Noura Yassine and Sanjay Kumar Singh
The purpose of this paper is to investigate a supply chain consisting of a producer and multiple suppliers of a type of component needed for the production of a certain product…
Abstract
Purpose
The purpose of this paper is to investigate a supply chain consisting of a producer and multiple suppliers of a type of component needed for the production of a certain product. The effects of carbon emission taxes, quality of components and human inspection errors as well as the collaboration among the supply chain members are considered.
Design/methodology/approach
A mathematical model is formulated for a non-collaborative supply chain, and the optimal policy is shown to be the solution of a constraint optimization problem. The mathematical model is modified to the case of a collaborative supply chain and to account for inspection errors. Algorithms are provided, and a numerical example is given to illustrate the determination of the optimal policy.
Findings
This study offers a new conceptual and analytical model that analyzes the production problem from a supply chain perspective. Human resource management practices and environmental aspects were incorporated into the model to reduce risk, optimally select the suppliers and properly maximize profit by accounting for human inspection error as well carbon emission taxes. Algorithms describing the determination of the optimal policy are provided.
Practical implications
This study provides practical results that can be useful to researchers and managers aiming at designing sustainable supply chains that incorporate economic, environmental and human factors.
Originality/value
This study can be useful to researchers and managers aiming for designing sustainable supply chains that incorporate economic and human factors.
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Anuj Aggarwal, Sparsh Agarwal, Vedant Jaiswal and Poonam Sethi
Introduction: Historically, the corporate governance (CG) framework was designed primarily to safeguard the economic interests of shareholders, as a result of political and legal…
Abstract
Introduction: Historically, the corporate governance (CG) framework was designed primarily to safeguard the economic interests of shareholders, as a result of political and legal interventions, developing into an effective instrument for stakeholders and society in general.
Purpose: The core objectives of the study include: identifying journals/publications responsible for publishing CG studies in India, key CG issues covered by CG researchers, the amount of high-impact CG literature across different time periods, sectors/industries covered by CG researchers and different research instruments (quantitative or qualitative) used in CG studies in India.
Design/methodology: The chapter used a sample of 130 corporate governance studies that fulfil the selection criteria, drawn from the repository of over 100 reputed journals that are either recognised by the Australian Business Deans Council (ABDC) or indexed by SCOPUS. A systematic literature review has been carried out pertaining to CG issues in India, based on various statistical tools, data, industries, research outlets & citations, etc.
Findings: The results show an overwhelming number of studies have assessed the relationship between CG variables and firm performance, which could be measured through a variety of performance metrics such as ROA and ROI. Apart from empirical analysis, many conceptual studies use repetitive basic statistical tools like descriptive statistics or regression analysis. The chapter offers insights into current achievements and future development.
Originality/value: This bibliometric study is a useful guide for policymakers, corporate leaders, research organisations and management faculty to draw insights from work produced by eminent researchers in GC in India.
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Bhanu Prakash Saripalli, Gagan Singh and Sonika Singh
Estimation of solar cell parameters, mathematical modeling and the actual performance analysis of photovoltaic (PV) cells at various ecological conditions are very important in…
Abstract
Purpose
Estimation of solar cell parameters, mathematical modeling and the actual performance analysis of photovoltaic (PV) cells at various ecological conditions are very important in the design and analysis of maximum power point trackers and power converters. This study aims to propose the analysis and modeling of a simplified three-diode model based on the manufacturer’s performance data.
Design/methodology/approach
A novel technique is presented to evaluate the PV cell constraints and simplify the existing equation using analytical and iterative methods. To examine the current equation, this study focuses on three crucial operational points: open circuit, short circuit and maximum operating points. The number of parameters needed to estimate these built-in models is decreased from nine to five by an effective iteration method, considerably reducing computational requirements.
Findings
The proposed model, in contrast to the previous complex nine-parameter three-diode model, simplifies the modeling and analysis process by requiring only five parameters. To ensure the reliability and accuracy of this proposed model, its results were carefully compared with datasheet values under standard test conditions (STC). This model was implemented using MATLAB/Simulink and validated using a polycrystalline solar cell under STC conditions.
Originality/value
The proposed three-diode model clearly outperforms the earlier existing two-diode model in terms of accuracy and performance, especially in lower irradiance settings, according to the results and comparison analysis.
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Phong Ba Le and Sy Van Ha
Given the important role of knowledge resource for firms to pursuit innovation, this paper aims to investigate the influence of knowledge-based human resource management (HRM…
Abstract
Purpose
Given the important role of knowledge resource for firms to pursuit innovation, this paper aims to investigate the influence of knowledge-based human resource management (HRM) practices on innovation performance through the mediating roles of tacit and explicit knowledge sharing (KS). This study also explores the potential moderating role of perceived organizational supports (POSs) in fostering the KS–innovation relationship of firms in the developing and emerging markets.
Design/methodology/approach
The relationship among the latent variables is empirically examined through 289 employees from 118 manufacturing and service firms. Confirmatory factor analysis and structural equation modeling were performed to validate the constructs and estimate the regression coefficients of relationships.
Findings
The empirical findings of this study support the mediating role of KS behaviors in the relationship between knowledge-based HRM practices and innovation performance. It highlights the important role of POSs in stimulating the influence of KS behaviors on innovation performance.
Research limitations/implications
Future research should investigate the impact of knowledge-based HRM practices on specific forms of innovation via the mediating effects of knowledge management processes to bring better understanding on the importance of knowledge resources in pursuing innovation competence.
Originality/value
The paper significantly contributes to enhancing understanding of the antecedent role of knowledge-based HRM practices in fostering KS behaviors and innovation performance under the moderating effects of POSs. Generally, it advances the body of comprehension of knowledge-based resources and innovation theory.
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Ashulekha Gupta and Rajiv Kumar
Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types…
Abstract
Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types of employment have risen significantly, there has been significant growth in adopting AI technology in enterprises. Despite the anticipated benefits of AI adoption, many businesses are still struggling to make progress. This research article focuses on the influence of elements affecting the acceptance procedure of AI in organisations.
Design/Methodology/Approach: To achieve this objective, propose a hierarchical paradigm for the same by developing an Interpretive Structural Modelling (ISM). This paper reveals the barriers obstructing AI adoption in organisations and reflects the contextual association and interaction amongst those barriers by emerging a categorised model using the ISM approach. In the next step, cross-impact matrix multiplication is applied for classification analysis to find dependent, independent and linkages.
Findings: As India is now focusing on the implementation of AI adoption, therefore, it is essential to identify these barriers to AI to conceptualise it systematically. These findings can play a significant role in identifying essential points that affect AI adoption in organisations. Results show that low regulations are the most critical factor and functional as the root cause and further lack of IT infrastructure is the barrier. These two factors require the most attention by the government of India to improve AI adoption.
Implications: This study may be utilised by organisations, academic institutions, Universities, and research scholars to fill the academic gap and faster implementation of AI.
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Prateek Kumar Tripathi, Chandra Kant Singh, Rakesh Singh and Arun Kumar Deshmukh
In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this…
Abstract
Purpose
In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.
Design/methodology/approach
The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.
Findings
Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.
Practical implications
As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.
Originality/value
Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.
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Due to the vital role of innovation for firms to respond to the change and achieve competitive advantage, the purpose of this study is to investigate the influence of…
Abstract
Purpose
Due to the vital role of innovation for firms to respond to the change and achieve competitive advantage, the purpose of this study is to investigate the influence of knowledge-oriented leadership (KOL) on innovation performance (IP) via the mediating role of knowledge sharing (KS). This study also clarifies the KS-IP relationship by exploring the moderating role of market turbulence.
Design/methodology/approach
Analysis of moment structures and structural equation modeling are applied to examine the relationship among the latent factors in the proposed research model using data collected from 281 participants in 112 manufacturing and service firms in Vietnam.
Findings
The findings revealed that KOL serves as a key precursor to foster IP, directly or indirectly, through knowledge-oriented leaders’ effect on tacit and explicit KS behaviors. In addition, the paper highlights the moderating role of market turbulence in strengthening the impact of KS activities on IP.
Research limitations/implications
By highlighting the important role KOL practice for stimulating KS behaviors, this paper provides a valuable understanding and novel approach for firms to improve IP. The research findings support the idea that market turbulence significantly contributes to increasing the effects of KS behaviors on IP.
Originality/value
This study contributes to bridging research gaps in the literature and advances the insights of how KOL directly and indirectly fosters IP via mediating roles of tacit and explicit KS processes under the effects of market turbulence.