Deepika Pandoi, Sanjaya Singh Gaur and Anup Kumar Gupta
Plagiarism is an epidemic for scholars that needs to be managed. Penalties do not seem to be able to stop people from indulging in it. Manipulation of emotions and values may help…
Abstract
Purpose
Plagiarism is an epidemic for scholars that needs to be managed. Penalties do not seem to be able to stop people from indulging in it. Manipulation of emotions and values may help in discouraging people from plagiarism. Therefore, the purpose of this paper is to understand the association between felt emotion and plagiarism outcome behaviours. Another objective of the study is to see the role of virtues in discouraging people from plagiarism.
Design/methodology/approach
A scenario-based quasi-experimental method is used to collect the data. Graduate students from various Indian universities were invited for the experiment. The partial least square based structural equation modelling is used to test the measurement as well as path model.
Findings
The authors found that manipulated shame resulted in feelings of both international and external shame. When individuals feel internal shame, they avoid and discontinue plagiarism. They also try to repair the damage that they cause by plagiarism. However, feeling of external shame only encourages individuals to discontinue plagiarism behaviour. Virtues such as influence, competitiveness and equality weaken the relationship between internal shame and plagiarism-related outcome behaviour. At the same time, these virtues do not affect the relationship between external shame and outcome behaviours.
Practical implications
This study has important implications for the institutions of higher education. The study suggests that universities should provoke the emotion of shame through various communications to students to control the act of plagiarism by their students.
Originality/value
No study seems to have examined if the manipulation of emotions and values can help reduce the problem of plagiarism. This is an attempt towards bridging this important gap in literature. Therefore, findings of this study are of great value to scholars and content developers.
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Atul Kumar Sahu, Anup Kumar, Anoop Kumar Sahu and Nitin Kumar Sahu
Today, industrial revolutions demands advanced technologies, means, mediums, tactics and so forth for optimizing their operating behavior and opportunities. It is probed that the…
Abstract
Purpose
Today, industrial revolutions demands advanced technologies, means, mediums, tactics and so forth for optimizing their operating behavior and opportunities. It is probed that the effectual results can be seized into system by not only developing advance means and technologies, but also capably adapting these developed technologies, their user interface and their utilization at optimum levels. Today, industrial resources need perfect synchronization and optimization for getting elevated results. Accordingly, present study is furnished with the purpose to expose quality-driven insights to march toward excellence by optimizing existing resources by the industrial organizations. The present study evaluates quality attributes of mechanical machineries for seizing performance opportunities and maintaining competitiveness via synchronizing and reconfiguring firm's resources under quality management system.
Design/methodology/approach
In the present study, Kano’s integrated approach is implemented for supporting decision rational concerning industrial assets. The integrative Kano–analytic hierarchy process (AHP) approach is used to reflect the relative importance of quality attributes. Kano and AHP tactics are integrated to define global relative weight and their computational medium is adapted along with ratio analysis, reference point theory and TOPSIS technique for understanding robust decision. The study described an interesting idea for underpinning quality attributes for benchmarking system substitutes. A machine tool selection case is discussed to disclose the significant aspect of decision-making and its virtual qualities.
Findings
The decision executives can realize massive benefits by streaming quality data, advanced information, technological advancements, optimum analysis and by identifying quality measures and disruptions for gaining performance deeds. The study determined quality measures for benchmarking machine tool substitute for industrial applications. Momentous machine alternatives are evaluated by means of technical structure, dominance theory and comparative analysis for supporting decision-making of industrial assets based on optimization and synchronization.
Research limitations/implications
The study linked financial, managerial and production resources under sole platform to present a technical structure that may assist in improving the performance of the manufacturing firms. The study provides a decision support mechanism to assist in reviewing the momentous resources to imitate a higher level of productive strength toward the manufacturing firms. The study endeavors its importance toward optimizing resources, which is an evident requirement in industries as the same not only saves money, escalates production, improves profit margins and so forth, but also gratifies the consumption of scarce natural resources.
Originality/value
The study stressed that advance information can be sought from system characteristics in the form of quality measures and attributes, which can be molded for gaining elevated outcomes from existing system characteristics. The same demands decision supports tools and frameworks to utilize data-driven information for benchmarking operations and supply chain activities. The study portrayed an approach for ease of utilizing data-driven information by the decision-makers for demonstrating superior outcomes. The study originally conceptualized multi-attributes appraisement framework associated with subjective cum objective quality measures to evaluate the most significant machine tool choice amongst preferred alternatives.
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Anup Kumar, Santosh Shrivastav, Amit Adlakha and Niraj K. Vishwakarma
The authors develop a methodology to select appropriate sustainable supply chain indicators (SSCIs) to measure Sustainable Development Goals (SDGs) in the global supply chain.
Abstract
Purpose
The authors develop a methodology to select appropriate sustainable supply chain indicators (SSCIs) to measure Sustainable Development Goals (SDGs) in the global supply chain.
Design/methodology/approach
SSCIs are identified by reviewing the extant literature and topic modeling. Further, they are evaluated based on existing SDGs and ranked using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Notably, the evaluation of indicators is a multi-criteria decision-making (MCDM) process within a fuzzy environment. The methodology has been explained using a case study from the automobile industry.
Findings
The case study identifies appropriate SSCIs and differentiates them among peer suppliers for gaining a competitive advantage. The results reveal that top-ranked sustainability indicators include the management of natural resources, energy, greenhouse gas (GHG) emissions and social investment.
Practical implications
The study outcome will enable suppliers, specialists and decision makers to understand the criteria that improve supply chain sustainability in the automobile industry. The analysis provides a comprehensive understanding of the competitive package of indicators for gaining strategic advantage. This proactive sustainability indicator selection promotes and enhances sustainability reporting while fulfilling regulatory requirements and increasing collaboration potential with trustworthy downstream partners. This study sets the stage for further research in SSCIs’ competitive strategy in the automobile industry along with its supply chains.
Originality/value
This study is unique as it provides a framework for determining relevant SSCIs, which can be distinguished from peer suppliers, while also matching economic, environmental and social metrics to achieve a competitive advantage.
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Anup Kumar, Sudhanshu Joshi, Manu Sharma and Neeraj Vishvakarma
This study proposes a digital humanitarianism dynamic capability (DHDC) paradigm that explores the direct effects of DHDC on disaster risk reduction (DRR) and the mediating…
Abstract
Purpose
This study proposes a digital humanitarianism dynamic capability (DHDC) paradigm that explores the direct effects of DHDC on disaster risk reduction (DRR) and the mediating effects of process-oriented dynamic capabilities (PODC) on the relationship between DHDC and DRR.
Design/methodology/approach
To validate the proposed model, the authors used an offline survey to gather data from 260 district magistrates in India managing the COVID-19 pandemic.
Findings
The results affirm the importance of the DHDC system for DRR. The findings depict that the impact of PODC on DRR in the DHDC system is negligible. This study can help policymakers in planning during emergencies.
Research limitations/implications
Technological innovation has reshaped the way humanitarian organizations (HOs) respond to humanitarian crises. These organizations are able to provide immediate aid to affected communities through digital humanitarianism (DH), which involves significant innovations to match the specific needs of people in real-time through online platforms. Despite the growing need for DH, there is still limited know-how regarding how to leverage such technological concepts into disaster management. Moreover, the impact of DH on DRR is rarely examined.
Originality/value
The present study examines the impact of the dynamic capabilities of HOs on DRR by applying the resource-based view (RBV) and dynamic capability theory (DCT).
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Vipin Valiyattoor and Anup Kumar Bhandari
This paper aims to evaluate the performance of basic metals industry in India and analyze its determinants, using data envelopment analysis (DEA) method. It also intends to…
Abstract
Purpose
This paper aims to evaluate the performance of basic metals industry in India and analyze its determinants, using data envelopment analysis (DEA) method. It also intends to compare the results through conventional two-stage and bootstrap-based inferences.
Design/methodology/approach
Considering technical efficiency as a measure of performance, this paper specifically investigates whether the participation of a firm in the global market affects its performance. The conventional two-stage procedure is used to test the export intensity and firm performance nexus. The bootstrap-based algorithms (by Simar and Wilson, 2007) are used to correct the bias and serial correlation issues involved in the conventional approach.
Findings
The result shows a negative relation between export intensity and firm performance while following the conventional procedure. Even after accounting for serial correlation, the relation remains more or less similar to that of conventional analysis. However, a strong negative relation between export intensity and firm performance is not observed in a more reliable inference obtained after correcting for possible bias as well as serial correlation.
Research limitations/implications
This paper is based on cross-sectional analysis, and a more reliable result can be obtained by considering a larger sample and longer period.
Originality/value
This paper shows how the conventional two-stage procedure may result in misleading inferences due to bias in the estimation of efficiency scores and the serial correlation during the second stage inferential analysis. This paper also empirically exemplifies how the double bootstrap DEA procedure can overcome these limitations of the conventional two-stage approach.
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Anup Krishnamurthy and G. Shainesh
The purpose of this paper is to determine the impact of an additional service on existing consumers’ usage of existing services from the same service provider. Research has often…
Abstract
Purpose
The purpose of this paper is to determine the impact of an additional service on existing consumers’ usage of existing services from the same service provider. Research has often focused on marketers’ efforts to sell new offerings to existing customers. However, does the consumption of these new offerings by existing customers affect their usage of the firm’s existing services? This research examines this question in the context of a subscription service.
Design/methodology/approach
This study uses matched consumer- and firm-level data from a leading telecom service provider in India. These data include responses from 230 consumers, as well as details on their usage of existing and additional services. The data are analyzed using three-stage least squares regressions while controlling for consumers’ past usage of the existing services.
Findings
The results indicate that existing consumers’ cross-buying of the new service results in a reduction of their future usage of existing services. Most consumers also managed to maintain their monthly payments constant, even though they had subscribed to the new service. Together, these findings imply that consumers reallocate their budget by reducing their usage of existing services to accommodate the usage of an additional service from the same service provider. Consequently, the revenue of the firm might not always increase when the consumer cross-buys an additional service from the firm.
Originality/value
Marketing research on cross-buying has so far neglected to look at the effects of existing consumers’ adoption of an additional service on existing services of the service provider. This study focused on this gap in knowledge, in the context of subscription services. Using consumers’ perceptions and matched service usage data, the authors extend the literature that tries to understand why cross-buying may not be beneficial to the firm in certain service settings.
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The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed…
Abstract
Purpose
The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed at containing the pandemic. Isolation through social distancing played a key role in achieving this objective. This research study examines the factors affecting the intention of individuals toward social distancing in India.
Design/methodology/approach
A correlation study was conducted on residents from across Indian states (N = 499). Online questionnaires were floated, consisting of health belief model and theory of planned behavior model, with respect to social distancing behavior initially. Finally, structural equation modeling was used to test the hypotheses.
Findings
The results show that perceived susceptibility (PS), facilitating conditions (FC) and subjective norms are the major predictors of attitude toward social distancing, with the effect size of 0.277, 0.132 and 0.551, respectively. The result also confirms that the attitude toward social distancing, perceived usefulness of social distancing and subjective norms significantly predict the Intention of individuals to use social distancing with the effect size of 0.355, 0.197 and 0.385, respectively. The nonsignificant association of PS with social distancing intention (IN) (H1b) is rendering the fact that attitude (AT) mediates the relationship between PS and IN; similarly, the nonsignificant association of FC with IN (H5) renders the fact that AT mediates the relationship between FC and IN.
Practical implications
The results of the study are helpful to policymakers to handle operations management of nudges like social distancing.
Originality/value
The research is one of its kind that explores the behavioral aspects of handling social nudges through FC.
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Kunal Kamal Kumar, Sushanta Kumar Mishra and Pawan Budhwar
The “war for talent” is not limited to developed economies but has become a common feature in emerging economies such as India. From the sociocultural perspective, India…
Abstract
The “war for talent” is not limited to developed economies but has become a common feature in emerging economies such as India. From the sociocultural perspective, India represents one of the oldest cultural heritages with distinct cultural values. The cultural difference may contribute to explain organizational practices toward talent retention. In the present chapter, the authors focus on the institutional, legal, and cultural context and highlight their uniqueness with respect to the Indian context. Within the institutional context, the authors found that prior to liberalization (which happened in 1990s), the Indian business scene was dominated by public firms or a small enclave of private firms. For both types of organization, turnover hardly mattered, and turnover was indeed negligible. Employees saw firms as “employers for life”: in such a context, voluntary turnover was extremely rare. Further, in the early legal context, it was hard for any private firm to “fire” an employee. Therefore, involuntary turnover was close to nil as well. Things began to change post-liberalization when the Indian scene was dominated by an influx of private players. The Indian mind too accepted turnover to be a part of the corporate life. In the present chapter, the authors provide a snapshot of what, why, and how of employee turnover in the Indian context. The authors specifically focus on what motivates employees to remain with the organization or why do they leave the organization. The authors close the chapter with insights relevant to both academicians and practitioners.
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This chapter explores the multifaceted relationship between quantum computing (QC) and sustainability, with a focus on the Quadratic Unconstrained Binary Optimisation (QUBO…
Abstract
This chapter explores the multifaceted relationship between quantum computing (QC) and sustainability, with a focus on the Quadratic Unconstrained Binary Optimisation (QUBO) framework. The manuscript delves into the theoretical underpinnings of QUBO and its formulation as a quantum annealing problem, identifying the quantum principles that facilitate the resolution of such optimisation challenges. It offers a critical analysis of the suitability of QUBO for unconstrained problems and its efficacy in consistently locating the global minimum – a pivotal concern in optimisation tasks. Further, this study provides a nuanced discussion on the intersection of QC and sustainability. It delineates the types of optimisation problems within sustainability initiatives that are amenable to formulation as QUBO problems, while also highlighting sustainability challenges that elude the QUBO framework. It argues for the integration of quantum solutions into business operations, highlighting the potential for QC to play a transformative role in achieving sustainability objectives. The critique of the current hype surrounding QC provides a balanced viewpoint, ensuring a grounded approach to the adoption of quantum technologies in tackling pressing global issues.
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Anup Kumar and Vinit Singh Chauhan
This study examines the relationship between servant leadership and its dimensions on firm performance, with big data playing the role of a mediator.
Abstract
Purpose
This study examines the relationship between servant leadership and its dimensions on firm performance, with big data playing the role of a mediator.
Design/methodology/approach
Survey responses used for analysis in this study have been taken from business managers associated reputed private sector organizations in India. A conceptual model is proposed grounded to the Conservation of Resource Theory (COR). Structural equation modeling has been used to test the proposed model.
Findings
Servant leadership significantly relates to firm performance, whereby Big Data is seen to play the role of a mediator. The results also indicate that none of the dimensions of servant leadership independently affect firm performance.
Originality/value
The study adds to extant research by examining the mediating mechanism of Big Data in servant leadership and firm performance. It also suggests that each dimension of servant leadership gets reflected in overall servant leadership. Here it is important to note that Big Data analytics partially mediate the effectiveness of servant leadership.