Attitudes of social work students towards older people

Demographic ageing is a challenge for many countries. Even though Turkey has a relatively younger demographic composition, the proportion of the older people (65+) within the population is rapidly increasing. Within this framework, older people are becoming more important clients for both social work students and social workers in Turkey. This study aims to reveal the attitudes of social work students towards older people and determine the various factors that affect their views on older persons. In the scope of the project, Kogan's Attitude Towards Old People Scale was applied to 419 social work undergraduate students at a university located in Central Anatolia. The findings showed that social work students scored a mean of 130.96 and they generally had positive attitudes towards older people. The correlation between year of study, gender and age was not statistically significant. However, having lived mostly in urban areas was positively correlated with the mean Kogan scores and this finding was found to be statistically significant. Exposure to personal contact with older people at both the personal and professional levels was influential in shaping attitudes about the older people.     

Can Trade Help Poor People? The Role of Trade,Trade Policy and Market Access in Tanzania

Many development economists prescribe trade as a poverty‐reducing formula. But how is this elixir supposed to work? This article contributes to the lively debate on this topic with household evidence from Tanzania — a poor country even within sub‐Saharan Africa, the poorest region. About 81% of the poor work in agriculture, which accounts for 88% of the export bundle. The article describes existing poverty and then evaluates the poverty‐reduction potential of trade, trade policy and market access. The article extends the analysis by simulating tariff changes and four switching scenarios that swap some poor households into trade‐related sectors, such as cash cropping or tourism, to project national poverty reductions of up to 5.6% and household income increases of up to 21.5%.     

Supplier Selection for Framework Agreements in Humanitarian Relief

In this study, we consider the supplier selection problem of a relief organization that wants to establish framework agreements (FAs) with a number of suppliers to ensure quick and cost‐effective procurement of relief supplies in responding to sudden‐onset disasters. Motivated by the FAs in relief practice, we focus on a quantity flexibility contract in which the relief organization commits to purchase a minimum total quantity from each framework supplier over a fixed agreement horizon, and, in return, the suppliers reserve capacity for the organization and promise to deliver items according to pre‐specified agreement terms. Due to the uncertainties in demand locations and amounts, it may be challenging for relief organizations to assess candidate suppliers and the offered agreement terms. We use a scenario‐based approach to represent demand uncertainty and develop a stochastic programming model that selects framework suppliers to minimize expected procurement and agreement costs while meeting service requirements. We perform numerical experiments to understand the implications of agreement terms in different settings. The results show that supplier selection decisions and costs are generally more sensitive to the changes in agreement terms in settings with high‐impact disasters. Finally, we illustrate the applicability of our model on a case study.     

The effect of Phase I sample size on the run length performance of control charts for autocorrelated data

Traditional control charts assume independence of observations obtained from the monitored process. However, if the observations are autocorrelated, these charts often do not perform as intended by the design requirements. Recently, several control charts have been proposed to deal with autocorrelated observations. The residual chart, modified Shewhart chart, EWMAST chart, and ARMA chart are such charts widely used for monitoring the occurrence of assignable causes in a process when the process exhibits inherent autocorrelation. Besides autocorrelation, one other issue is the unknown values of true process parameters to be used in the control chart design, which are often estimated from a reference sample of in-control observations. Performances of the above-mentioned control charts for autocorrelated processes are significantly affected by the sample size used in a Phase I study to estimate the control chart parameters. In this study, we investigate the effect of Phase I sample size on the run length performance of these four charts for monitoring the changes in the mean of an autocorrelated process, namely an AR(1) process. A discussion of the practical implications of the results and suggestions on the sample size requirements for effective process monitoring are provided.     

Interactions in new product development: How the nature of the NPD process influences interaction between teams and management

Effective interaction across organisational boundaries is a critical success factor in new product development (NPD). However, few studies have investigated how different mechanisms enable effective interaction across organisational and particularly hierarchical boundaries.This study explores how the formality of the NPD process influences the nature of interactions across different organisational boundaries and specifically identifies interaction mechanisms used across hierarchical boundaries. Cross-sectional interviews were conducted in nine firms. Findings highlight that in firms with a formalised NPD process, interactions tend to have a transactional/managerial bias. In contrast, in firms where the NPD process is flexible, interactions have a more social objective.     

Dual Sourcing Under Random Supply Capacities: The Role of the Slow Supplier

Sourcing from multiple suppliers with different characteristics is common in practice for various reasons. This paper studies a dynamic procurement planning problem in which the firm can replenish inventory from a fast and a slow supplier, both with uncertain capacities. The optimal policy is characterized by two reorder points, one for each supplier. Whenever the pre‐order inventory level is below the reorder point, a replenishment order is issued to the corresponding supplier. Interestingly, the reorder point for the slow supplier can be higher than that of the fast even if the former has a higher cost, lower reliability, and smaller capacity than the latter, suggesting the possibility of ordering exclusively from an inferior slow supplier in the short term. Moreover, the firm may allocate a larger portion of the long‐term total order quantity to the slow supplier than to the fast, even if the former does not possess any cost or reliability advantage over the latter. Such phenomena, different from the observations made in previous studies, happen when the demand is uncertain and the supply is limited or unreliable. Our observations highlight the importance of incorporating both demand uncertainty and supplier characteristics (i.e., cost, lead time, capacity and uncertainty) in a unified framework when formulating supplier selection and order allocation strategies.     

Scheduling Methods for Efficient Stamping Operations at an Automotive Company

We consider scheduling issues at Beyçelik, a Turkish automotive stamping company that uses presses to give shape to metal sheets in order to produce auto parts. The problem concerns the minimization of the total completion time of job orders (i.e., makespan) during a planning horizon. This problem may be classified as a combined generalized flowshop and flexible flowshop problem with special characteristics. We show that the Stamping Scheduling Problem is NP‐Hard. We develop an integer programming‐based method to build realistic and usable schedules. Our results show that the proposed method is able to find higher quality schedules (i.e., shorter makespan values) than both the company's current process and a model from the literature. However, the proposed method has a relatively long run time, which is not practical for the company in situations when a (new) schedule is needed quickly (e.g., when there is a machine breakdown or a rush order). To improve the solution time, we develop a second method that is inspired by decomposition. We show that the second method provides higher‐quality solutions—and in most cases optimal solutions—in a shorter time. We compare the performance of all three methods with the company's schedules. The second method finds a solution in minutes compared to Beyçelik's current process, which takes 28 hours. Further, the makespan values of the second method are about 6.1% shorter than the company's schedules. We estimate that the company can save over €187,000 annually by using the second method. We believe that the models and methods developed in this study can be used in similar companies and industries.     

On the Mean Remaining Strength of the k-Out-of-n:F System with Exchangeable Components

In this article, we consider the mean remaining strength of a k-out-of-n:F system in the stress–strength setup for the exchangeable components. We provide some results for parallel and series systems under this setup, where X₁, X₂, …, X_n are the strengths of the components designed under the common stress. An illustrative example is given for the k-out-of- n:F system using the multivariate FGM distribution.