This paper provides a review on recent works in the field of competitive facility location models based on the following seven components: 1) Variables, 2) Competition type, 3) Solution space, 4) Customer behavior, 5) Demand type, 6) Number of new facilities and 7) Relocation and redesign possibility. First, the components are introduced and then based on these components; different studies are compared with each other via a proposed taxonomy and finally a review on work of each paper is provided.
In this article, a manpower allocation and cell loading problem is studied, where demand is sto-chastic. The inter-cell and intra-cell movements are considered and attention is focused on as-signing operators with different skill levels to operations, because cell performance in addition to load cell is dependent on manpower. The purpose of this article is manpower allocation in cellu-lar manufacturing with consideration to learning and training policies. The manpower skill levels are determined in order to enhance production rate. The main contribution of this approach is the scenarios of training and learning in addition to the combination of training and learning being simulated. By using these three scenarios, the skill level of workers increase which reduces the processing time. In this regard cell layout is static where processing times and customer demand follow a normal distribution. As one of the significant costs of industrial unit is related to pro-duction cost, this study has attempted to reduce these costs by increasing the skill level of opera-tor which causes to reduce the processing time. Scenarios are evaluated by using a simulation method that finally attained results indicate this simulation provides better manpower assign-ments.
A simple yet powerful optimization algorithm is proposed in this paper for solving the constrained and unconstrained optimization problems. This algorithm is based on the concept that the solution obtained for a given problem should move towards the best solution and should avoid the worst solution. This algorithm requires only the common control parameters and does not require any algorithm-specific control parameters. The performance of the proposed algorithm is investigated by implementing it on 24 constrained benchmark functions having different characteristics given in Congress on Evolutionary Computation (CEC 2006) and the performance is compared with that of other well-known optimization algorithms. The results have proved the better effectiveness of the proposed algorithm. Furthermore, the statistical analysis of the experimental work has been carried out by conducting the Friedman’s rank test and Holm-Sidak test. The proposed algorithm is found to secure first rank for the ‘best’ and ‘mean’ solutions in the Friedman’s rank test for all the 24 constrained benchmark problems. In addition to solving the constrained benchmark problems, the algorithm is also investigated on 30 unconstrained benchmark problems taken from the literature and the performance of the algorithm is found better.
Engaging customer is the burning issue for companies especially the service sector, either online or offline. Minimizing the customer disengagement is the same like reducing dissatisfaction or churn. Customer disengagement may be caused by many factors, ad skepticism is one of them; ad skepticism has two main antecedents personality variable and consumption/influencing varia-bles. This research explores the relationship of ad skepticism with customer disengagement through personality variables which are cynicism, reactance and self-esteem. The unit of analysis is the telecom and banking industry of Pakistan which is foreseeing an era of virtual currency and both are customer oriented industries. Only offline disengagement is researched and data is collected from the Business centers of telecom and banking branches dealing with virtual curren-cy in Pakistan. Hypothetical model is given after digging the relevant literature; model is tested through confirmatory factor analysis and structural equation modeling. Eight hypotheses were purposed from the connections of model, all hypotheses are accepted except the cynicism posi-tive effect on social ad skepticism. This can be due to commonality of social and charity in Paki-stani society, Muslims consider charity as a pious act and they do not think for cynic behavior in charity or social related works. The results manifest that customers in telecom industry are hav-ing ad skepticism and that is becoming the cause of their disengagement. Further, social ad skep-ticism has more impact on the customer disengagement than the general ad skepticism. While the reactance has more effect on general ad skepticism than other antecedents and cynicism has the lowest impact on social ad skepticism than other antecedents.
In a Pay What You Want (PWYW) setting companies empower their customers to fix the prices buyers voluntarily pay for a delivered product or service. The seller agrees to any price (includ-ing zero) customers are paying. For about ten years researchers empirically investigate customer reactions to and economic outcomes of this pricing method. The present paper distinguishes PWYW from other voluntary payment mechanisms and reviews 72 English- or German-speaking PWYW publications, which appeared between January 2006 and September 2016 and contain 97 independent empirical data sets. Prior PWYW research is structured with the help of a conceptual framework which incorporates payment procedure design, buyer, seller, focal sales object and market context characteristics as factors potentially influencing customer perceptions of the PWYW scheme and their behavioral reactions to PWYW offers. The review discusses both consistent key findings as well as contradictory results and derives recommendations for future empirical PWYW research efforts.
This paper presents a multiobjective ant colony algorithm for the Multi-Depot Vehicle Routing Problem with Backhauls (MDVRPB) where three objectives of traveled distance, traveling times and total consumption of energy are minimized. An ant colony algorithm is proposed to solve the MDVRPB. The solution scheme allows one to find a set of ordered solutions in Pareto fronts by considering the concept of dominance. The effectiveness of the proposed approach is examined by considering a set of instances adapted from the literature. The computational results show high quality results within short computing times.
Successful flow-shop scheduling outlines a more rapid and efficient process of order fulfilment in warehouse activities. Indeed the way and the speed of order processing and, in particular, the operations concerning materials handling between the upper stocking area and a lower forward picking one must be optimized. The two activities, drops and pickings, have considerable impact on important performance parameters for Supply Chain wholesaler companies. In this paper, a new flow shop scheduling algorithm is formulated in order to process a greater number of orders by replacing the FIFO logic for the drops activities of a wholesaler company on a daily basis. The System Dynamics modelling and simulation have been used to simulate the actual scenario and the output solutions. Finally, a t-Student test validates the modelled algorithm, granting that it can be used for all wholesalers based on drop and picking activities.
This study aims to investigate the technology acceptance and purchase intention for Third Generation (3G) technology in Pakistan’s telecom sector. In such respect, Technology Acceptance Model (TAM) has been used to find the effects of the independent variables (Perceived Usefulness, Perceived Ease of Use, Perceived Value, Perceived Enjoyment, Personal Innovativeness and Price) on dependent variable (purchase intention). The study population consisted of smartphone users among Millennials in district Haripur-a region in transition towards urbanization. 200 respondents provided the useable data. The results of the study show that perceived usefulness, perceived ease of use, perceived value, perceived enjoyment, personal innovativeness, and price have a significant and positive relationship with purchase intention which validates the growing acceptance of advanced technologies in such regions.
In most of the published articles dealing with optimal order quantity model under permissible delay in payments, it is assumed that the supplier only put forwards fully permissible delay in payments if retailer ordered a bulky sufficient quantity otherwise permissible delay in payments would not be permitted. Practically, in competitive market environments and recession phases of business, every supplier wants to attract more retailers by the help of providing good facilities for trading. Necessity of order quantity may put a negative pressure on supplier’s demand. So, within the economic order quantity (EOQ) framework the main purpose of this paper is to broaden this extreme case by introducing a new credit policy, Flexible Trade Credit Policy (FTCP), for supplier which can help him provide more free space of trading to retailers. This policy, after adopting by suppliers, not only provides attractive trading environments for retailers but also enhances the demand of supplier due to the large number of new retailers. Here in, under this policy, an inventory system is investigated as a cost minimization problem to establish the retailer’s optimal inventory cycle time and optimal order quantity. Three theorems are established to describe and to lighten optimal replenishment policies for the retailer. Finally, numerical examples are considered to illustrate all these theorems and managerial insights are given based on considered numerical examples.
Cell load variation is considered a significant shortcoming in scheduling of cellular manufacturing systems. In this article, a new method is proposed for scheduling dynamic cellular manufacturing systems in the presence of bottleneck and parallel machines. The aim of this method is to control cell load variation during the process of determining the best trading off values between in-house manufacturing and outsourcing. A genetic algorithm (GA) is developed because of the high potential of trapping in the local optima, and results are compared with the results of LINGO® 12.0 software. The Taguchi method (an L_9 orthogonal optimization) is used to estimate parameters of GA in order to solve experiments derived from literature. An in-depth analysis is conducted on the results in consideration of various factors, and control charts are used on machine-load variation. Our findings indicate that the dynamic condition of product demands affects the routing of product parts and may induce machine-load variations that yield to cell-load diversity. An increase in product uncertainty level causes the loading level of each cell to vary, which in turn results in the development of “complex dummy sub-cells”. The effect of the complex sub-cells is measured using another mathematical index. The results showed that the proposed GA can provide solutions with limited cell-load variations.