Purpose The purpose of this paper is to understand the dark side of blockchain technology (BCT) adoption in small and mid-size enterprises. The focus of the authors is to decode the intricate relationship among the selected variables missing in the existing literature. Design/methodology/approach A focused group approach is initiated by the authors to identify the barriers. Total interpretive structural modeling, Matrice d'impacts croisés multiplication appliquée á un classment, that is, matrix multiplication applied to classification and decision-making trial and evaluation laboratory are used to analyze the complex relationships among identified barriers. Findings This study finds that implementation of BCT reduces maintenance cost by withdrawing manual effort, as BCT has better capability to quantify the internal status of the system (observability characteristic). The observability characteristic of BCT provides high compatibility to the system. This study also finds that the compatibility of BCT with the organization reduces implementation cost and facilitates project management. The findings of this study recommend analyzing maintenance cost and compatibility of BCT before implementing it. Small and mid-size enterprises can select complex BCT depending on the sophistication level of IT usage and IT project management capabilities. Research limitations/implications This study comes with various limitations, where the model developed by the authors may not be conclusive, as it is based exclusively on expert opinion. The samples collected may not help in validating the model statistically. Though the model has its limitations, it can still be considered as a nascent initiative for further investigation using structural equation modeling. Originality/value The outcomes of the theoretical and managerial contributions of the study can be categorized into three levels. This study can be used both by the industrialists and researchers to understand the barriers and the recovery methods thereafter. Suggestions that serve as future directives are also discussed by the authors.
Purpose In the era of multiple global disruptions, firms are finding it to continue their business. MSMEs are impacted more as they have constrained resources. Organizational flexibility has emerged as an organizational and management principle that would help firms stay competitive even in volatile markets. This study aims to present a set of guidelines and insights for MSME managers to implement organizational flexibility in their organizations. Design/methodology/approach This study uses total interpretive structural modelling to study how the various factors contributing to organizational flexibility behave together. Behavioural theory is used to explain why organizations need to incorporate flexibility, and systems theory of organization is used to explain why an organization needs to have open boundaries. Findings Organizational flexibility is a principle that may be supported by the systems theory of organization. The study has shown that it is important for MSMEs to have supply chain collaborations to be more flexible. The study also shows pressure from competitors as the key driver that would make a firm more flexible, and that adequate support from management and technological skills are required to drive flexibility in an organization. Research limitations/implications Single respondent bias may have occurred in this study. This can be eliminated by interviewing multiple people from the same organization. Further research around the reasoning for linkages can be explored with theory-driven grounded studies. Originality/value This study attempts to use a multi-criteria decision-making technique to present insights to managers to help them make their organizations flexible.
In this paper, we present formulations to improve operational efficiency with optimum utilization of working capital management. A case of manufacturing firm is conducted to discuss the stages of analysis. This paper discussing the method to establish the target values for the firms to optimize the working capital and perform as an efficient firm. The concept is explained with the help of Data Envelopment Analysis (DEA) and Goal Programming (GP) techniques. By using the principles of DEA, the firms are able to identify their slacks in inputs and outputs variables to perform as efficient firms. GP model is formulated in which input and output variables are set as goals and then target values are calculated. GP model solution provides the values of each variable with the efficiency in attaining the goals. Here the analysis is explained with the help of a published dataset obtained from the firm Wheel India Limited. The output of the GP model provides the values to be maintained by input variables. These outputs from GP model are validated using output oriented DEA analysis, by replacing the variables value of Wheels India Ltd. by model value.
Operational efficiency in machinery manufacturing industry is determined using data envelopment analysis models. Data pertaining to 137 machinery manufacturing firms in India for the years 2005–2010 is used for the study. The output can be increased by 30.12 percent without affecting the input levels. Fourteen among the firms identified efficient appear to be peers to other less efficient machinery firms. The slack of the input variables are identified and reducing these to zero is suggested to achieve 100% efficiency. A super-efficiency analysis of peer firms is conducted to identify the firms important for efficiency improvement. The gearing ratio contributes significantly to the inefficiencies, and attaining the efficiency frontier requires the follower of a peer firm to maintain constant values of the sensitive variables and reduce the input slack of the influencing variable to zero.
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