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The purpose of this paper is to present partial results of a survey conducted in Pune, India. Its aim is to determine the importance of factors, other than the buyer-related factors, that influence the purchase of a flat/apartment, of buyers of different types of flats/apartments.

The author follows three hypotheses for recent buyers of three different types of flats/apartments, namely, 1 BHK, 2 BHK and 3 BHK (where 1, 2 and 3 indicate the number of bedrooms, H stands for hall and K stands for kitchen. Thus 1 BHK designates a flat/apartment with one bedroom, a hall and a kitchen). A total of 284 respondents from buildings located on the outskirts of Pune city participated in the questionnaire survey for this study. Ten factors have been considered.

From this study, it is concluded that price is significantly the most important factor for buyers of 1 BHK, followed by product, and then followed by location. For 2 BHK buyers, there is no single significantly most important factor. For 3 BHK buyers, there is no single significantly most important factor and the two most important factors are product and location.

The results of this study show that buyers of different types of flats/apartments give different types of importance to the influencing factors. This study of buyer behavior will be helpful for the marketers of real estate companies, as they can identify the most important factors for various categories of buyers and implement those accordingly.

This study is the first to analyze the importance of the influencing factors for buyers of different types of flats/apartments. Also, it is the first to analyze the home-buying behavior for flats/apartments constructed in the outskirts, where most of the new constructions are taking place. This study will be useful to all the stakeholders of the housing industry.

The purpose of this paper is to develop a new composite model using structural equation modelling (SEM) and analytic hierarchy process (AHP) for the selection of suppliers.

In this paper the authors have made an attempt to arrive at the supplier selection score using SEM and AHP. An attempt has been made to develop a new composite model using SEM and AHP technique, based on the survey of 151 respondents. Attributes' weightage are found out using cluster analysis.

Based on the output from the composite model, cluster analysis has been carried out to find out the strengths and weakness of each supplier on the influencing factors. Based on these findings, the supplier can improve on factors where they lag and can maintain the factors where they excel.

In this paper the authors have made an attempt to arrive at the supplier selection score using SEM and AHP.

The purpose of this paper is to create a model called “Balanced score for the balanced score card” and to provide an objective benchmarking indicator for evaluating the achievement of the strategic goals of the company.

The paper uses the concepts of “Balanced scorecard” proposed by Robert. S. Kaplan and David P. Norton. This paper also adopts the model given by Brown P.A. and Gibson D.F. and the extension to the model provided by P.V. Raghavan and M. Punniyamoorthy. Preference theory is used to calculate the relative weightage for each factor, using the process of pair wise comparison. The balanced score for balanced scorecard provides a single value by taking into account all the essential objective and subjective factors – be it financial or non‐financial. It also provides a suitable weightages for those parameters. The target performance and the actual performance are compared and the analysis is made.

Information from a leading organization was obtained and the balanced score for a balance scorecard was calculated for that organization. The variations were analyzed through this model. The depth and objectivity in the analysis is highlighted.

This provides a single bench marking measure to evaluate how far the firm had been successful in achieving the strategies. The paper has adopted the preference theory which limits the weightage to be accorded to the factors concerned. However, further refinement can be provided by the usage of analytic hierarchy process for arriving suitable weightages.

The organization can calculate the balanced score by themselves, by assigning appropriate importance to the activities – as they deem fit. It is a tailor made benchmarking information system created by the firm for itself.

This is of value to the top management to identify the important activities and setting suitable target measures to be achieved in those activities. The variations are arrived by comparing the targeted performance with the actual. This will help the firm to take suitable actions under those parameters where there are significant deviations.

For repairable systems (RSs), reliability estimation is generally performed using virtual age models. Virtual age models consider the effect of maintenance actions by reducing system age using restoration factor (RF). RF is generally estimated from system failure data using various statistical methods. However, RSs such as railway systems experience various types of maintenance actions at different times during their life cycle. To consider all these different types of actions, we need multiple RFs in the virtual age model. As failure data are limited, the estimation of so many parameters becomes a complex problem and it can lead to erroneous inferences. These RFs are representative of effects of maintenance activities on the system. Therefore, these can be predicted from the information about the maintenance actions performed on the system. The paper aims to discuss these issues.

The paper considers different types of maintenance actions to predict RF of the system. These maintenance actions involve the replacement of components at some level of assembly. Each component in an assembly has its own impact on assembly restoration. RF for assembly/systems can be obtained by aggregating effects of multiple component replacement using analytical hierarchy process . The RF values obtained for different types of maintenance actions are then used to calculate the virtual age of the system at different failure points. Using these virtual age failure points, suitable distribution is fitted and parameters are estimated. The distribution and parameters provide information about reliability of the system at any point of time.

This paper provides an easier approach that gives different RFs for different types of PM and CM. To calculate RFs, it considers the impact of maintenance actions performed as well as the impact of the component on which they are performed. It is simpler and gives more consistent results than other approaches, which estimate RF using different statistical methods.

This paper provides an alternative approach to predict RF parameters instead of estimating these parameters using statistical methods. Estimation of parameters using different statistical methods is complex in nature and gives erroneous and inconsistent results. The approach given in this paper is simpler and gives more reliable results. This approach can be useful in estimating parameters for RSs when failure data are limited.

Standard quality is very highly important parameter in the education sector. Accreditation is a process where standard quality of education is given and the process of continuous improvement is defined. Emphasizing quality of student education is achieved through outcome-based education system (OBE). Program outcomes signify the comprehension, skills and attitude the students should have at the end of the program. At the end of each course, course outcomes signify the knowledge acquired by the students. Course outcomes assessment is one of the key aspects of the OBE model. In this research, the following four factors: subject quality, number of times subject handled by faculty members, faculty experience and student quality with different weightage, are used for analysis of the target setting for individual courses, used for higher education accreditation. This new approach for target setting will improve the teaching and learning process.

Four factors: subject quality, number of times subject handled by faculty members, faculty experience and student quality with different weightage, are used for analysis of the target setting for individual courses, used for higher education accreditation.

Using proposed approach, higher targets can be achieved in teaching and learning.

New approach for target setting will improve the teaching and learning process.

Proposed approach for target setting will improve the teaching and learning process; it should be implemented across all engineering colleges or universities.

All engineering colleges will have impact on teaching and learning process.

The following four factors: subject quality, number of times subject handled by faculty members, faculty experience and student quality with different weightage, are used for analysis of the target setting for individual courses, used for higher education accreditation.

This paper aims to identify and examine the determinants for sustainable manufacturing in cement manufacturing industry in India. Further, the study examines the causal relationship between different indicators of sustainable manufacturing.

Author (s) have identified and extracted the key dimensions of sustainable manufacturing from literature. After identification of the key dimensions, analytic hierarchy process (AHP) is used to finalize the weights and further DEMATEL is used to understand the causal relationship between key dimensions.

Findings from AHP provide the weightage to the all 13 indicators of sustainable manufacturing. From AHP, it is identified that material cost has maximum weightage, whereas material consumption has minimum weightage. From DEMATEL, it is evident that occupational health safety and safety has maximum influencing variables, whereas air emission does not have any influencing variables.

The approach adopted in the study will help firms to identify the weightage of key dimensions and further the interdependency can be developed to understand the causal relationship between different indicators of sustainable manufacturing.

The purpose of this paper is to propose an integrated qualitative and quantitative approach to the development of a balanced scorecard (BSC) for a real life case company KVIC (Khadi and Village Industries Commission, organic food sector, India).

In this paper the semi‐structured interviews with director, managers, professional consultant, review of published reports and observations made during research work are considered as basis.

This paper illustrates how the use of a mix approach of cause and effect diagram, Interpretive Structural Modeling (ISM) and Analytic Network Process (ANP) can address some of the shortcomings related to the development of BSC in the light of a real life case company KVIC (Khadi Village and Industry Commission, organic food sector India). The paper delivers a complete framework of BSC for the case company.

The paper outlines the limitations of proposed approach in regard to validity of present logical relationships among various objectives of organization in the futuristic environment and indicates the need for a computer software system, which can improve the efficiency of proposed approach.

In the paper a number of case studies report the fact that companies have attempted to derive measures from strategy, based on cause‐and‐effect reasoning, but the claimed link between strategy and measures appeared weak in analysis (Malmi, 2001). The paper establishes the basis for integrating organization's strategic intent with the identification of performance measures and at large development of BSC.

The paper shows that present work demonstrates the use of an innovative approach to the development of performance measurement system at one end while to deliver a workable framework of balanced scorecard for a real life case company is the objective of the other end. The present work encapsulates the philosophy of strategy maps using a mix of quantitative and qualitative approach for a real life case.

The purpose of this paper is to provide a framework for designing a multiple performance measurement tool for evaluating, comparing and benchmarking the working of engineering educational institutes in a group based on total quality management (TQM) criteria and performance measurement criterion, respectively.

Proposed framework is based on fuzzy analytic hierarchy process (FAHP) which takes in to account the fuzziness of human opinion for realistic outcome and generalization of the results. Based on the proposed framework a case study was conducted on engineering institutes of central India for collecting data and analyzing the current practices followed in these institutes. A relationship among TQM implementation criterion was developed, their respective weights derived and then institutes were ranked.

It was found that the rank of institutions based on both the criterion is same, which indicates that the institutes having better TQM implementation have better performance.

The research in this paper is limited to Indian scenario; studies in other countries and sectors may be conducted to compare the results obtained.

The results will help policy makers in identifying institutions having poor performance in the region.

The paper is navel in its attempt to provide a model based on TQM criteria for evaluating the working of engineering educational institutes in a group in terms of their relative weightage and benchmark.

Integrated supply chain in pharmaceutical industry requires organized planning and modeling of each strategic element of pharmaceutical supply chain (PSC). The aim is to coordinate each activity of PSC and design a robust strategy to make the system hassle-free. Each activity of industry is interdependent and follows certain co-relations with each other. The paper focuses on the four most significant identified issues in PSC and analyses the weightages of these issues and their sub issues with respect to cost incurred and time taken to manage whole chain of supply.

Fuzzy analytical hierarchy process methodology has been applied to rank the issues which consume maximum time and/or costs.

The derived result shows that warehouse design and management (WDM) consumes more than one third of the total time and around half of the total cost. Other than WDM, process of supplier selection for procurement is second most time and cost consuming issue. The derived results are discussed and provided to the field experts of the area. The analysis will be useful for decision makers to economize PSC.

The study is limited to PSC; hence, result may vary with other practical situations.

This generated scope for further research on how to minimize the weightage of WDM for cost and time in PSC industry so that decision-makers can optimize the economic system of PSC.

The research is based on the field survey of India’s largest generic medicine distributing company in the government sector; hence, analysis has been performed on real situation.

Despite being a global public–private partnerships (PPPs) leader, India faces a vast PPP divide at a sub-national level, wherein a few states receive the majority of PPP projects, whereas other states face severe issues in attracting PPP investments. This necessitates the identification of factors that make some states attractive to PPP investors. The purpose of this study is to construct a “PPP readiness index” at the Indian state-level, which aims to assess the readiness of states for the diffusion of PPPs.

Using a quantitative method on secondary data, the study scores 17 Indian states on dimensions such as experience with PPPs, physical infrastructure, financial sector development, market conditions, institutional quality and political stability and fiscal constraints for each of the years during 2009–2018. Principal component analysis is used for assigning weights to the dimensions, thereby arriving at the composite index.

Results highlight that Tamil Nadu and Maharashtra offer the most favorable environment for PPPs to flourish. In contrast, Jharkhand and Bihar are laggards because they score the least and have limited PPP experience.

The index will assist the private sector in conducting a comparative analysis between state-specific PPP arrangements, thereby enabling them to make informed decisions prior to forging PPP arrangements. Further, the index will help the state governments in improving their PPP readiness by following the policies of the leading states.

Improvement in PPP readiness of the states will enable higher PPP investments in infrastructure, thereby reducing infrastructure deficits. This, in turn, will lead to economic growth, development and an improvement in the quality of life.

To the best of the authors’ knowledge, this is the first study that comprehensively analyzes the PPP readiness at a sub-national level in India.