ knowledge, this is the first study in IT security to examine and forecast volatility, and further design risk-optimal software portfolios.

Drawing from transactional stress and conservation of resource theories, this study untangles the relationship between power outage, patient incivility, job stress and proactive service performance. Further, this study also explores the mediating role of patient incivility and job stress.

A questionnaire-based survey was used, and data were collected from 275 healthcare professionals working in various public hospitals in Pakistan through convenience sampling. Structural equation modeling (SEM) via Smart PLS was used for data analysis.

Results revealed that power outage has significant positive impact on patient incivility and patient incivility has significant direct effect on job stress. Job stress has significant negative relationship with proactive service performance. Findings also confirmed that patient incivility mediates the relationship between power outage and job stress, and job stress mediates the relationship between patient incivility and proactive service performance.

This study helps the health administrators to think about the service standards of the public hospitals. Implications of this study are not limited to health sector. This study is useful for other service sectors where performance of employee affected by power outage. In addition to this, the current research helps to conduct research in other developing and underdeveloped countries which also face the problem of power outage.

This study marks the first step toward establishing power outage as an organizational behavior construct by demonstrating that power outage impacts significantly on proactive service performance. This study also explored the relationship between job stress and proactive service performance which was also not explored before.

The aim of this paper is to examine the role of perceived system quality (PSQ) as an antecedent to the implementation success (IMP) of ERP projects, and its interrelationships with other antecedents that influence the outcome of organizational adoption process.

The authors derive a model containing the relationships between PSQ and IMP and between PSQ and some antecedents of organizational adoption. The relationships were analysed with data from a survey of 217 Australian companies, using structural equation modelling.

PSQ is an important antecedent to implementation success of ERP projects. It also has a positive influence on other antecedents of organizational adoption, namely: perceived information quality, organizational readiness and perceived strategic value of adoption.

Prior findings have shown that PSQ is a significant antecedent to the adoption of ERP by individuals and organizations and the paper extends this by providing evidence that PSQ is also a significant antecedent to implementation success. The authors have empirically established the role of interrelationships among antecedent factors at the adoption stage of ERP systems.

Establishing a proposed ERP system's system quality, when considering whether to adopt a particular system is important, as it influences the other important antecedents and beliefs on the potential benefits from an ERP project. Understanding of system quality attributes can help managers put in place strategies to avoid potential pitfalls at the project implementation stage.

Empirical evidence of the importance of PSQ for success in ERP adoption, implementation and explanation of how and why this has positive effects on other antecedents.

Rotor performance analysis and design are complex due to the wide variation in flow characteristics. Design tools that can rapidly and accurately compute aerofoil data are needed for rotorcraft design and analysis purposes. The purpose of this paper is to describe a process which has been developed that effectively automates the generation of two‐dimensional (2D) aerofoil characteristics tables.

The process associates a number of commercial software packages and in‐house codes that employ diverse methodologies, including the Navier‐Stokes equation‐solving method, the high‐order panel method and Euler equations solved with the fully coupled viscous‐inviscid interaction (VII) method. The paper describes the development of a general automated generation method that extends from aerofoil shape generation to aerofoil characteristic analysis. The generated data are stored in C81 aerofoil characteristics tables for use in comprehensive rotorcraft analysis codes and rotor blade design. In addition, the methodology could be easily applied for fixed‐wing analysis and design, especially for transonic aircraft.

The method is demonstrated to achieve aerofoil characteristics quickly and accurately in automated process. Calculations for the SC1095 aerofoil section are presented and compared with existing experimental C81 data and previous studies.

The development of C81 tables is of interest to industry as they seek to update their airfoil tables as new designs. Automated processes to achieve this are helpful and applicable.

The paper presents an effective automated process to generate aerofoil characteristics tables quickly, and accurately.

Recent socio-economic trends have made Artificial intelligence (AI) a vital institutional force driving development among countries with optimal opportunities and costs. Among researchers in this domain, the benefit of AI is highly espoused, having been underexplored in Africa. However, the outbreak of the COVID-19 pandemic has highlighted the need to strengthen the education sector, given that many schools have migrated their teaching and learning online. While face-to-face teaching was the norm, the transition to online teaching has brought about the need to rethink the use of Information Technology to strengthen teaching and learning. To proffer solutions for the implementation of AI in Africa, there is the need to understand the challenges. Therefore, in this chapter, we explore the possible challenges that hinder the implementation of AI in Africa. Further, we propose solutions for the implementation of AI in the education sector, especially in this era of the COVID-19 pandemic. The solutions stem from rethinking the role of AI in the education sector. Finally, a conceptual framework that synthesises the problems and the proposed solution is developed. We envision that the proffered solutions can mitigate the deepening misconceptions and challenges bedevilling AI implementation in Africa.

In the disruptive technologies era, the lack of convincing business cases on blockchain (BC) adoption about food supply chain, the existence of uncertainties and barriers to adoption due to knowledge scarcity on characteristics as well as the potentialities and risks involved in it, have triggered the need to investigate the first multinational BC adoption for food supply chain in Europe, to consider how it can guarantee knowledge for the consumption/purchase decision-making and the creation-mechanism of consciousness for sustainable behavioral choice.

The authors provide a field exploratory analysis based on customers' perceptions and real knowledge about BC (as a knowledge-constructive tool) in the food and beverage sector. This connected with the need for an informed context, favoring sustainable conscious decision-making related to both the food chain and innovation acceptance. This analysis included the use of innovation acceptance as a corporate social responsibility (CSR) strategic orientation through a survey- and interview-based field analysis (80 respondents).

The findings of this study can be considered as antecedents of innovation acceptance in the sector. The analysis assesses consumers' scarce knowledge and perceptions on the BC system, the scarce usage level and the higher acquiring propensity for traceable foodstuffs generating bi-directional/dimensional value, considering that consumption habits could change through security and certainty antecedents and induced knowledge provided by external technological intervention.

By trying to match innovation and the knowledge-construction need as a vehicle for acceptance, the theoretical contribution would empower the literature on food traceability from the perspective of strategic BC application through a from-knowledge-to-knowledge strategy.