Shubham Garg, Sangeeta Mittal and Aman Garg
This study aims to investigate the determinants of GSTefficiency of the Indian states to assist the policymakers, government and GST council to devise their policies and…
Abstract
Purpose
This study aims to investigate the determinants of GSTefficiency of the Indian states to assist the policymakers, government and GST council to devise their policies and strategies to boost the GSTefficiency of the Indian states.
Design/methodology/approach
The analysis has used the panel data set of 27 Indian states and 3 UTs with a time span of 2017–18 to 2022–23. The study has used the Generalized Method of Moment regression for exploring the determinants of GSTefficiency of the state governments in India.
Findings
The findings depict that sectoral composition, inflation rate, financial development, state’s self-reliance, per capita income and gross fiscal deficit have a significant effect on GSTefficiency of the state governments. The findings support the Tanzi effect 1977 and claim that the rise in the inflation level erodes GSTefficiency of the state governments. The rise in the self-reliance of the state government will make the Indian states self-dependent and will reduce their reliance on central transfers.
Practical implications
The government should make efforts to make the Indian states self-reliant by increasing the share of OTR (Own Tax Revenue) instead of increasing their revenue efficiency in short-run through devolution and central transfers. Moreover, the Indian government should devise their macro-economic policies to curb the inflation level and gross fiscal deficit of the state governments in the country.
Originality/value
To the best of the authors’ knowledge, this may be the first study to explore the determinants of GSTefficiency of the state governments in India.
Details
Keywords
Vinay Gadi, Shivam Singh, Manish Singhariya, Ankit Garg, Sreedeep S. and Ravi K.
The purpose of this paper is to numerically investigate the combined effects of canopy (leaf area index [LAI]) and root properties (root distribution function [Rdf] and root area…
Abstract
Purpose
The purpose of this paper is to numerically investigate the combined effects of canopy (leaf area index [LAI]) and root properties (root distribution function [Rdf] and root area index [RAI]) on a suction induced in soil-root composite under three different scenarios.
Design/methodology/approach
Richards equation coupled with sink term was solved using a commercial finite element package “HYDRUS” to investigate suction induced in soil-root composite.
Findings
Scenario 1 unveiled that soil-root composite induces 1 to 20 per cent higher suction than bare soil under the absence of transpiration. From Scenario 2, value of suction at depth of maximum RAI in case of linearly decreasing Rdf was found to be higher than that of other Rdfs. However, depth of suction influence zone (SIZ) for uniform Rdf and non-linear Rdf was found to be 10 and 11 per cent higher than that of linearly decreasing Rdf. Depth of evaporation dominant zone (EDZ) for uniformly decreasing Rdf and non-linear Rdf was found to be 1.08 to 3 times higher than that of linearly decreasing Rdf. From Scenario 3, influence of LAI on depth of SIZ is minimal. Depth of EDZ was found to decrease with the increase in LAI. Based on simple calculation on infinite slope stability, influence of variation in root and shoot properties was found to be significant on its factor of safety.
Research limitations/implications
Numerical constitutive model has limitations that it does not consider aging of plant. This model is only applicable for a particular set of soil conditions. A long-term study is required in this field to further quantify parameters for improving calibration and modeling performance.
Practical implications
Following are the practical implication: consideration of vegetation properties into engineered design of green infrastructure (slopes in this case) and selection of vegetation with appropriate characteristics in design for enhancement of stability of green infrastructure.
Originality/value
Contents of this paper are original, and they have not been submitted to any other journal.
Details
Keywords
Kumari Amrita, Chandra Prakash Garg and Saumya Singh
The contribution of women toward entrepreneurial activities has gained significant attention in recent years because of economic and social concerns, government support and…
Abstract
Purpose
The contribution of women toward entrepreneurial activities has gained significant attention in recent years because of economic and social concerns, government support and initiatives and increased education and awareness. Women’s entrepreneurial activity has increased and women-owned businesses can today be found in every sector of the economy, irrespective of region. In India, government bodies such as the Ministry of Micro, Small and Medium Enterprises (MSMEs) and several other organizations (private and NGOs) have adopted considerable measures to promote women entrepreneurship (WE). To improve WE, the critical factors of WE adoption need to be identified and evaluated. The purpose of this paper is to identify, prioritize and evaluate the critical success factors of WE adoption in Indian MSMEs.
Design/methodology/approach
This paper proposes a methodology based on fuzzy analytical hierarchal process to prioritize the critical success factors of WE adoption. A numerical analysis of Indian MSMEs is presented to demonstrate the use of the proposed method. This proposed method considered fuzzy framework, which can handle impreciseness and uncertainty. Sensitivity analysis is also performed to test the robustness of the proposed model.
Findings
Potential critical success factors are identified from relevant literature and validated by industry experts. This research finalize the critical success factors of WE adoption in Indian MSMEs under seven dimensions, so prioritization of identified critical success factors can be developed and insights relationship of factors would be explored. The results of the study found that individual, management and government dimensions take paramount importance while women aim to become entrepreneurs in Indian MSMEs.
Research limitations/implications
This study is limited to identifying evaluation factors; other factors have not been identified and categorized. Evaluation is one by experts in this area so it is natural that views of decision-makers may be subjective and vary with regard to industry-type, priorities, resources, etc.
Practical implications
This study will help industry to identify, evaluate and prioritize factors for successful implementation of women entrepreneurship. MSMEs could device these factors by applying the outcome of the study in their decisions with higher priority to implement women entrepreneurship culture.
Originality/value
Potential factors are identified from relevant literature and validated by industry experts. Indian MSMEs could device these factors by applying the outcome of the study in their decisions with higher priority to adopt women entrepreneurship.
Details
Keywords
Shubham Garg, Karam Pal Narwal and Sanjeev Kumar
In the recent few decades, there has been a rampant increase in the demand of sustainable food products around the world because of high cognizance of consumers toward environment…
Abstract
Purpose
In the recent few decades, there has been a rampant increase in the demand of sustainable food products around the world because of high cognizance of consumers toward environment and health. Asian countries, especially India and China, are also expecting a tremendous boost in the domestic demand for organic food products in the upcoming few years. Therefore, it becomes pertinent to explore the factors affecting the purchase intention behavior of organic food items, especially in emerging economies, i.e. India. Hence, the paper aims to explore the factors driving the purchase decision of organic consumers by collecting data set from 603 organic food item consumers in India.
Design/methodology/approach
The study has applied advanced statistical tools, i.e. structural equation modeling, Harman’s single factor test and other statistical measures, to analyze the collected research data.
Findings
The results posit that consumers’ purchase intention has a favorable impact on health aspects; trustworthiness; social innovativeness; functional value; subjective norms and organic product knowledge. Moreover, the result explicates that health consciousness and trustworthiness are vital predictors of organic food purchase intention.
Practical implications
The findings may assist the producers, processors, marketers, policymakers and regulators in devising appropriate policies and strategies for comprehending the complex phenomenon of organic consumers’ purchase behavior.
Originality/value
To the best of the authors’ knowledge, this is the first study to explore the drivers of purchase intention of organic food items by collecting data from well-defined consumers of organic food items in India.
Details
Keywords
Donald C. Hambrick and Craig Crossland
Despite widespread interest in “behavioral strategy,” it is not clear what this term, or its associated academic subfield, is all about. Unless a critical mass of scholars can…
Abstract
Despite widespread interest in “behavioral strategy,” it is not clear what this term, or its associated academic subfield, is all about. Unless a critical mass of scholars can agree on the meaning of behavioral strategy, and professionally identify with it, this embryonic community may face a marginal existence. We describe three alternative conceptions for the academic subfield of behavioral strategy, along with assessments of the pros and cons of each. The “small tent” version amounts to a direct transposition of the logic of behavioral economics to the field of strategic management, specifically in the style of behavioral decision research. The “midsize tent” view is that behavioral strategy is a commitment to understanding the psychology of strategists. And the “large tent’ view includes consideration of any and all psychological, sociological, and political factors that influence strategic outcomes. We conclude that the midsize tent represents the best path forward, not too narrow and not too broad, allowing rich scope but with coherence. The large tent conception of behavioral strategy, however, is not out of the question and warrants serious consideration.
Details
Keywords
Yujia Liu, Changyong Liang, Jian Wu, Hemant Jain and Dongxiao Gu
Complex cost structures and multiple conflicting objectives make selecting an appropriate cloud service difficult. The purpose of this study is to propose a novel group consensus…
Abstract
Purpose
Complex cost structures and multiple conflicting objectives make selecting an appropriate cloud service difficult. The purpose of this study is to propose a novel group consensus decision making method for cloud services selection with knowledge deficit by trust functions.
Design/methodology/approach
This article proposes a knowledge deficit-based multi-criteria group decision-making (MCGDM) method for cloud-service selection based on trust functions. Firstly, the concept of trust functions and a ranking method is developed to express the decision-making opinions. Secondly, a novel 3D normalized trust degree (NTD) is defined to measure the consensus levels. Thirdly, a knowledge deficit-based interactive consensus model is proposed for the inconsistent experts to modify their decision opinions. Finally, a real case study has been carried out to illustrate the framework and compare it with other methods.
Findings
The proposed method is practical and effective which is verified by the real case study. Knowledge deficit is an important concept in cloud service selection which is verified by the comparison of the proposed recommended mechanism based on KDD with the conventional recommended mechanism based on average value. A 3D NTD which considers three values (trust, not trust and knowledge deficit) is defined to measure the consensus levels. A knowledge deficit-based interactive consensus model is proposed to help decision-makers reach group consensus. The proposed group consensus model enables the inconsistent decision-makers to accept the revised opinions of those with less knowledge deficit, rather than accepting the recommended opinions averagely.
Originality/value
The proposed a knowledge deficit-based MCGDM cloud service selection method considers group consensus in cloud service selection. The concept of knowledge deficit is considered in modeling the group consensus measuring and reaching method.
Details
Keywords
Harsha Vardhan, Sanandam Bordoloi, Akhil Garg, Ankit Garg and Sreedeep S.
The purpose of this study is to measure the effects of density, moisture, fiber content on unconfined compressive strength (UCS) of soil by formulating the models based on…
Abstract
Purpose
The purpose of this study is to measure the effects of density, moisture, fiber content on unconfined compressive strength (UCS) of soil by formulating the models based on evolutionary approach and artificial neural networks (ANN).
Design/methodology/approach
The present work proposes evolutionary approach of multi-gene genetic programming (MGGP) to formulate the functional relationships between UCS of reinforced soil and four inputs (soil moisture, soil density, fiber content and unreinforced soil strength) of the silty sand. The hidden non-linear relationships between UCS of reinforced soil and the four inputs are determined by sensitivity and parametric analysis of the MGGP model.
Findings
The performance of MGGP is compared to those of ANN and the statistical analysis indicates that the MGGP model is the best and is able to generalize the UCS of reinforced soil satisfactorily beyond the given input range.
Research limitations/implications
The explicit MGGP model will be useful to provide optimum input values for design and analysis of various geotechnical infrastructures. In addition, utilization of Water hyacinth reinforced fiber reinforced soil will minimize negative impact of this species on environment and may generate rural employment.
Originality/value
This work is first of its kind in application and development of explicit holistic model for evaluating the compressive strength of heterogeneous soil blinded with fiber content. This includes the experimental and cross-validation for testing robustness of the model.
Details
Keywords
Shubham Garg, Sangeeta Mittal and Aman Garg
The Indian government is grappling in generating sufficient revenue resources through taxation to meet their expenditure on public goods and services. Therefore, the government…
Abstract
Purpose
The Indian government is grappling in generating sufficient revenue resources through taxation to meet their expenditure on public goods and services. Therefore, the government authorities must possess adequate information on factors affecting the taxation revenue of the country to craft and execute policies effectively. Hence, this study endeavors to explore the determinants of tax revenue by incorporating conventional, economic policy and institutional factors.
Design/methodology/approach
The study employed the Auto Regressive Distributed Lag (ARDL) modeling by using the data set from 1991 to 2022 according to the availability of the data.
Findings
The findings illustrate that trade openness, life expectancy, value added by the manufacturing sector and per capita GDP (Gross domestic Product) positively affect the tax efforts of the government in the conventional determinants. Similarly, in economic policy factors, the financial deepening also exhibits a favorable effect. Conversely, the inflation rate positively boosts the tax efforts in the short run, but it ultimately erodes the tax effort of the government in the long run. In the institutional factors, the official development assistance also illustrates a positive effect.
Practical implications
The findings assert that the Indian government should devise better macro-economic and foreign trade policies with expediting the economic restructuring and bolstering their ability to manage and utilize the foreign aid assistance to boost the tax revenue of the country.
Originality/value
To the authors’ knowledge, this is the first study to incorporate these factors in the Indian context.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2024-0314
Details
Keywords
Karin Sanders, Rebecca Hewett and Huadong Yang
Human resource (HR) process research emerged as a response to questions about how (bundles of) HR practices related to organizational outcomes. The goal of HR process research is…
Abstract
Human resource (HR) process research emerged as a response to questions about how (bundles of) HR practices related to organizational outcomes. The goal of HR process research is to explain variability in employee and organization outcomes by focusing on how HR practices are intended (adopted) by senior managers, the way that these HR practices are implemented and communicated by line managers, and how employees perceive, understand, and attribute these HR practices. In the first part of this chapter, we present a review of 20 years of HR process research from the start, to how it developed, and is now maturing. Within the body of HR process research, several different research theoretical streams have emerged, which are largely studied in isolation without benefiting from each other. Therefore, in the second part of this chapter, we draw on previous work to propose a staged process model in which we integrate the different research streams of HR process research, recognizing contingencies in the model. This leads us to an agenda for future research and practical implications in the final part of the chapter.
Details
Keywords
Sanjeev Yadav, Dixit Garg and Sunil Luthra
Performance measurement (PM) of any supply chain is prerequisite for improving its competitiveness and sustainability. This paper develops a framework for supply chain performance…
Abstract
Purpose
Performance measurement (PM) of any supply chain is prerequisite for improving its competitiveness and sustainability. This paper develops a framework for supply chain performance measurement (SCPM) for agriculture supply chain (ASC) based on internet of things (IoT). Moreover, this article explains the role of IoT in data collection and communication (SC visibility) based on the supply chain operation reference (SCOR) model.
Design/methodology/approach
This research identifies various key performance indicators (KPIs) and also their role in SCPM for improving its sustainability by using SCOR. Further, Shannon entropy is utilized for weighing the basic processes of SCPM and by using weights, fuzzy TOPSIS is applied for ranking of identified KPIs at metrics level 2 (deeper level).
Findings
“Flexibility” and “Responsiveness” have been reported as two most important KPIs in IoT based SCPM framework for ASC towards achieving sustainability.
Research limitations/implications
In this research, metrics are explained only at SCOR level 2. But, this research will guide the managers and practitioners of various organizations to set their benchmark for comparing their performance at different levels of business processes. Further, this paper has managerial implications to develop an effective system for PM of IoT based data-driven ASC.
Originality/value
By using IoT based data driven system, this article fills the gap between SCPM by measuring different SC strategies in their performance measurable form of reliable, responsive and asset management etc.