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This paper aims to focus on identifying various human enablers that could influence the performance of a firm using advanced manufacturing systems (AMSs), and to develop a framework to manage them through an analytical case study.

In this work, digraph and matrix technique through case study was utilized for finding the single numerical value, i.e. human enabler index (HEI), for quantifying the impact of human enablers of a firm under consideration using AMSs.

The major finding of this analytical case study is that a firm can identify the weak human‐related issues existing in their organizations. The HEI value for the considered organization is found to be low because it does not understand its corporate social responsibility, therefore the necessary decisions/actions may be taken for the performance enhancement and optimal utilization of the human element. In this way, the effectiveness of an AMS can be enhanced without big investments.

A larger number of human enablers could be considered for the analysis. However, the ranking has been done on the basis of the survey and expert opinion which may have an element of bias.

Analytical case study and the evaluated HEI could be used for quantifying the impact of human enablers in an AMS environment. This index can also be used to rank different organizations according to their capability to extract benefits in manufacturing from human characteristics.

The major and unique contribution of this research is to perform an analytical case study of a company using AMSs. Besides this, evaluating the HEI value for the organization, framework for comparison of two organizations and ways to improve its performance have been the unique contribution in its domain.

This paper aims to study the correlation between knowledge management (KM) enablers and performance indices of KM.

Referring to the literature reviews, it attempts to construct the KM process performance index, analyze its importance, and further analyze a company's characteristics, the relationship between KM enablers with the importance of the KM process performance index, and try to adopt four KM enablers as independent variables. Lastly, it intends to explore whether the relationship between the importance of the KM process performance and financial performance indices affects the importance of the financial performance index.

Among KM enablers, the factor strategy and leadership appears to be one of the most significant positive relationships among all of the KM process performance indices. The importance of performance indices in knowledge creation and knowledge internalization on the operational and customer sides show a positive, significant relationship in the importance of the financial performance index.

With the constraint of the number of samples, this study does not construct the KM process performance indices of every industry category or strategy.

The main contribution of the paper is that it explores the causes that influence KM process performance indices, and this enriches empirical research literatures in the domain of the KM process performance indices.

Though there has been steady growth in the automobile sector in India, India is still a player of little consequence in global auto production. Despite total quality management (TQM) playing an increasingly important role in the survival and growth of companies in the automobile sector, the dynamic interactions among its subsystems have not received due attention in the literature. Based on the Malcolm Baldrige National Quality Award model, this paper develops causal relationships among the different variables that represent “enablers” and “results” – operating within 44 identified feedback loops. Of these loops, 33 are positive and 11 are negative. The resulting causal loop diagram provides an insight into understanding the dynamic interactions among TQM subsystems which helps identify proactive action in implementing the TQM philosophy.

The purpose of this paper is to identify factors which influence participation of developing countries in the global value chains (GVC) and to present a mathematical modeling technique to calculate a “National Participation Index of a developing country in the GVC” (hereinafter referred to as G-NPI).

The paper identifies 17 factors, encompassing both country-specific and firm-specific considerations that influence a developing countries’ participation in the GVCs. These factors have been grouped into four sets of enablers, namely, macroeconomic, geo-economic, strategic and geopolitical. The national participation index (G-NPI) has been calculated using the graph theoretic modeling approach.

Besides identifying the factors of a developing country’s participation in the GVC and grouping them as enablers, the paper considers the case of India as an example and assesses the level of interactions within (i.e. among various factors of a given enabler) and among these enablers (leading to a G-NPI value) using graph theory.

The findings can be used to calculate G-NPI for different countries to ascertain their potential for participation and also to find the factors(s) which may be deterring their participation in the GVCs.

This paper can help in policy advocacy to enhance the competitiveness of developing countries and consequently to improve the life of their consumers.

This paper introduces the concept of G-NPI and presents a unique way of assessing a developing country’s participation in the GVCs through a mathematical modeling approach.

Today's volatile condition of the market is forcing the manufacturing organizations to adapt the flexible manufacturing systems (FMS) to meet the challenges imposed by international competition, ever‐changing customer demands, rapid delivery to market, and advancement in technology. There are certain enablers, which help in the implementation of FMS or in the transition process from traditional manufacturing system to FMS. The utmost need is to analyze the behavior of these enablers for their effective utilization in the implementation of FMS. This paper aims to address these issues.

This paper presents a methodology based on graph theoretical approach for finding the feasibility of transition to FMS for any industry. A universal feasibility index of transition (FIT) is proposed that evaluates and ranks different organizations according to their capability to be converted into FMS. This FIT value is obtained from a permanent feasibility function obtained from an enablers' digraph of FMS.

The major finding of this paper is that one can judge whether a particular industry is fit for FMS or not by calculating its FIT value. This FIT value can also be utilized in ranking different industries for their possible transition to FMS.

The FIT obtained from a permanent function indicates the strength of enablers and their inter‐relations. More is the value of this index; more will be suitability of that organization for FMS adoption. In this way, managers can judge that a particular organization is suitable or fit for FMS implementation or not, without making the huge investments for such a complex production system and thus, minimize their risks.

Identification, classification of enablers into some important categories, and their analysis is a unique and innovative effort in the area of FMS.

The purpose of this paper is to validate the enablers of bio-inspired model of organizational excellence proposed by Agarwal and Vrat (2015a). It is also aimed to test its usefulness as an instrument in evaluating the degree of organizational excellence achieved.

Survey methodology has been used to investigate the hypotheses. Data have been collected through a self-structured questionnaire with closed-ended questions. Structural equation modeling and analytic hierarchic process have been used to test and analyze the data.

The results of hypothesis testing indicated that out of 19 paths only ten were significant. However, in the revised model only six paths out of those ten significant paths were retained and three new suggested paths were incorporated to make the final model. Besides, calculation of relative weights of each enabler shows that being self-driven occupies the top-most rankings, supply chain optimization occupies the second rank and promptness and reliability and maintainability occupy the bottom ranking in driving performance excellence, being resulting outcomes.

The major limitations of this research are: verification of the proposed model is done on only two test companies, and results of which are compared with one excellence award model only. Besides, the score resulted for test companies are based on self-assessment by them and thus require further validation.

The validated model can be applied for assessing degree of organizational excellence achieved by any company. The results of the assessment would serve as key focus areas for improvement.

The research is first to benchmark the human body for assessing the degree of organizational excellence achieved. The uniqueness of this model is that the various parameters of excellence assessment which are derived from human body, perceived as a benchmark in being the most well managed system.

This paper forms part of an ongoing research project being undertaken by the authors into construction safety culture. The paper aims to investigate the interactions among five key enablers of construction safety culture, as well as the potential impact of each enabler on organisational safety goals over a period of time.

Using system dynamics modelling, the paper reports on the development of a causal model simulating the interactions among safety culture enablers. The model is developed based on the logical assumption that, by improving the enablers, there will be an inevitable safety performance improvement. An index is also proposed and used as an indicator for assessing the maturity level of safety culture.

The paper presents and reports on simulation results which reveal that an organisation with ad‐hoc safety implementation (starting at a basic level of safety culture maturity) should primarily focus on enhancing leadership attributes, in the context of safety, to rapidly and successfully progress through to higher maturity levels in the future.

The use of system dynamic modelling, with the developed index, will help organisations to plan the most effective safety implementation process to achieve their safety goals within a planned time frame.

The use of modelling, with the developed index, will help organisations to plan the most effective safety implementation process to achieve their safety goals within a planned time frame.

The purpose of this paper is to report a case study carried out to assess the agility and identify obstacles to agility in a supply chain. A human perception-based framework is used for the calculation of agility. The case study was carried out in a North India-based manufacturing organization.

In this study, the concept of a multi-grade fuzzy logic approach is used. Using this concept, the overall agility index has been determined. The fuzzy logic approach has been used to overcome the disadvantages such as impreciseness and vagueness using a scoring method.

From the analysis, it is observed that the organization on which the study was performed is “very agile.” After evaluating the agility level, the fuzzy performance importance index is calculated, which helps to identify the barriers of agility in the supply chain. These barriers help decision makers to implement appropriate improvement measures for improving agility level. Overall, 11 barriers were identified in the study.

Managers of the contemporary manufacturing organization have to measure the agility level of the organization and identify barriers to agility in order to survive in a competitive environment. The obstacles identified in this study are used to improve the performance of the organization. The enterprise should improve on the weak areas in order to achieve the highest agility level.

The agile supply chain (ASC) enablers proposed by previous researchers are not sufficient for the evaluation of agility of a supply chain. There are a few more ASC enablers such as customer satisfaction, flexibility and adaptability that also play a vital role in making a supply chain agile. Adding these three ASC enablers, a total of seven ASC enablers along with their attributes are being considered for the development of a conceptual model.

The Healthcare sector is one of the important sectors of the Service Industry. It is believed that in this sector, the customer server relationship is very critical, and even the slightest gap in the people quality may have a huge impact on the delivered service quality. Some of these enablers are doctors, nursing staff and support staff. Furthermore, the nonpeople quality enablers such as diagnostic services, facilities, hygiene levels and so on are also likely to impact the delivered service quality. It was also felt that the degree of impact each enabler has on the service quality could vary. Therefore there is a need for structured and deep analysis. The paper attempts to identify, analyze and prioritize the enablers that impact the delivered service quality.

The enablers have been identified through literature review and inputs from experts in the healthcare fraternity. The authors have explored different decision-making tools such as analytic hierarchy process (AHP), analytic network process (ANP), stepwise weight assessment ratio analysis, Hybrid Model and DEMATEL (Decision-Making Trial and Evaluation Laboratory) for the analysis of data in this paper. Based on the strengths of the approach and careful considerations by focus group discussions, DEMATEL was chosen as the best option. It is simple, unique, sparingly used in the healthcare sector, effective in prioritizing and gives meaningful insights on importance, cause and effect factors. DEMATEL approach converts the complex problem with interrelated factors into a clear structure that makes simple interrelationships among factors in the form of cause and effects digraph, and hence, the authors chose to use it. A case study in one of the hospitals has also been conducted to demonstrate the applicability of the developed index. The case study very strongly validates the developed index.

This research paper has found that there are people quality enablers such as the doctor, nursing staff, support staff and nonpeople quality enablers such as facilities, diagnostic services and hygiene levels maintenance, which impact the delivered service quality. It also concludes that the delivered service quality depends not only on the quality but also on the availability of these enablers. The inputs received from the experts have been run through the DEMATEL methodology and importance computed for each. The top five priority enablers are Quality of Doctor, Availability of Doctor, Quality of Support Staff, Quality of Nursing Staff and Availability of Support Staff.

The weights of the enablers have been obtained using the DEMATEL tool. These weights have been calculated using the inputs from 22 experts, which meets the statistical requirement (Skulmoski, 2007). However, a larger group of experts can be reached, and based on the inputs received from them, the tool can be revalidated for repeatability and reproducibility. Using Fuzzy DEMATEL can also be explored for further analysis.

The proposed framework to assess the service quality level of a healthcare organization is based on a sound approach of DEMATEL. The service index arrived, thereafter, can be used to rate the delivered service quality by any healthcare organization. It can be used to compare the similar type of healthcare organizations across locations. This Index can facilitate improvements in the healthcare organization through internal and external benchmarking. It also helps the organization to know the gaps, understand the root cause, improve upon them and become the best in class. This Index uses the inputs from the end customers to calculate the rating, which makes it more reliable and accurate. The overall scores obtained from the Index can provide the ranking to the healthcare providing organizations and options to customers to choose from best. The service quality index can be used by an organization to continuously monitor their delivered service quality scores and improve them to become the best in class. The research paper highlights the significant role played by the people quality and its strong impact/contribution on the delivered service quality. Hence, it is believed that it will encourage the healthcare organizations to prioritize the improvement and upgrade of the people quality over the nonpeople quality aspect.

Putting people and nonpeople quality enablers in one single model and assigning weights to them using the DEMATEL approach is a new application in healthcare. Developing an Index to measure the delivered service quality in the healthcare sector is also different and new.

Numerous leanness assessment models were developed for both manufacturing and service sectors. However, little research effort was made to provide an instrument that can be used to measure the leanness level of the product-service system (PSS). This paper aims to propose an index to assess the leanness of PSS in a UK manufacturing company.

The development of the assessment model was carried out through an iterative process. Commencing from existing literature on lean manufacturing assessment and lean service assessment, the initial model for assessing PSS leanness was developed. This initial model was refined via two consecutive phases. The first one includes semi-structured interviews with academic researchers involved in lean projects where their comments were considered. In the second phase, semi-structured interviews with several experts working in different UK manufacturing industries and involved in lean and continuous improvement projects were conducted to reach the final assessment model. After developing the model, the next step was identifying a suitable company for applying the model. The case company was selected because of its commitment to implement lean practices and its ability to participate in this study. After that, data was collected from the case company and the PSS leanness index was calculated using a multi-grade fuzzy approach. Finally, areas for further improvement were identified and the results obtained were validated.

The PSS leanness index computed for the case company indicates that the service offering process provided by the company is generally lean. Areas for further improvement were identified.

This study focussed on a single case company and is based on the experts’ opinions; this may tend to be biased. However, future studies will be performed to multiple-case studies to enhance findings and more empirical research will be conducted to catch more insights into PSS leanness.

This paper provides guidelines to manufacturing companies’ managers for measuring the PSS leanness index and planning for the future. This index gives information regarding the degree of lean adoption in the service offering process and identifying the gap between the current PSS leanness level and the desired state.

The proposed model has been developed by the opinion of academicians and industry experts. The proposed model can provide guidelines and directions for managers for PSS leanness assessment.