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Article
Publication date: 26 February 2020

Gunjan Soni, Surya Prakash, Himanshu Kumar, Surya Prakash Singh, Vipul Jain and Sukhdeep Singh Dhami

The Indian marble and stone industry has got the potential to contribute well to the development of the emerging economy. However, unlike the other Indian industries…

Abstract

Purpose

The Indian marble and stone industry has got the potential to contribute well to the development of the emerging economy. However, unlike the other Indian industries, stone and marble industries are highly underrated sectors, which may become a critical factor for development. This paper analyses the sustainability factors in supply chain management practices.

Design/methodology/approach

A literature review is used to identify the barriers and drivers in sustainable supply chain management practices. Interpretive structural modeling has been used to obtain a hierarchy of barriers and drivers along with driving power and dependence power analysis. Further, MICMAC analysis is used for segregating the barriers and drivers in terms of their impact on sustainability.

Findings

The findings of the work of this research are that the attention of society, government, and commercial banks should be more toward the unorganized condition of stone and marble sector. There should be an increase in the commitment of stakeholders to reduce pollution and install safety, by enforcing more relevant laws and regulations and creating the importance of environmental awareness.

Originality/value

The main contribution of this research is to identify the barriers and drivers of sustainable supply chain management in a stone and marble industry. The paper proposes a sound mathematical model to prioritize the critical factors for responsible production and consumption of resources from sustainability perspectives of stone industry.

Details

Management of Environmental Quality: An International Journal, vol. 31 no. 5
Type: Research Article
ISSN: 1477-7835

Keywords

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Article
Publication date: 1 August 2020

Sanjiv Narula, Surya Prakash, Maheshwar Dwivedy, Vishal Talwar and Surendra Prasad Tiwari

This research aims to outline the key factors responsible for industry 4.0 (I4.0) application in industries and establish a factor stratification model.

Abstract

Purpose

This research aims to outline the key factors responsible for industry 4.0 (I4.0) application in industries and establish a factor stratification model.

Design/methodology/approach

This article identifies the factor pool responsible for I4.0 from the extant literature. It aims to identify the set of key factors for the I4.0 application in the manufacturing industry and validate, classify factor pool using appropriate statistical tools, for example, factor analysis, principal component analysis and item analysis.

Findings

This study would shed light on critical factors and subfactors for implementing I4.0 in manufacturing industries from the factor pool. This study would shed light on critical factors and subfactors for implementing I4.0 in manufacturing industries. Strategy, leadership and culture are found key elements of transformation in the journey of I4.0. Additionally, design and development in the digital twin, virtual testing and simulations were also important factors to consider by manufacturing firms.

Research limitations/implications

The proposed I4.0 factor stratification model will act as a starting point while designing strategy, adopting readiness index for I4.0 and creating a roadmap for I4.0 application in manufacturing. The I4.0 factors identified and validated in this paper will act as a guide for policymakers, researchers, academicians and practitioners working on the implementation of Industry 4.0. This work establishes a solid groundwork for developing an I4.0 maturity model for manufacturing industries.

Originality/value

The existing I4.0 literature is critically examined for creating a factor pool that further presented to experts to ensure sufficient rigor and comprehensiveness, particularly checking the relevance of subfactors for the manufacturing sector. This work is an attempt to identify and validate major I4.0 factors that can impact its mass adoption that is further empirically tested for factor stratification.

Details

Journal of Advances in Management Research, vol. 17 no. 5
Type: Research Article
ISSN: 0972-7981

Keywords

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Article
Publication date: 21 May 2021

Surya Prakash Singh

Abstract

Details

Benchmarking: An International Journal, vol. 28 no. 5
Type: Research Article
ISSN: 1463-5771

Content available

Abstract

Details

Management of Environmental Quality: An International Journal, vol. 29 no. 3
Type: Research Article
ISSN: 1477-7835

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Article
Publication date: 13 May 2021

Surya Prakash, Naga Vamsi Krishna Jasti, F.T.S. Chan, Nilaish, Vijay Prakash Sharma and Lalit Kumar Sharma

The objective of the present study is to identify and analyze a set of critical success factors (CSFs) for ice-cream industry [cold chain management (CCM)] that helps in…

Abstract

Purpose

The objective of the present study is to identify and analyze a set of critical success factors (CSFs) for ice-cream industry [cold chain management (CCM)] that helps in increasing the efficacy, quality, performance and growth of the supply chain organization.

Design/methodology/approach

A questionnaire survey with companies in ice-cream sector and a panel study with experts were conducted to identify and validate CSFs and their associated sub-factors. Eight CSFs identified from the cold chain domain vetted for the ice-cream industry and then prioritized by using one of the most well-known decision-making frameworks, Decision-Making Trial and Evaluation Laboratory. The general verdicts of the modelling and its application to the real-world case have been tested through an ice-cream company supply chain.

Findings

The result shows that the significant CSFs accountable for the growth of the ice-cream industry are the infrastructure and capacity building, consistent product improvement and operational efficiencies of the value chain. Subsequently, it was identified that the use of IT and related technologies and improved processes for operations also play a considerable role in the performance of ice-cream industry.

Practical implications

The study successfully outlines the effective CCM practices for critical issues. The proposed methodology and factor modelling case demonstration might be useful in analyzing the logistic chains of products such as fruits, drugs and meat.

Originality/value

The meritorious identification of critical areas and executing mitigation plans bring notable benefits to the firms such as improved operational efficiencies, improved time to market performance and product innovation, which bring additional benefits to the producers.

Details

Measuring Business Excellence, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1368-3047

Keywords

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Article
Publication date: 8 January 2020

Sonali Shankar, P. Vigneswara Ilavarasan, Sushil Punia and Surya Prakash Singh

Better forecasting always leads to better management and planning of the operations. The container throughput data are complex and often have multiple seasonality. This…

Abstract

Purpose

Better forecasting always leads to better management and planning of the operations. The container throughput data are complex and often have multiple seasonality. This makes it difficult to forecast accurately. The purpose of this paper is to forecast container throughput using deep learning methods and benchmark its performance over other traditional time-series methods.

Design/methodology/approach

In this study, long short-term memory (LSTM) networks are implemented to forecast container throughput. The container throughput data of the Port of Singapore are used for empirical analysis. The forecasting performance of the LSTM model is compared with seven different time-series forecasting methods, namely, autoregressive integrated moving average (ARIMA), simple exponential smoothing, Holt–Winter’s, error-trend-seasonality, trigonometric regressors (TBATS), neural network (NN) and ARIMA + NN. The relative error matrix is used to analyze the performance of the different models with respect to bias, accuracy and uncertainty.

Findings

The results showed that LSTM outperformed all other benchmark methods. From a statistical perspective, the Diebold–Mariano test is also conducted to further substantiate better forecasting performance of LSTM over other counterpart methods.

Originality/value

The proposed study is a contribution to the literature on the container throughput forecasting and adds value to the supply chain theory of forecasting. Second, this study explained the architecture of the deep-learning-based LSTM method and discussed in detail the steps to implement it.

Details

Industrial Management & Data Systems, vol. 120 no. 3
Type: Research Article
ISSN: 0263-5577

Keywords

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Article
Publication date: 19 May 2020

Neeraj Yadav, Ravi Shankar and Surya Prakash Singh

This paper compares impact of Industry 4.0 / emerging information and communication Technologies (ICTs), for example, Internet of things (IOT), machine learning…

Abstract

Purpose

This paper compares impact of Industry 4.0 / emerging information and communication Technologies (ICTs), for example, Internet of things (IOT), machine learning, artificial intelligence (AI), robotics and cloud computing, on 22 organisational performance indicators under nine combinations of Lean Six Sigma (LSS) and quality management systems (QMS).

Design/methodology/approach

Survey of 105 Indian organisations was done about their experience of using QMS, Lean Six Sigma and emerging ICTs. Respondents included both manufacturing and service enterprises of different scales and sectors. The responses collected were compared, and statistically significant difference among them was evaluated using chi-square test.

Findings

The study confirmed statistically significant difference among 20 organisational performance indicators under different combinations of QMS, LSS and ICTs. These indicators include quality performance, delivery performance, sales turnover, inventory level and so forth. However, for two indicators, namely, absenteeism and throughput, significant difference in responses was not established.

Research limitations/implications

All possible combinations of QMS, LSS, only LSS tools and ICTs were not studied because of either theoretical impossibility (e.g. using LSS without LSS tools) or practically rare situations (e.g. organisations using ICTs and LSS without QMS). Furthermore, the impact from different sequences of implementing QMS, LSS and ICTs can be studied.

Practical implications

Using this study, practitioners can identify which LSS, Quality System and ICT combination results in best performance and quick success. On theoretical front, the study confirms impact of LSS and QMS on organisational performance.

Originality/value

This study evaluates organisational performance under several possible combinations of QMS, LSS, and emerging ICTs, which was so far unexplored.

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Article
Publication date: 1 October 2018

Seema Shukla, Surya Prakash Singh and Ravi Shankar

The ever-widening competitive global markets demand food business to demonstrate safe food supplies across the world. The causes of food borne illness are complex to…

Abstract

Purpose

The ever-widening competitive global markets demand food business to demonstrate safe food supplies across the world. The causes of food borne illness are complex to determine and require a careful evaluation of all stages of food supply chain and food safety practices. The purpose of this paper is to systematically investigate the factors responsible for the assessment of food supply chain and evaluation of food safety system in India.

Design/methodology/approach

The study utilizes a combination of qualitative and quantitative approach by exploring expert’s opinion systematically using a semi-structured interview followed by careful grouping of responses using the grounded theory approach to build the research theme. The prioritization of the critical factors is carried out using Pareto analysis. The methodological review was carried out to identify factors and categorize them based on their impact on hierarchical logical relationship using total interpretive structural modeling approach to determine the enablers.

Findings

This paper attempts to deliver an inimitable list of seven vital factors for the effective design of evaluation system for food safety practices. The study provides a careful insight on the issue pertaining to designing of assessment system including competence building for assessor and availability of well-defined technical protocol. The recommendation for developing a robust food safety inspection system by implementing stricter regulation, enhancing competence and design initiatives is provided.

Originality/value

The study provides a unique list of factors for the assessment of food safety practices and develops the relationship. Food safety assessment is an integral part of food safety study which is systematically explored and conceptualized in this paper. The study is carried out using the opinion of Indian experts.

Details

Benchmarking: An International Journal, vol. 25 no. 7
Type: Research Article
ISSN: 1463-5771

Keywords

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Article
Publication date: 29 November 2018

Seema Shukla, Surya Prakash Singh and Ravi Shankar

India is in the process to achieve an important place in $2,000bn global food trade. In order to achieve this goal, there is a need to develop a food safety system which…

Abstract

Purpose

India is in the process to achieve an important place in $2,000bn global food trade. In order to achieve this goal, there is a need to develop a food safety system which is well written down in line with international practices that are highly coordinated based on self-compliance to assure consumer protection. Accordingly, many organizations undergo assessment of their food safety system to verify compliance internally as well as externally. The purpose of this paper is to provide insight on the critical factors and benefits by evaluating the food safety assessment practices.

Design/methodology/approach

A questionnaire-based survey is conducted among 96 Indian food business operators and regulators involved in assessment practices to obtain critical factors for the assessment of food safety practices. The questionnaire captures indicators for motivations or challenges and benefits of food safety assessment to identify critical factors using exploratory factor analysis. Model for the food safety assessment practices was developed based on multiple regression analysis by determining the impact of factors on the benefits of food safety assessment.

Findings

This paper identifies four factors responsible for assessing food safety practices, namely, business-centric approach, legislative needs, technical practices and organization resentment as a combination of reasons and challenges along with two benefits risk: protection and organization reinforcement. The regression analysis indicates that the organization reinforcement gets positively impacted by business and technical practices and negatively by organization resentment. Risk protection has a significant relationship with legislative needs.

Originality/value

This is the first attempt to systematically explore the factors around the assessment of food safety practices in India. This study provides inputs for the practical application of managers and regulators.

Details

International Journal of Quality & Reliability Management, vol. 35 no. 10
Type: Research Article
ISSN: 0265-671X

Keywords

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Article
Publication date: 14 August 2017

Surya Prakash, Gunjan Soni and Ajay Pal Singh Rathore

The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and…

Abstract

Purpose

The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and logistics operations. The modeling approach adopted aims at the embedding supply chain risks in a closed-loop supply chain (CLSC) network design process and suggests optimal supply chain configuration and risk mitigation strategies.

Design/methodology/approach

The method proposes a closed-loop supply chain network and identifies the network parameter and variables required for closing the loop. Mixed-integer-linear-programming-based mathematical modeling approach is used to formulate the research problem. The solutions and test results are obtained from CPLEX solver.

Findings

The outcomes of the proposed model were demonstrated through a case study conducted in an Indian hospital furniture manufacturing firm. The modern supply chain is mapped to make it closed loop, and potential risks in its supply chain are identified. The supply chain network of the firm is redesigned through embedding risk in the modeling process. It was found that companies can be in great profit if they follow closed-loop practices and simultaneously keep a check on risks as well. The cost of making the supply chain risk averse was found to be insignificant.

Practical implications

Although the study was conducted in a practical case situation, the obtained results are not indiscriminate to the other circumstances. However, the approach followed and proposed methodology can be applied to many industries once a firm decides to redesign its supply chain for closing its loop or model under risks.

Originality/value

By using the identified CLSC parameters and applying the proposed network design methodology, a firm can design/redesign their supply chain network to counter the risk and accordingly come up with planned mitigation strategies to achieve a certain degree of robustness.

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