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The main problem addressed by this research is the current debate between the negative and positive effects of industrial clusters. This debate is a result of gaps between theoretical implications and empirical evidence in both the classical agglomeration theory and the agglomeration lifecycle theory. The purpose of this study is to propose a framework for developing an index measuring both organizational cluster involvement and organizational supply chain including the three pillars (economic, social, and environmental). Furthermore, the index acts as a quantitative predictor of the stages of the life cycle of industrial clusters. Adopting a case study methodology, the applicability of the index development framework is demonstrated. First, cross-sectional exploratory interviews are performed to locate items measuring the three pillars of organizational sustainability within Egyptian communication industry. Second, an explanatory, cross-sectional approach is applied gathering data from eight professionals related to involvement and supply chain sustainability of their organizations. Analytical hierarchical process is used for weighting and aggregating individual item metrics into two indicators (Saaty, 1980). Measuring, managing, and controlling capabilities of organization's supply chains outweighs the need to manage risks. The proposed framework aids firms within a cluster in making timely decisions about what needs addressing to improve supply chain sustainability performance. Hence, all environmental, social, and economic capabilities can be effectively monitored and controlled.

While cost allocation decisions attract considerable attention in the management accounting literature, many studies are contradicting and inconclusive. They often seek to develop product or service weights in order to make operating decisions with the sole objective of maximizing the firm’s profitability. But before developing these weights, the studies must first rank these products – which is a complex endeavor that is often driven by many hierarchical financial and nonfinancial goals and objectives. Ranking is also difficult due to using such complex concepts as time, uncertainty, cost, and interdependencies between accounting systems and manufacturing systems and among the products of the product mix. These concepts are inherently fuzzy and coextensively applied often with a confluence of variables operating simultaneously.

This paper applies an advanced mathematical model to account for a hospital cost allocation decisions in treating spinal cord injuries (SCI). The model combines the powers of fuzzy set theory (Zadeh, 1965) and the analytic hierarchy process (Saaty, 1978). The precise ratings required in the conventional analytic hierarchy process but practically hard to obtain are replaced by naturally semantic variables by using the fuzzy set concept. de Korvin and Kleyle’s (1999) fuzzy-analytic-hierarchical process (FAHP) then develop these ambiguous variables. FAHP can help to optimize decisions involving ambiguous variables and the web of prioritized strategies and goals of cost leadership, product differentiation, financial objectives of earnings, cash flows, and market share and nonfinancial goals such as tradition and owners’ convictions and philosophies.

We use data from seven Michigan SCI facilities in applying the FAHP model to rank and otherwise develop more optimal strategies and goals and compare our results to the decisions of hospital management.

An issue that is becoming yet more relevant to modern manufacturers is that of flexibility. As life cycles become shorter a manufacturing firm can easily be left with redundant stock and dated processes. In Taiwan this issue has been addressed at several levels, this case study describes one such project. A Taiwanese academic conducted a study, gaining business acceptance of a hierarchical set of theoretical flexibility factors, then rearranging these via pictorial representations of fuzzy logic-derived plane surfaces, and finally re-presenting them to business as a set of ordered propositions designed to identify the key factors contributing to flexibility. The learning points relate, first, to the empirical facts uncovered about the specific factors that have a major bearing on manufacturing flexibility. These factors are, of course, specific to Taiwan and the current environment there. Second, though, is the more enduring illustration of a mixed-method case approach; where interviews, fuzzy logic analytical methods, and pictorial representation of the fuzzy logic output all combine to give clear guidance to managers of an industrial sector under stress, and to the policy makers who exert significant control over their environment.

With the advent of technology and science, the business environment will keep changing very fast. Today, Information Technology (IT) is used in almost all business applications. The most important improvements are being realized at the management side since IT is fully supporting decision-making processes now. Human Resources Management (HRM) is being affected by IT such as web-based technologies and intelligent systems and these systems make HRM much more effective. Today’s HRM-related software do not deal with just payrolls, they also include recruiting and record-keeping, training and performance appraisal which have transitioned HRM from task-oriented to people-oriented. Today, Human Resources Information Systems (HRIS) and electronic HRM (e-HRM) are being utilized by many organizations all over the world and play a strategic role in decision-making processes for effective and efficient HRM. This study investigates the recent literature on HRIS, e-HRM and Decision Support Systems in HRM to identify the improvements and debates on contemporary Human Resources Management.

Demand for goods/services has increased in Latin America due to urbanization, leading to a complex delivery system and increased logistical activities. In Quito, the Historic Center and La Mariscal are two zones that face logistical challenges. The objective of this chapter is to analyze the commercial logistic activities related to loading and unloading goods in these zones. To address this urban freight problem, this chapter proposes a solution through the calculation of the optimal number and location of loading and unloading bays in each zone based on actual commercial activity data. First, a delivery survey was completed in each zone regarding frequency and amount of deliveries. Then, based on the data obtained, an optimization model is proposed to determine the optimal number and location of loading and unloading bays. Finally, a simulation model of the delivery process is performed to readjust the bay’s optimal number. A total number of 75 and 98 bays were calculated to serve the total shopping district of a representative square kilometer (km²) of the Historic Center and La Mariscal. This solution aims to minimize the delivery time and the distance for deliveries, improve urban freight transportation, and reduce traffic. This study could be used as a baseline and guide for further research in urban logistics, especially in Latin America, where urban logistics is still under study. This chapter is part of a Research Project of Urban Logistics in Quito, led by Universidad San Francisco de Quito (USFQ), in association with the Megacity Logistics Lab of MIT.