Purpose: The purpose of this paper is to contribute to the existing knowledge about the relationships between advanced manufacturing technology (AMT), lean manufacturing (LM), agile manufacturing (AM), and business performance.Design/methodology/approach: A questionnaire-based survey was performed to collect data from 189 Iranian automobile part manufacturers. Statistical analysis of hypothesized relationships was conducted via partial least squares structural equation modeling.Findings: AMT significantly contributes to the development of both LM and AM. These manufacturing systems can co-exist in one system, and LM is a precursor to AM. LM contributes to operational performance whereas AM improves marketing performance and financial performance.Research limitations/implications: Relying on the cross-sectional data of this research, and lack of generalizability of findings are key limitations. An interesting direction for future research would be to empirically offer a hybrid lean-agile approach and further map the mechanism through which this hybrid approach can be achieved in practice.Practical implications: Both LM and AM are information-intensive and highly supported by AMT. They contribute to different aspects of business performance. Pursuing both cost-leadership strategy and product mix flexibility is viable via hybridizing the lean and agile systems.Originality/value: This study is among the first to address issues related to the lean-AM relationship among developing countries. This study is unique in the sense it shows the mechanism through which the value of AMT is truly transformed to performance improvement.

One way to develop local clusters is to strengthen those clusters by using outsourcing to conduct strategic social responsibility, or in other words, to create shared value, which is a win-win strategy for the buyer, supplier, and society and the best and most viable alternative to traditional corporate social responsibilities. In the leading research, a model for decision-making within the supply chain has been developed for purchasing based on shared value creation, long-term relationship management, and purchasing strategies. The research consists of two strategic mathematical models, using goal programming, and then is solved by a meta-heuristic algorithm. Potential outsourcing companies are assessed and then clustered according to their geographic locations in the decision-making process. One (or several) cluster(s) was selected among clusters based on knowledge and relationship criteria. Besides, in the primary mathematical model, the orders in different periods and the selection of suppliers are determined. In this model, in addition to optimizing the cost, the dispersion of purchases from suppliers is maximized to increase relationships and strengthen all members of the cluster. Maximizing the distribution by converting a secondary objective function to goal-programming variables transforms the multi-objective model into a single-objective model. In addition to economic benefits for buyers and suppliers, this purchasing plan concentrates on strengthening the local industrial cluster, fostering employment and ease of recruitment for human resources, accessing more infrastructures and technical support facilities, developing an education system in the region, and assisting knowledge-based enterprises with development.

In this article, we study the impact of teamwork on an organization’s performance, considering a cooperative game’s framework. To promote teamwork culture, performance indexes were considered both individually and collectively, and by comparing the scores that every employee earned individually and collectively, their differences became obvious. In this approach, a cooperative game’s model was used in order to improve the organization’s performance. The proposed model, in addition to evaluating the organization and employee’s activities, implemented all payments, including overtime pay, rewards, etc., fairly and along with increasing performance and satisfaction. The cooperative approach created effective communications between employees and authorities and enhanced their motivation for teamwork. Moreover, results could be used for decisions related to employees (such as promotion, transition, firing, and secondment), analysis of training requirements, employees’ development, and research and plan valuation. Our findings show that the collaborative coefficient (CC) is a key factor in increasing productivity and improving the efficiency of an organization in the long run. The collaborative coefficient is a new concept in teamwork that has rarely been considered in scientific research.

Health systems are recognised as playing a potentially important role in many risk management strategies; however, there is strong evidence that health systems themselves have been the victims of unanticipated risks and have lost their functionality in providing reliable services. Existing risk identification and assessment tools in the health sector, particularly in the blood supply chain, address and evaluate risks without taking into account their interdependence and a holistic perspective. As a result, the aim of this paper is to develop a new systemic framework based on a semi-quantitative risk assessment approach to measure supply chain risks, which will be implemented through a case study on the Iranian BSC. This paper identifies and assesses supply chain risks (SCRs) by employing a novel systemic process known as SSM-SNA-ISM (SSI). First, the supply chain and its risks are identified using Soft Systems Methodology (SSM). Then, given the large number of risks, the second stage uses Social Network Analysis (SNA) to identify the relationships between the risks and select the most important ones. In the third stage, risk levelling is performed with a more in-depth analysis of the selected risks and the application of Interpretive Structural Modelling (ISM), and further analysis is performed using the Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). The study found that by using the new proposed approach, taking into account risk relationships, and taking a holistic view, various supply chain risks could be assessed more effectively, especially when the number of risks is large. The findings also revealed that resolving the root risks of the blood supply chain frequently necessitates management skills. This paper contributes to the literature on supply chain risk management in two ways: First, a novel systemic approach to identifying and evaluating risks is proposed. This process offers a fresh perspective on supply chain risk modelling by utilising systems thinking tools. Second, by identifying Iranian BSC risks and identifying special risks.

Purpose: In order to answer which opportunities are better to pursue, the purpose of this paper is to propose and empirically test a decision-making model for evaluating and selecting entrepreneurial opportunities. Design/methodology/approach: First, the authors identified common evaluation criteria through a systematic review of 45 high quality articles published in top entrepreneurship and management journals between 2000 and 2017. Second, fuzzy screening technique has been employed to offer the decision-making model. Third, the authors used data of six evaluations provided by five experts at a medium-sized biotech firm to test the model. Findings: The study shows that common decision criteria for evaluating entrepreneurial opportunities fall into seven categories. According to these criteria and using fuzzy screening technique, a multi-expert multi-criteria decision-making (ME–MCDM) model has been suggested for evaluating and selecting opportunities. Practical implications: This model can be served in situations in which decision makers should select a small number of opportunities among the larger set with regard to opportunity profile and minimal information. More opportunities and more decision makers can be included in the model. When the number of opportunities and decision makers are high, it is possible to use programming for fast, accurate and easy calculation. Originality/value: This study is the first systematic review of opportunity evaluation criteria. It is also the first considering opportunity evaluation as a multi-expert decision-making process.

The purpose of this study is to contribute to the existing knowledge about the value of post-implementation Enterprise Resource Planning (ERP) system at the firm level. A questionnaire-based survey was conducted to collect data from 217 Malaysian firms that successfully implemented ERP system. Data analysis was conducted with partial least squares-structural equation modeling and partial least squares multi-group analysis techniques. Higher ERP spending and greater ERP scope in the post-implementation stage were associated with higher performance gains. Among other limitations, relying on a small sample size and cross-sectional data of this study and lack of generalizability of findings tend to have certain limitations. An interesting direction for future research would be to extend this study by conducting a multi-level analysis to understand how ERP spending and scope would affect the micro-level performance. Non-financial performance gain is another valuable outcome of ERP implementation. The choice between in-house and off-the-shelf ERP systems will have dramatic impacts on the future profitability of firms. ERP risk management team and related practices during implementation phase result in a significantly higher financial gain in the post-implementation phase. This study assesses the business value of ERP at the post-implementation phase while accounting for key contextual and managerial issues, a topic that has received little attention to date.