Journal Of Industrial Engineering International
Volume:15 Issue: 1, Winter 2019

The present study proposes a Customer Behavior Mining Framework on the basis of data mining techniques in a telecom company. This framework takes into account the customers’ behavior patterns and predicts the way they may act in the future. Firstly, clustering technique is used to implement portfolio analysis and previous customers are divided based on socio-demographic features using k-means algorithm. Then, the cluster analysis is conducted based on two criteria, i.e., the number of hours the telecom services used and the number of the services selected by customers of each group. Six groups of customers are identified in three levels of attractiveness according to the results of the customer portfolio analysis. The second phase has been devoted to mining the future behavior of the customers. Predicting the level of attractiveness of newcomer customers and also the churn behavior of these customers are accomplished in the second phase. This framework effectively helps the telecom managers mine the behavior of their customers. This may lead to develop appropriate tactics according to customers’ attractiveness and their churn behavior. Improving managers’ abilities in customer relationship management is one of the obtained results of the study.

Production costs in general, and workforce and inventory costs in particular, constitute a large fraction of the operating costs of many manufacturing plants. We introduce cooperative aggregate production planning as a way to decrease these costs. That is, when production planning of two or more facilities (plants) is integrated, they can interchange workforce and products inventory; thus, their product demands can be satisfied at lower cost. This paper quantifies the cost saving and synergy of different coalitions of production plants by a new linear model for cooperative aggregate planning problem. The developed approach is explicated with a numerical example in which inventory and workforce levels of different coalitions of facilities are evaluated. Afterward, a key question would be how the cost saving of a coalition should be divided among members. We tackle the problem using different methods of cooperative game theory. These methods are implemented in the numerical example to gain an insight into properties of the corresponding game results.

Drawing on the supply chain (SC) management literature, this article conceptualizes and empirically tests a framework that shows how both external and internal integration practices are significant and positively associated with SC value addition and firm performance. The framework also tests the impact of value addition as a reinforcing factor on firm performance. The outcome of this investigation is interesting for both SC researchers and practitioners because the current SC integration literature is conflicting. A structural equation modeling technique, using a sample of 366 large-scale manufacturing companies based in India, is considered in this paper to test the framework. The results support all five research hypotheses which indicate that paramount firm performance requires tight external and internal integration and higher level of value addition. Although the external integration is found to be rather influential than the internal integration, SC players need to have integrated internal business processes for tight external integration. This paper also explains the implication of collective planning and decision making to respond promptly to external market events and reveals the importance of value addition.

Humanitarian organizations pre-position relief items in pre-disaster and distribute them to the affected areas in post-disaster. Improper planning of emergency operations causes more deaths in post-disaster. In this paper, the problem of relief item pre-positioning and multi-period distribution planning is addressed considering lateral transhipment among distribution centres to improve the efficiency of the humanitarian relief chain. The proposed model not only improves cost efficiency of the relief chain, but also enhances the equity and fairness. Therefore, a multi-objective two-stage stochastic programming, which involves imprecise parameters, is developed to address the problem. Moreover, TH method is utilized to solve the proposed multi-objective programming and efficient possibilistic programming is adopted to deal with the imprecise input parameters. Applicability of the proposed model and the effectiveness of the solutions are examined through a numerical analysis. Finally, sensitivity analyses are conducted on key input parameters to extract managerial insights.

It is undeniable that SMEs face many management-related problems. These problems are often deeply rooted in the strategic decision making by managers. One of these decisions is associated with the production section. Many of these companies provide production infrastructure at high costs; however, they are unsuccessful in acquiring their market share. In these circumstances, providing a solution to the decision-making problem of managers in these companies can prevent the loss of capital. In this research, the system dynamics approach is used to test the hypothesis of a company’s participation in the production field after securing a success in business activities of the market. In the present study, the SME performance model, proposed by Schmid’s, is considered as the base model. After analyzing its construction steps according to managers’ viewpoints, the model has been developed based on the conditions in Iran. Then, the research scenario is presented as follows. If an entrepreneur, before entering the production sector, tries to establish a customer network by conducting business activities, the organization’s chance for success will increase. By defining a variable called “production switch” and adding it as a function of a loyal customer network, the model has been tested. After simulating the model for a 5-year period, it is concluded that the rate of return on investment of an organization that has conducted the commercial activities at the outset of production is four times higher than that at the outset of production without the commercial activity.

This paper deals with construction of confidence intervals for process capability index using bootstrap method (proposed by Chen and Pearn in Qual Reliab Eng Int 13(6):355–360, 1997) by applying simulation technique. It is assumed that the quality characteristic follows type-II generalized log-logistic distribution introduced by Rosaiah et al. in Int J Agric Stat Sci 4(2):283–292, (2008). Discussed different bootstrap confidence intervals for process capability index. Maximum likelihood method is considered for obtaining the estimators of the parameter. Monte Carlo simulation technique is applied to find out the coverage probabilities and average widths of the bootstrap confidence intervals. The results are illustrated with real data sets.

This paper presents an application of interactive fuzzy goal programming to the nonlinear multi-objective reliability optimization problem considering system reliability and cost of the system as objective functions. As the decision maker always have an intention to produce highly reliable system with minimum cost, therefore, we introduce the interactive method to design a high productivity system here. This method plays an important role to maximize the worst lower bound to obtain the preferred compromise solution which is close to the best upper bound of each objective functions. Until the preferred compromise solution is reached, new lower bounds corresponding to each objective functions will be determined based on the present solution to develop the updated membership functions as well as aspiration levels to resolve the proposed problem. Considering judgmental vagueness of decision maker, here we consider the resources as trapezoidal fuzzy numbers and apply total integral value of fuzzy number to transform into crisp one. To illustrate the methodology and performance of this approach, numerical examples are presented and evaluated by comparing with the other method at the end of this paper.

In the current competitive and dynamic market, customer demands and interests are changing continuously, and hence, risk of disruption in the supply chain is also increasing. To be successful in this scenario, supply chain of a firm should be resilient. Most of the firms realize that with a specific end goal to develop a resilient supply chain, there is a need for assessment of performance. The purpose of this paper is to discuss supply chain resilience and identify indicators which can help in increasing the performance and making a supply chain resilient. Articles published on this issue were collected and classified to draw out some meaningful information. After classification and analyses of the collected literature, seventeen performance indicators for supply chain resilience are found. A supply chain resilience framework is developed using these indicators to assist the supply chain managers to examine and withstand the disruption.