Bersam Bolat

A multiattribute ABC classification model using fuzzy AHP

ABC analysis is one of the most widely used techniques in organizations to classify inventory items. This classification is based on the Pareto principle. The main limitation of the Pareto principle comes from its one dimensional analysis. To overcome this limitation, an ABC analysis based on a multiattribute classification can be used. Many attributes are hard to define precisely in this analysis. The fuzzy set theory can overcome this problem by incorporating imprecision and subjectivity into a multiattribute ABC classification model. In this paper, Zengs fuzzy analytic hierarchy process is used for classifying inventory items by taking care of conflicting attributes like demand, unit cost, substitutability, payment terms, and lead time. A real case study in a Turkish firm distributing fast moving consumer goods is realized. The obtained results show that this multiattribute fuzzy methodology can be effectively used in classifying inventory items.

A fuzzy integrated approach for project selection

Purpose – The purpose of this paper is to develop a systematic and comprehensive project selection model utilizing fuzzy multi-objective linear programming (FMOLP) that deals with the imprecise data in IS projects and uncertain judgment of decision makers. Design/methodology/approach – First, projects are prioritized by considering both quantitative and qualitative factors. A fuzzy analytical hierarchical process (FAHP) is used in order to obtain weights of each project that indicates their priorities. At the second step, project selection decision is completed by using FMOLP. Then, the sensitivity analysis is performed to evaluate the robustness of the proposed integrated model. Findings – The result of this study indicates that an integrated approach utilizing FAHP and FMOLP can be used as a supportive tool for project selection in IS context. It decreases the uncertainty caused from uncertain judgment of decision makers. Research limitations/implications – Future studies are suggested to design models ...

A fuzzy expert system design for forecasting return quantity in reverse logistics network

Purpose – The purpose of this study is to develop a fuzzy expert system to design robust forecast of return quantity in order to handle uncertainties from the return process in reverse logistic network. Design/methodology/approach – The most important factors which have impact on return of products are defined. Then the factors which have collinearity with others are eliminated by using dimension redundancy analysis. By training data of selected factors with fuzzy expert system, the return amounts of alternative cities are forecasted. Findings – The performance metrics of the proposed model are found as satisfactory. That means the result of this study indicates that fuzzy expert systems can be used as a supportive tool for forecasting return quantity of alternative areas. Research limitations/implications – In the future, the proposed model can be used for forecasting other uncertain parameters such as return quality and return time. Other fuzzy systems such as type-2 fuzzy sets can be used, or other exp...

Light rail passenger demand forecasting by artificial neural networks

The success of strategic and detailed planning of public transportation highly depends on accurate demand information data. Short-term forecasting is the key to the success of transportation operations planning such as time-tabling and seat allocation. This study adopts neural networks to develop short-term passenger demand forecasting models to be used in operational management of light rail services. A multi-layer perceptron (MLP) model is preferred due to not only its simple architecture but also proven success of solving approximation problems. For eliminating the significant seasonality in time slots, each time slot is handled independent of the others, and an artificial neural network based on daily data is developed for each. Regarding to the 74 different time slots, 74 different neural networks are trained by history data. Three illustrative examples are demonstrated on one of the time slots and performance of the forecast models are evaluated based on mean square errors (MSE) and mean absolute percentage errors (MAPE).

Evaluating efforts to build sustainable WEEE reverse logistics network design: comparison of regulatory and non-regulatory approaches

Abstract Many developing countries such as Turkey are still making an effort on building an infrastructure for waste of electrical and electronic equipment (WEEE) reverse logistic network design (RLND) processes. It is obvious that policies/laws/regulations related to WEEE management provide a sustainable framework for implementation in the RLND. The question is here: Does the implementation of WEEE directives make sense in terms of reducing the total cost of the network in the long term? This study aims to compare regulatory and non-regulatory situations of WEEE RLND in developing countries by formulating two models named as ‘regulatory’ and ‘non-regulatory’. Model 1 is considered as sustainable with economic, environmental and social goals, and the quotas imposed by the environmental directive are taken into consideration as the data of product return amount. In Model 2, only economic goal is considered, and product return amount is forecasted using Artificial Neural Network (ANN). A case study is conducted in a recycling company in order to evaluate performance of the proposed models. This study contributes to the relevant literature by (1) comparing the regulatory and non-regulatory situations RL models explicitly and (2) proposing ANN model to forecast EEE product return or WEEE quantity for non-regulatory situation.

A comparative study for differences on Information System success perceptions: a study of retailing industry

In today’s business environment, the implementation process of Information System (IS) has deep effect on supply chain position o f an organisation. IS projects have multi-dimensional impacts, and they are evaluated regarding implementation success criteria that managers want to achieve. This paper aims to investigate the distinguishing impact of different functional categories on managers’ perceptions on IS Project Implementation Success criteria by comparing two classification models. Within the scope of this study, related literature was examined and then a questionnaire survey was conducted to managers in an organisation from retailing sector to reveal out the importance of the success criteria. Artificial Neural Network (ANN) and Multiple Discriminant Analysis (MDA) have been utilised to seek the effects of different functional department perceptions.

A proposed conceptual framework for building supply chain strategies to meet marketplace requirements

Over last two decades, a new approach has emerged: competitive advantage lies through the supply chain (SC). Especially unique set of relations between organisations in a supply network enables the achievement of competitive advantage through lower costs, greater differentiation and focus on niche segments. The success and failure of SCs are ultimately determined in the marketplace by the end consumer. Delivering the right product, at the right time, at the right price to the consumer is vital not only to achieve competitive success but also to survive in todays marketplace. Hence, understanding of marketplace requirements and customer satisfaction are crucial elements to consider for devising and revising the right SC strategy. Any competitive advantage arises from both the choice of SC activities and how they are performed. In this paper, a conceptual framework which is linking competitive capabilities to SC management (SCM) strategies through the aspects of demand and SC is provided. The idea behind such a framework is to give managers a guide while devising their SC strategies according to customer needs. It is aimed to detail the specific SC tools and techniques, as well as decisions which are required to service each SC process distinguished according to customer needs. A conceptual framework is built for SCs in order to meet marketplace requirements in alignment with business strategies.

A Bayesian Network Analysis for Occupational Accidents of Mining Sector

The mining sector is one of the most important raw material sources and wealth sources for countries. On the other hand, many work accidents occur during its activities due to the adverse working conditions. Research is being conducted to reduce the security risk factor, which is one of the most critical obstacles to the social sustainability of the mining industry. In this study, under-recorded mine accidents and injuries are handled, rather than the accidents of the roof falling and the explosions which are frequently considered in the literature. In this scope of the study, accidents and incidents that occur during the specified processes (support, face, loading and transportation activities) of an underground chrome mine are investigated. Expert judgments have been used since no past accidents are allowing statistical inferences. BN has been used to find out the issues about the safety risk by addressing the causal relationships between the events. OHS education, OHS inspection, employee attention and, rock and ground structure of the working area have been deduced as the root causes of the accidents which occur mostly during the labor-intensive processes. By using the updating ability of the BN, comprehensive sensitivity analysis has been performed with the new information related to root causes. According to different scenarios associated with the various states of the root causes, the results and the future suggestions are presented.

DIFFERENCES IN MANAGER ASSESSMENTS OF ISO 14000 STANDARD IMPLEMENTATION IN TURKEY

This study reports the results of a survey about the improvements achieved as result of ISO 14000 Environmental Management System (EMS) standard implementation and the differences of improvements with respect to firm characteristics. A survey has been conducted in order to explain the improvements related to environmental management process and overall firm performance. The survey involved sixty-six enterprises implementing ISO 14000 EMS standard in Turkey. In order to assess improvements obtained from ISO 14000 EMS implementation, statements related to environmental management process and overall firm performance indicators have been prepared. The statements in this study are relevant to previous research. A factor analysis was employed to determine the factors of the variables explaining improvements. Nine factors have been identified related to achieved improvements, such as establishment of pro-active environmental management system, effectiveness in resource utilization, effectiveness of process control, relationships with industry and government, meeting expectations of stakeholders, demonstration of social responsibility, profitability, productivity, and competitiveness. Then, a T- test was conducted to determine the differences of managers’ assessments with respect to certain firm characteristics. The findings have shown that there are differences in the assessments of improvements achieved as a result of ISO 14000 EMS standard implementation with respect to sales volume, foreign-capital possession, and ISO 14000 EMS standard implementation. On the other hand, industrial sector, age of establishment, and export orientation are not statistically significant for the differences in the assessments of improvements.