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Lean manufacturing (LM) has attracted the attention of industries all over the world. Many operation managers have implemented or will be implementing LM because of the benefits reported by other companies or because their customers have demanded it. This paper aims to present a case study of a medium‐sized valve manufacturer in which the decision of implementing LM is made by analyzing the capabilities, practices, tools and techniques of alternative manufacturing systems apart from understanding its effect on the decision areas of the operations department.

A multi attribute decision making (MADM) model, namely, the analytic network process (ANP) has been used for this purpose, which structures the problem related to selection of alternative manufacturing systems in a hierarchical network form. In this problem, it links the performance measures or competitive priorities, decision areas, and the elements with alternatives available to the decision maker and provides a holistic framework for the selection of alternative manufacturing systems to achieve the competitive priorities of the organisation under study.

From an extensive analysis of the results, under the given circumstances, it is evident that implementation of a lean manufacturing system (LMS) is a better alternative, as it would result in overall improvement in the performance of an organisation in comparison with the alternatives.

This paper demonstrated a step‐by‐step approach of the ANP model using a case study of a small‐ and medium‐sized enterprise, which makes it more suitable for managers to learn and adopt such MADM models to support their decisions.

To the author's knowledge, there is no paper available in the existing literature that discusses the application of ANP in the field of LM.

The purpose of this paper is to review the existing literature on supply chain performance measures and metrics (PMMs). It provides a critical evaluation of 234 articles published in past 24 years.

The paper examines the studies published from 1991 to 2014 by adopting the bibliometric technique of citation and co-citation analysis.

The analysis of the results indicate that the number of articles on supply chain PMMs is increasing at its fastest pace in the past few years. Furthermore, the study identifies some of the most influential articles on performance measurement and metrics. Finally, it concludes that there has been a transition from traditional to more sophisticated performance measurement system.

This study focuses only on supply chain performance measurement and metrics and excludes research on performance management and control. Thus, researchers may explore and extend this area of research.

To the knowledge of the authors, this is the first study to review the literature on supply chain PMMs by using citation and co-citation analysis. The study includes 234 articles over the time of 24 years (1991-2014).

In recent years, there has been a growing awareness that most decision makers are not only concerned with the financial implications of information technology/system (IT/IS) projects, but they are also concerned with other objectives such as competitive advantage, market share and future growth. Nowadays, multi‐criteria decision‐making methods are gaining importance due to their inherent ability to judge different alternative scenarios for possible selection of the best alternative. This paper provides a decision‐making framework for senior executives when selecting innovative IT/IS projects. The proposed framework is based on the multi‐criteria utility theory (MCUT) combined with information economics principles to select IT/IS project(s) based on “business value” and “risk” criteria. MCUT has the advantage of taking into consideration the decision maker’s preferences in the form of utility functions defined over a set of tangible and intangible criteria. To illustrate the application of the proposed framework, a hypothetical case study is provided, where input elicited from four engineering professionals is used to develop utility functions for a predefined set of selection criteria.

Globalisation of markets, the knowledge economy, e‐business and introduction of new technologies pose new challenges to all organizations irrespective of their size and sector for sustaining their competitiveness. In this scenario successful implementation of advanced manufacturing technologies (AMTs) by firms can give them an edge over their competitors. This paper aims to identify and develop the structural relationship among different factors for successful implementation of AMTs.

A questionnaire‐based survey and interpretive structural modelling (ISM) approach has been applied in this study. In this research, 14 factors have been identified such as top management commitment, organization culture, sound financial condition, training, integration of departments, etc. On the basis of survey results and opinion of experts from industry and academia, a structural relationship model has been developed through an ISM approach.

Top management commitment and sound financial condition are the major drivers for implementing AMTs. Effective implementation of AMTs will improve organization performance in terms of lead time, product cost, fast delivery and product quality. For effective implementation of AMTs, management should not ignore managerial aspects such as organization culture, employee training, integration of departments, vendor development, strategy development and customer involvement.

Management needs to address driving variables more carefully for successful implementation of AMTs.

There are various risks that can derail the adoption of business analytics (BA) practice in a telecom service provider (TSP) thereby jeopardising the possibility to increase profitability and improved customer experience. The purpose of this paper is to analyse different associated risks using situation-actor-process, learnings-actions-performance (SAP-LAP) model and build mitigation strategies for the adoption. Also the risks are ranked using the interactive ranking process (IRP) methodology and the dominating matrix provides insight to the actions and actors that need attention to improve the processes and performance.

A case study of a TSP (X1) was analysed through close interactions with experts within the company and externals involved in setting up the BA practice in X1. Using the SAP-LAP framework risks were identified and then the IRP was used to rank the actors w.r.t performance and actions w.r.t processes.

X1 has taken initiatives for setting up the BA practice in order to improve the profitability and customer experience through data insights. The suggested conceptual SAP-LAP model helps to address risk mitigation strategies for its adoption and the IRP frameworks helps in understanding the prioritisation matrix (using the ranking) to be considered to mitigate the risks.

The IRP framework is limited to certain relationships between actors, w.r.t processes and actions w.r.t performance for the prioritisation matrix of identified risks. This has scope to be further expanded to other relationships and therefore refining the findings. Also this approach could be used to study other industries too.

SAP-LAP model identifies the risks in adopting the BA practice in a TSP. The synthesis of SAP leads to LAP, which bridges the gap by suggesting improvement actions based on the learning from the present situation, actors and processes. IRP provides the prioritisation matrix for mitigating the risks by identifying the dominating factors.

BA practice plays a dominant role in a TSP. An approach to study the risks of its adoption using the SAP-LAP and IRP framework bridges the gap between the academic and corporate world. This paper is very relevant to managers involved in setting up a BA practice. For the academic, use of research model validates the identification of risks that are recognised in the corporate world and prioritising the risks that need to be addressed.

The purpose of this paper is to evaluate the enablers for improving the utilization level of advanced manufacturing technologies (AMTs) in Indian manufacturing industry.

In this paper, a large number of manufacturing organizations have been extensively surveyed, to ascertain the contributions made by success factors of AMTs towards realizing manufacturing performance improvements. The correlations between enablers of AMTs' utilization and manufacturing performance parameters have been evaluated and validated by employing various statistical tools.

The paper focuses upon significant contributions of AMTs' success factors namely: education and training of employees; interdisciplinary team formation; rewards and recognition to employees; and industry‐institute interaction, towards affecting improvements in manufacturing performance in Indian industry. The inter‐relationships between various AMTs' utilization success factors with the manufacturing performance parameters have been evaluated.

The study has been conducted only in Northern Indian manufacturing organizations.

The paper highlights the strong potential for enablers of AMTs' utilization in improving organizational performance parameters.

The paper's aim is to provide a tool for decision makers to make more informed decisions regarding their investment in advanced technologies.

Selection of an advanced technology for adoption requires evaluation of several competing alternatives. The difficulty in the evaluation process arises when the ranking of the alternatives is not possible from the result of the financial analysis alone. The purpose of this study is to overcome such difficulty by considering other factors that allows distinction among alternatives with similar economic evaluation results. This is accomplished by identifying the risks or undesirable consequences of technology implementation and including them in the evaluation process. These are costs that are not measurable for inclusion in the financial analysis but could have major impact on the final selection. Owing to uncertainties involved with adoption of a new technology, the involvement of human expertise and judgment seems to be essential in the evaluation process. To accomplish this a process is proposed where decision maker's perceptions on the performance of technology alternatives along with the importance of the relevant risks are solicited in linguistic terms. Fuzzy numbers are then used to represent these linguistic perceptions. Fuzzy arithmetic operators are applied to calculate an aggregate fuzzy score for each alternative. These fuzzy scores are then converted to crisp scores to allow the ranking and selection of the best alternative.

Addition of subjective perceptions to the purely quantitative approach provides a more realistic evaluation process.

The proposed procedure can help practitioners with their technology adoption decisions.

The value of the paper is the inclusion of the decision maker's judgment in the evaluation process by use of fuzzy logic.

The purpose of this research is to develop a framework/model for the implementation of advanced manufacturing technologies (AMTs) in small and medium enterprises (SMEs).

A quantitative approach has been applied. This approach is subjective, as is the data collected and compared in detailed, and the outcome is only as good as the questions developed. The research methodology employed here is based on a literature survey, a model/framework and an empirical analysis using the data collection from the structured questionnaire from SMEs located in the Province of Sindh in Pakistan.

There is a lack of engineering orientation, in‐house expertise and organizations long‐term vision to accept new technologies. The surveyed companies are giving less importance to arranging training and education facilities either in‐house or out side of the companies to their employees. Also, there is a lack of incentives and rewards scheme inside the surveyed companies.

The framework developed in this paper and findings of the research results will provides a road‐map to the SMEs who are in a process of implementing AMT.

Globalisation and liberalization of today's markets economy has posed new challenges to all manufacturing organizations, irrespective of their size and sector, for effective utilization of advanced manufacturing technologies (AMTs) for sustaining their competitiveness. The purpose of this paper is to provide a new insight into the use of hybrid methodology using analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach, which is a multi‐criteria decision‐making methodology for measuring the effective utilization of advanced manufacturing technologies.

A hybrid methodology using analytical hierarchy process and technique for order preference by similarity to ideal solution approach has been applied in this study. In this research work, seven factors such as top management support, resistance of employees, pay scale, training to employees, industry‐institute‐interaction, proper planning and team structure have been selected to determine the priority weights of attributes by using AHP. TOPSIS method is then employed to achieve the final ranking results. To benchmark the success possibility of AMTs utilization, AHP has been applied.

Top management support, resistance of employees and pay scale have been ranked as first, second and third important sub‐objectives for effective utilization of AMTs. While industry‐institute‐interaction, proper planning, training to employees and team structure have been placed at fourth, fifth, sixth and seventh positions for effective utilization of AMTs. It has been further noted that by using AHP, the successful utilization of AMTs can be found out.

The parameters selected for this study are applicable to the northern India manufacturing industry.

An attempt has been made to apply hybrid methodology approach using AHP and TOPSIS for effective utilization of AMTs. This is probably the first time that an attempt has been made to apply the hybrid methodology using AHP‐TOPSIS‐AHP for benchmarking the success possibility of utilization of AMTs in the northern Indian manufacturing industry.

The aim of this study is to identify the association between leadership styles (LS) and employee commitment(EC) among employees working in the mechanical manufacturing small- and medium-sized enterprises (SMEs), mediated by job satisfaction.

The research is cross-sectional and the survey method was used, and Pearson correlation analyses, regression analysis and structural equation modelling (SEM) were used to examine the hypothesis. A sample of 911 responses was collected from 102 mechanical manufacturing SMEs in and around Bangalore, India.

EC depends on the age, the experience of employees, LS of the superior and job satisfaction of employees who are working in the mechanical manufacturing SMEs. The research found out that job satisfaction partially mediates the relationship between LS and EC.

The study is cross-sectional in nature; it measures and quantifies the different variables at a single point period; therefore, the research does not offer outcomes over a long period.

To enhance the commitment of employees working in the mechanical manufacturing SMEs, managers/superiors should make an effort to exhibit a holistic view of LS that enhances job satisfaction and improves the pleasant relationship in the work environment.

In the competitive business environment retaining skilled and talented employees is the major challenge for the organization. Many research studies explored that committed employees will retain in the organization for a long tenure. Thus, our study contributes to the body of the literature on predictors of EC. It is noted that the involvement of employees by the leaders during the decision-making process, creates an effective working ambience for the employees and establishes a pleasant relationship among employees. The leader will motivate the employees to work efficiently and effectively, in addition to that they motivate employees to continue working with the same organization. Hence there is a need for the mechanical manufacturing firms to design and implement strategies of motivating employees to remain in the organization. Our study was cross-sectional in nature; it measures and quantifies the different variables at a single point period; therefore, research does not offer outcomes over a long period. Hence a longitudinal study over some time gives more accurate outcomes, and it is more appropriate. This study focused on employees working in the mechanical manufacturing firms, in and around Bangalore, India; therefore, findings cannot be generalized to all employees of the mechanical manufacturing firms.

This research contributes to the existing literature by exploring further evidence and support for the relationship between LS and EC in mechanical manufacturing SMEs. And research also reveals that job satisfaction partially mediates the relationship between the LS and EC in mechanical manufacturing SMEs.