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1 – 10 of over 1000Ravichandran Joghee and Reesa Varghese
The purpose of this article is to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the analysis of variance (ANOVA…
Abstract
Purpose
The purpose of this article is to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the analysis of variance (ANOVA) application after the preliminary test on the model specification.
Design/methodology/approach
A new approach is proposed to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the ANOVA application. First, we determine this relationship from the general perspective of Six Sigma methodology under the normality assumption. Then, the approach is extended to a balanced two-stage nested design with a random effects model in which a preliminary test is used to fix the main test statistic.
Findings
The features of mean-shifted and inflated (but centred) processes with the same specification limits from the perspective of Six Sigma are studied. The shift and inflation coefficients are derived for the two-stage balanced ANOVA model. We obtained good predictions for the process shift, given the inflation coefficient, which has been demonstrated using numerical results and applied to case studies. It is understood that the proposed method may be used as a tool to obtain an efficient variance estimator under mean shift.
Research limitations/implications
In this work, as a new research approach, we studied the link between mean shift and inflation coefficients when the underlying null hypothesis is rejected in the ANOVA. Derivations for these coefficients are presented. The results when the null hypothesis is accepted are also studied. This needs the help of preliminary tests to decide on the model assumptions, and hence the researchers are expected to be familiar with the application of preliminary tests.
Practical implications
After studying the proposed approach with extensive numerical results, we have provided two practical examples that demonstrate the significance of the approach for real-time practitioners. The practitioners are expected to take additional care before deciding on the model assumptions by applying preliminary tests.
Originality/value
The proposed approach is original in the sense that there have been no similar approaches existing in the literature that combine Six Sigma and preliminary tests in ANOVA applications.
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Subhamoy Chatterjee and R.P. Mohanty
Interest rate derivatives (IRDs) are the essential components of financial risk management and are used across various industry sectors. The objective is to analyze the…
Abstract
Purpose
Interest rate derivatives (IRDs) are the essential components of financial risk management and are used across various industry sectors. The objective is to analyze the differences in approach to managing interest rate risks between the Indian corporates that execute IRDs and the ones that do not.
Design/methodology/approach
Interest rate fluctuations require Indian corporates to hedge their exposures in foreign currency interest rates. This is all the more true for mid-sized corporates because of their balance sheet exposures. Additionally, they may not have the resources to formulate risk management policies. This paper analyzes data collected from financial statements of a diverse set of companies that use IRD and helps in formulating such a strategy.
Findings
The results indicate significant differences for some of the parameters like information asymmetry and agency cost between users and non-users of IRDs. The study further suggests causality between users of derivatives and parameters like size, growth and debt.
Research limitations/implications
The study compares users and non-users of IRDs, thereby identifying factors unique to users of IRDs. It also studies causality relations which explain the motivation to do IRDs. Thus, it enables risk managers to use this as a reference point to decide on their strategies.
Originality/value
While there are multiple studies across geographies and sectors including commercial banks in India on the usage of interest rate swaps, this study focuses on Indian mid-tier corporates. Furthermore, the study distinguishes between users and non-users based on financial parameters, which in turn would provide a framework for decision-hedging strategies.
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Mayuri Srivastava, Shradha Shivani and Sraboni Dutta
The purpose of this empirical study is to enable a better understanding of the construct sustainability-oriented entrepreneurial intentions (SEI) and thereby promote sustainable…
Abstract
Purpose
The purpose of this empirical study is to enable a better understanding of the construct sustainability-oriented entrepreneurial intentions (SEI) and thereby promote sustainable entrepreneurship. It aims to examine the significance of work values (extrinsic rewards, intrinsic rewards and job security) as antecedents of SEI and to test the mediating effect of three constructs derived from the theory of planned behaviour – attitude towards sustainability, perceived entrepreneurial desirability and perceived entrepreneurial feasibility on the relationships between work values and SEI.
Design/methodology/approach
Confirmatory factor analysis and exploratory factor analysis were performed using analysis of moment structures v27 and statistical package for social science v28 on data obtained from the survey of young individuals of India. The respondents were students enrolled in higher education programmes.
Findings
All the identified antecedents (extrinsic rewards, intrinsic rewards, job security and theory of planned behaviour constructs) were found to be statistically significant. The partial mediating effect of the theory of planned behaviour constructs was also reported.
Originality/value
This empirical work leads to the theoretical advancement of the emerging construct, SEI, by presenting evidence of the significant individual-level antecedents of the construct. The results lead to recommendations for policymakers and educators to design strategies to strengthen SEI, thereby expanding the adoption of sustainable entrepreneurship.
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Harold Delfín Angulo Bustinza, Bruno de Souza and Roberto De la Cruz Rojas
Aamir Rashid, Neelam Baloch, Rizwana Rasheed and Abdul Hafaz Ngah
This study aims to examine the role of big data analytics (BDA) powered by artificial intelligence (AI) in improving sustainable performance (SP) through green supply chain…
Abstract
Purpose
This study aims to examine the role of big data analytics (BDA) powered by artificial intelligence (AI) in improving sustainable performance (SP) through green supply chain collaboration (GSCC), sustainable manufacturing (SM) and environmental process integration (EPI).
Design/methodology/approach
Data was collected from 249 supply chain professionals working at various manufacturing firms, and hypotheses were tested through a quantitative method using PLS-SEM with the help of SmartPLS version 4 to validate the measurement model.
Findings
This study identified that BDA-AI significantly and positively affects GSCC, SM and EPI. Similarly, the results showed that GSCC significantly and positively affects SP. At the same time, SM and EPI have an insignificant effect on SP. The GSCC found a significant relationship between BDA-AI and SP for mediation. However, SM and environmental performance integration did not mediate the relationship between BDA and AI and SP.
Originality/value
This research evaluated a second-order model and tested SP in conjunction with the dynamic capability theory in the manufacturing industry of Pakistan. Therefore, this research could be beneficial for researchers, manufacturers and policymakers to attain sustainable goals by implementing the BDA-AI in the supply chain.
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Leema Rose Victor, Mariadoss Siluvaimuthu, Hesil Jerda George and Satyanarayana Parayitam
The present study aims to investigate the relationship between institutional influence and performance, mediated through transformational leadership (TL) and moderated by…
Abstract
Purpose
The present study aims to investigate the relationship between institutional influence and performance, mediated through transformational leadership (TL) and moderated by barriers, situational factors, communication and implementation.
Design/methodology/approach
Using a structured survey instrument, data were collected from 370 faculty members from 31 higher educational institutions in southern India. After checking the psychometric properties of the instrument, the authors used Hayes’s PROCESS to test the direct hypotheses and three-way interactions.
Findings
The results revealed that TL mediated the relationship between institutional influence and performance. Further, the findings supported the three-way interactions between (1) institutional influence, barriers and communication positively affecting TL; and (2) TL, situational factors and implementation affecting the performance of faculty members.
Research limitations/implications
This study underscores the importance of TL for the smooth functioning of higher educational institutions and achieving superior performance, especially in the new normal context after the global pandemic.
Practical implications
This study makes several significant recommendations to administrators in higher educational institutions, in addition to contributing to the vast literature on TL. The study suggests that administrators must invest resources in developing TL skills so that employees reach their fullest potential and contribute to achieving organizational goals. In addition, leaders in organizations need to exercise a transformational style to combat the new normal post-pandemic academic environment.
Originality/value
This study provides new insights into the importance of TL style and institutional influence to enhance performance. To the best of our knowledge, the conceptual model developed and tested the first of its kind in India, significantly contributing to theory and practice.
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Subhodeep Mukherjee, Ramji Nagariya, K. Mathiyazhagan, Manish Mohan Baral, M.R. Pavithra and Andrea Appolloni
Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial…
Abstract
Purpose
Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.
Design/methodology/approach
In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.
Findings
Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.
Practical implications
The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.
Originality/value
Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.
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Dhanraj P. Tambuskar, Prashant Jain and Vaibhav S. Narwane
With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big…
Abstract
Purpose
With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).
Design/methodology/approach
The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).
Findings
A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.
Research limitations/implications
This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.
Practical implications
This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.
Social implications
The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.
Originality/value
This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.
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Supatmi Supatmi, Christa Kurnia Alethea, Yeterina Widi Nugrahanti and MI Mitha Dwi Restuti
This study aims to examine the effect of family ownership on audit fees and whether political connections moderate the causal relationship. Indonesia, as emerging countries…
Abstract
Purpose
This study aims to examine the effect of family ownership on audit fees and whether political connections moderate the causal relationship. Indonesia, as emerging countries, arguably offers appropriate research setting for this research because most Indonesian firms are family owned and exhibit weak investor protection. The authors predict that family ownership positively affects audit fees, and political connections strengthen this influence.
Design/methodology/approach
This study uses 98 listed manufacturing firms on Indonesia Stock Exchange (IDX) in 2018–2020, resulting in 279 firm-year observations. Panel data regression used to test the hypothesis. Family ownership is divided into direct and indirect ownership while audit fees are measured by the natural logarithm of audit fees paid by the firms.
Findings
The results show that the greater total and direct family ownerships imply lower audit fees, while indirect family ownership does not affect audit fees. The finding is contrary to the alleged hypothesis. Further, political connections only strengthen direct family ownership's negative impact on audit fees.
Originality/value
This study's findings support the alignment effect hypothesis arguing that controlling shareholders, in this case, families, align their interests with non-controlling shareholders. These findings provide a different perspective from various empirical studies conducted in Asian countries where the majority of companies are also controlled.
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Alan J. McNamara, Sara Shirowzhan and Samad M.E. Sepasgozar
This paper aims to identify the relevant contributing constructs of readiness for the implementation of intelligent contracts (iContracts) in the construction industry. This study…
Abstract
Purpose
This paper aims to identify the relevant contributing constructs of readiness for the implementation of intelligent contracts (iContracts) in the construction industry. This study investigates the relationship between the personality dimensions of technology readiness index (TRI) and the system specific factors of technology acceptance model (TAM) within the context of iContracts.
Design/methodology/approach
Drawing insights from the extant literature and the author's previous qualitative investigations into iContract readiness constructs, a quantitative approach is used to operationalise the constructs by offering relevant statements to be measured and validated through a multiple-item scale against the users intent to accept the future iContract technology.
Findings
This study confirms and validates the relationship of the proposed iContract readiness index (iCRI) statements against the established TAM factors by offering 18 new constructs influencing technology readiness of the iContract technology. This study proves 9 of the 12 hypotheses highlighting key factors to be addressed for the successful development of the iContract technology.
Practical implications
This paper contributes to the body of knowledge by proposing a novel iCRI that informs an iContract technology readiness acceptance model (iCTRAM) for a trending technology. The iCTRAM can guide developers in producing an appropriate iContract solution and assess the readiness of users and organisations for the successful adoption of the iContract concept.
Originality/value
This study offers a unique theoretical framework, in an embryonic field, for predicting the success of iContract implementation within construction organisations. This study combines the established studies of TRI and TAM in producing a predictive iContract readiness assessment tool.
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