International Journal of Supply and Operations Management
Volume:3 Issue: 1, Spring 2016

Institutional theory argues that the isomorphic nature of quality management (QM) practices leads to similar QM implementation and performance among QM-embedded firms. However, contingency theory questions such 'universal effectiveness of QM practices'. Considering these conflicting arguments, this study tests samples from the U.S. and China to examine whether the 'universal effectiveness of QM practices’ across national boundaries actually exists. First, the confirmatory factor analysis was performed to examine the validity of the survey instruments developed in this study. Then, the hypotheses were tested using the structural equation modeling (SEM) analysis. The SEM test results indicated that the positive effect of behavioral QM on firm performance was more significant in the U.S. sample than in the China sample. The test results also presented that the relative effect of behavioral QM versus technical QM on firm performance was noticeably different in service firms, according to national economic maturity. The study’s findings demonstrated that a firm's contingency factors, such as national economic maturity and industry type, could result in the heterogeneous implementation of the firm’s TQM program; consequently, the findings weakened the 'universal effectiveness of QM practices'.

Nowadays Business intelligence (BI) tools provide optimal decision making, analyzing, controlling and monitoring of operations in enterprise systems like enterprise resource planning (ERP) and mainly refer to strong decision making methods used in online analytical processing, reporting and data analysis, such as improve internal processes, analysis of resources, information needs analysis, reduce costs and increase revenue. The main purpose of paper is creating a unified framework for the application of BI in ERP systems which results of value-added inflexible manufacturing systems (FMS). In this paper, business process system and interaction between technology and environment byapplying BI in ERPsystems of companies that use flexible manufacturing systems have been presented. This paper is a comprehensive review of recent literature that examined the effects of BI systems on the fourlevels of Tenhialaet al.' Model (2015).This model based on cross-sectional data from 151 manufacturing plants proved that ERP is essential for the FMS. According to results of this paper, the answer to this question is important “How can we use the potential data, and intelligence of BI in ERP systems for the effective flexible manufacturing systems?” This study has four hypotheses to answer this question and based on results, all four hypotheses were confirmed. Finally, a model has been developed to determine the relationship between BI (as enabler of ERP) and FMS.

The Internet of Things and Services (IoTS) has encouraged the development of service provisioning systems in respect to Smart City topics. Most of them are operated as heterogeneous systems which limits end customers’ access and contradicts with IoTS principles. In this paper, we discuss and develop a reference model of an interconnected service marketplace ecosystem. The prototypical implementation incorporates findings from an empirical study and lessons learned from research projects. The elaborated ecosystem enables service request roaming between different parties across system boundaries. The paper presents a feasible centralized architecture, introduces involved parties and parts of a developed message protocol. Why a contracting mechanism is indispensable for request roaming is also outlined. The model’s feasibility is demonstrated by means of a current electric mobility use case: providing access to foreign charging infrastructure without multiple registrations. This work contributes to simplify the data exchange between service platforms to improve Smart City solutions and to support travelers with intelligent mobility applications.

In this paper, robust optimization of a bi-objective mathematical model in a dynamic cell formation problem considering labor utilization with uncertain data is carried out. The robust approach is used to reduce the effects of fluctuations of the uncertain parameters with regards to all the possible future scenarios. In this research, cost parameters of the cell formation and demand fluctuations are subject to uncertainty and a mixed-integer programming (MIP) model is developed to formulate the related robust dynamic cell formation problem. Then the problem is transformed into a bi-objective linear one. The first objective function seeks to minimize relevant costs of the problem including machine procurement and relocation costs, machine variable cost, inter-cell movement and intra-cell movement costs, overtime cost and labor shifting cost between cells, machine maintenance cost, inventory, holding part cost. The second objective function seeks to minimize total man-hour deviations between cells or indeed labor utilization of the modeled.

In the present study, the Economic Order Quantity (EOQ) model of two-warehouse deals with non-instantaneous deteriorating items, the demand rate considered as stock dependent and model affected by inflation under the pattern of time value of money over a finite planning horizon. Shortages are allowed and partially backordered depending on the waiting time for the next replenishment. The main objective of this work is to minimize the total inventory cost and finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented.

This study develops a inventory model to determine ordering policy for deteriorating items with shortages under markovian inflationary conditions. Markov processes include process whose future behavior cannot be accurately predicted from its past behavior (except the current or present behavior) and which involves random chance or probability. Behavior of business or economy, flow of traffic, progress of an epidemic, all are examples of Markov processes. Since the far previous inflation rate don’t have a great impact on the current inflation rate, so, It is logical to consider changes of the inflation rate as a markov process. In addition, It is assumed that the cost of the items changes as a Continuous – Time - Markov Process too. The inventory model is described by differential equations over the time horizon along with the present value method. The objective is minimization of the expected present value of costs over the time horizon. The numerical example and a sensitivity analysis are provided to analyze the effect of changes in the values of the different parameters on the optimal solution.

Scheduling problem for the hybrid flow shop scheduling problem (HFSP) followed by an assembly stage considering aging effects additional preventive and maintenance activities is studied in this paper. In this production system, a number of products of different kinds are produced. Each product is assembled with a set of several parts. The first stage is a hybrid flow shop to produce parts. All machines can process all kinds of parts in this stage but each machine can process only one part at the same time. The second stage is a single assembly machine or a single assembly team of workers. The aim is to schedule the parts on the machines and assembly sequence and also determine when the preventive maintenance activities get done in order to minimize the completion time of all products (makespan). A mathematical modeling is presented and its validation is shown by solving an example in small scale. Since this problem has been proved strongly NP-hard, in order to solve the problem in medium and large scale, four heuristic algorithms is proposed based on the Johnson’s algorithm. The numerical experiments are used to run the mathematical model and evaluate the performance of the proposed algorithms.