Identifying enablers of technological innovation for Indian MSMEs using best–worst multi criteria decision making method

Gupta, H.C.; Barua, Mukesh Kumar

doi:10.1016/j.techfore.2016.03.028

Cited by 238 publications

(139 citation statements)

References 101 publications

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“…Scholars have used this method since then to identify enablers of technological innovation in Micro, Small and Medium Enterprises (MSMEs) in India [31], utilizing this method for the supplier selection life cycle [32], to evaluate the external forces affecting the sustainability of the oil and gas supply chain [33], or even wielding this tool in order to develop a roadmap to overcome barriers to energy efficiency in buildings [34]. Recently, intuitionistic fuzzy multiplicative BWM has been proposed by [35] to extend the method's use to uncertain circumstances.…”

Section: Best-worst Methodology (Bwm)mentioning

confidence: 99%

“…Therefore, the best and worst criteria are chosen among the proposed criterion suggested by decision-makers and the whole purpose is to find the optimal weights and consistency radio (CR) through an optimization model constructed using the comparison between the best criteria over others and vice versa. Figure 2 indicates the BWM process as a system and briefly sets out the steps in the rest of this section based on [29,31,32]. Step 1: Designation of criterion.…”

Section: Best-worst Methodology (Bwm)mentioning

confidence: 99%

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A Novel Hybrid Approach for Technology Selection in the Information Technology Industry

et al. 2018

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High-tech companies are rapidly growing in the world. Research and development (hereafter R&D) department strength is the main asset that allows a firm to achieve a competitive advantage in high-tech businesses. The allocated budget to this sector is finite; thus, integration, human resource, risk and budget limitations should be considered to choose the most valuable project in the best portion of time. This paper investigates a case study from a high-tech company in Iran to prioritize the most attractive technologies for the R&D department. The case consists of twenty three technology options and the goal is to find the most attractive projects to sort them out for implementation in the R&D department. In this research, scholars proposed the best-worst method (henceforth BWM) to find the weight of the criteria of the attractive technologies in first step and utilize the newly developed method total area based on orthogonal vectors (henceforward TAOV) to sort the selected technologies based upon the identified criteria. Project integration is one of the least-noticed subjects in scientific papers; therefore, the researchers presented a zero or one linear programming (ZOLP) model to optimize and schedule the implementation procedure on the project risk, budget and time limitation simultaneously. The results indicate that starting few but attractive projects in the first years and postponing the rest to the future, helps a firm to manage funds and gain profit with the least amount of risk.

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Section: Best-worst Methodology (Bwm)mentioning

confidence: 99%

Section: Best-worst Methodology (Bwm)mentioning

confidence: 99%

A Novel Hybrid Approach for Technology Selection in the Information Technology Industry

et al. 2018

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show abstract

“…We selected this method mainly because (1) it uses a very structured way to gather pairwise comparison data which results in highly reliable results; (2) It uses only two vectors instead of a full pairwise comparison matrix, which makes it an excellent method when data collection is costly with respect to time and money; (3) It is easy to understand by the evaluator, and also easy to revise by the evaluator in order to enhance the consistency level of the comparisons. The BWM has been successfully applied to other problems such as logistics and supply chain management (Rezaei et al 2015, 2016a, b), risk management (Torabi et al 2016), and innovation management (Gupta and Barua 2016). The steps of the BWM are as follows (we describe these steps to calculate the weights for inputs, the same procedure is used to calculate the weights for outputs).

Step 1 Determine a set of inputs.

…”

Section: Measuring Efficiency Using Bwmmentioning

confidence: 99%

Measuring efficiency of university-industry Ph.D. projects using best worst method

2016

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A collaborative Ph.D. project, carried out by a doctoral candidate, is a type of collaboration between university and industry. Due to the importance of such projects, researchers have considered different ways to evaluate the success, with a focus on the outputs of these projects. However, what has been neglected is the other side of the coin—the inputs. The main aim of this study is to incorporate both the inputs and outputs of these projects into a more meaningful measure called efficiency. A ratio of the weighted sum of outputs over the weighted sum of inputs identifies the efficiency of a Ph.D. project. The weights of the inputs and outputs can be identified using a multi-criteria decision-making (MCDM) method. Data on inputs and outputs are collected from 51 Ph.D. candidates who graduated from Eindhoven University of Technology. The weights are identified using a new MCDM method called Best Worst Method (BWM). Because there may be differences in the opinion of Ph.D. candidates and supervisors on weighing the inputs and outputs, data for BWM are collected from both groups. It is interesting to see that there are differences in the level of efficiency from the two perspectives, because of the weight differences. Moreover, a comparison between the efficiency scores of these projects and their success scores reveals differences that may have significant implications. A sensitivity analysis divulges the most contributing inputs and outputs.

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“…Mou et al (2016) presented a fuzzy multiplicative BWM for a group decision-making problem. Gupta and Barua (2016) determined enablers of technological innovation for Indian micro, small and medium enterprises based on BWM method. Gupta and Barua (2017) used BWM and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) (Hwang & Yoon, 1981) for green supplier selection among SMEs.…”

Section: Introductionmentioning

confidence: 99%

Best-worst multi-criteria decision-making method: A robust approach

Sadjadi¹,

Karimi²

2018

10.5267/j.dsl

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Identifying enablers of technological innovation for Indian MSMEs using best–worst multi criteria decision making method

Cited by 238 publications

References 101 publications

A Novel Hybrid Approach for Technology Selection in the Information Technology Industry

A Novel Hybrid Approach for Technology Selection in the Information Technology Industry

Measuring efficiency of university-industry Ph.D. projects using best worst method

Best-worst multi-criteria decision-making method: A robust approach

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