Indian Manufacturing Industries Research Articles

Analyzing barriers to green logistics in context of Circular Economy and Industry 4.0 in the Indian manufacturing industry

ABSTRACT In the current era of Industry 4.0 and Circular Economy, green logistics have become necessary for being sustainable. Adopting green logistics practices is a challenging task for the manufacturing industry, specifically in developing countries like India. In this study, we identified 16 barriers to implementing green logistics in the Indian manufacturing industry in reference to Industry 4.0 and circular economy. Data was collected from experts through a questionnaire-based survey. The decision-making trial and evaluation laboratory (DEMATEL) technique was applied to examine the degree of influence and interaction among the barriers. It has also helped in the classification of barriers into cause-and-effect categories. To validate the findings, a sensitivity analysis had also been carried out. The findings would help manufacturing organisations in developing strategies for implementing green logistics to achieve long-term sustainability.

Trade Integration and Production Disintegration of Manufacturing Industries: India in Global Platform

The bulk of the world trade in commodities now a days consist of intermediate goods, which play an essential role in production and creation of value-added. As a consequence, the global production process is getting much more integrated today than ever before. To understand and examine this internationalisation in Indian manufacturing industries, using World Input–Output Database (WIOD), we have estimated the foreign and domestic value-added contents in export and output of Indian manufacturing for the period 2000 to 2014. Further, to complement this analysis, we have also performed regression estimations to identify the relationship between export, imported inputs use, and output growth of Indian manufacturing industries. Our study reveals low usage of domestic inputs use and more usage of imported inputs. These indicate stronger backward linkages in production and weak forward linkages in global consumption and production networks. Regression analysis also strengthens the finding of higher backward participation of the manufacturing sector. We have employed panel vector error correction model, fully modified ordinary least square and dynamic OLS models. Our results reveal a robust long-run causality between imported inputs usage and export-growth of the sector. JEL Codes: C33, C67, F14, F15

Expectation-Reality Gap in Information Technology Discontinuance Intention

ABSTRACT Discontinuance intention has been reported as a major concern in the context of manufacturing SMEs. This study examines why user SMEs decide to discontinue the incumbent technology. The study employed the theoretical lens of diffusion of innovation theory, disenchantment-enchantment model, and technology-organization-environment model to develop an integrated Expectation-Reality gap (E-R gap) framework. The research model was examined using data gathered through a cross-sectional survey of 300 SMEs in the Indian manufacturing industry. We found E-R gap in compatibility, technology cost, government support, and ease of use are key reasons for the post-adoption disenchantment of SMEs. Further, we found that disenchanted SMEs’ discontinuance intentions are quite strong, and they are more likely to quit from adopted technology shortly. Information systems (IS) researchers can extend the E-R gap model to assess the phenomena of discontinuance intentions in other NIE contexts. Implications for research and practice are discussed.

Integrating Productivity & Safety in Indian Manufacturing Industries For Improved Performances

Integrating Productivity & Safety in Indian Manufacturing Industries For Improved Performances

Key performance factors for integration of Industry 4.0 and sustainable supply chains: a perspective of Indian manufacturing industry

PurposeThe purpose of this paper is to identify the key performance factors that can lead toward sustainability in the Industry 4.0 supply chains of manufacturing industries.Design/methodology/approachQuestionnaire is used to collect the data from manufacturing sector to prioritize the factors, which integrates both Industry 4.0 and sustainability. For this, stepwise weight assessment ratio analysis (SWARA) method is used to obtain the weights for criteria and sub-criteria to prioritize the factors.FindingsThe present study brings the findings about five key performance factors. Social factor needs much attention among all the criteria, followed by ecological, economic, information technology and dynamic capability theory. Further, change management, third-party audits and novel business models are key sub-factors to improve performance of sustainability in Industry 4.0 supply chains.Practical implicationsThis study prioritized the performance factors of Industry 4.0 and sustainable supply chain in Indian manufacturing sector. These prioritized factors help to improve performance of organizations, which are practicing the Industry 4.0 and sustainability practices. Managers in manufacturing industries can use the SWARA for assessment of weights for the criteria and sub-criteria factors to take appropriate decisions to improve the organizations’ performance.Originality/valueManagers in manufacturing industry can use these prioritized factors to improve the performance of their supply chains.

To study the comparison and effect of Six Sigma and Red Bin Analysis in Indian manufacturing industries

PurposeContinued quest for business improvement in terms of enhanced productivity and cost cuts is the most valued strategic function in an organization. Towards this endeavor, there have been evolutions of many problem-solving techniques like Lean, quality control (QC) tools, Six Sigma, total productive maintenance (TPM), etc. This paper introduces a different problem-solving methodology for quality improvement – prepare, measure, define, establish, control and stabilize (PMDECS) approach of Red Bin Analysis (RBA) – and presents empirical evidence of its effectiveness in eliminating the defectives at source (parts per million [PPM]) and improving the process capability (Cp).Design/Methodology/ApproachAn attempt has been made to compare RBA with the Six Sigma methodology in terms of number of defects, defectives, process capabilities, project duration, etc. Data validation with more than 2000 data points was conducted based on empirical data collected over multiple problem-solving projects conducted in six manufacturing industries of India to compare the effectiveness of both the methods. Finally, fuzzy AHP (analytical hierarchy process) model was proposed to identify the Quality Improvement Index for both the methods to address the manager’s dilemma in selecting an appropriate problem-solving method.FindingsThe paper provides empirical insights in establishing that the PMDECS approach of RBA is at par and sometimes better for problem-solving if the problem is not chronic and is at the initial stages, it requires less duration than Six Sigma projects and except casting process and it can yield better results in case of PPM rejection or Cp/Cpk improvement in other processes.Research limitations/implicationsBecause of the chosen research approach, the research results may lack generalizability. This research has been specifically conducted in automotive manufacturing industries. Therefore, researchers are encouraged to test the proposed propositions further.Practical implicationsThe paper includes implications for the usage of alternative problem-solving methods, like PMDECS approach of RBA.Originality/valueThis paper intends to compare how the results of six sigma projects in manufacturing industries are effective against a different methodology, PMDECS approach of RBA.

Validity and reliability of sustainable supply chain management frameworks in Indian smart manufacturing industries

PurposeSustainable supply chain management (SSCM) ensures integration of socially, environmentally and economically feasible practices in entire supply chain. SSCM principles can be implemented to improve efficiency and productivity of a system by different attributes of the system. The purpose of this article is to identify the most appropriate existing (SSCM) framework that can be implemented suitably in Indian smart manufacturing industries.Design/methodology/approachValidity and reliability analysis on the existing SSCM frameworks was carried out with the help of empirical data collected using questionnaire survey methodology from various Indian smart manufacturing organizations. The empirical data were gathered from various experts from top- and middle-level management in different smart manufacturing organizations across the country. Further, factor analysis was carried on the collected data to estimate the unidimensionality of each SSCM frameworks. Cronbach's alpha value was used to assess reliability of each framework. Subsequently, the frequency distribution analysis was done to obtain familiar elements in the segregated frameworks based on validity and reliability analysis.FindingsThe work observed that only five SSCM frameworks have shown unidimensionality in terms of the elements or constructs. The work further found that these segregated frameworks have not shown sufficiently high level of reliability. Additionally, this work attempted frequency distribution analysis and observed that there were very few elements which were being repeatedly used in numerous frameworks proposed by researchers. Based on the findings of this work, the work concluded that there is acute need of a new SSCM framework for Indian smart manufacturing industries.Research limitations/implicationsThis study gathered empirical data from 388 Indian smart manufacturing organizations. Thus, before generalizing the findings of the study across the sectors, there is a possibility of some more explication.Originality/valueThe main purpose of this article is to explore the feasibility of the existing SSCM frameworks in Indian smart manufacturing sector. The study also assumes that the manufacturing managers and executives may have the complete understanding on the existing sustainable manufacturing frameworks and a chance to executing proper suitable framework in the respective manufacturing organization.

Model development for assessing inhibitors impacting Industry 4.0 implementation in Indian manufacturing industries: an integrated ISM-Fuzzy MICMAC approach

Industry 4.0 (I4.0) adoption is becoming predominant in manufacturing industries due to its limitless opportunities. Even though companies are interested in adopting digitalization, several perceived barriers stymied them. However, in the interest of its smooth adoption, these perceived barriers must be addressed urgently. This research aims to analyze the broader spectrum of possible barriers that impede the implementation of I4.0 and converge them into the most prominent inhibitors, further assessing these inhibitors to develop contextual relationships among them. A comprehensive literature review and an empirical research-based survey considering a large sample size are used to address the study’s research objectives. Industry and academia experts’ inputs are considered to derive the I4.0 implementation barrier’s current prominence. The interrelationship among extracted twelve significant inhibitors through principle component analysis (PCA) is modeled using interpretive structural modeling (ISM) to manifest each inhibitor’s direct and indirect effect. Fuzzy matriced’ impacts croise’s multiplication applique’e a’ un classement (MICMAC) analysis is further considered to classify these inhibitors into drivers and dependents. The study depicts inadequate organizational strategies, uncertainty about financial decision making, limited employee readiness, inconsistent legal and government policies, Insufficient IT and automation infrastructure as the most prominent driver inhibitors of the I4.0 adoption. An integrated novel PCA-ISM Fuzzy MICMAC model developed in this research paper is unique and used for the first time to establish the hierarchical relationship among I4.0 implementation inhibitors considering the post-COVID-19 scenario. This study offers practical insights and outcomes that will help researchers, decision-makers, and practitioners in unlocking the potential of I4.0 by dealing with its inhibitors efficaciously.

Magnitude and determinants of energy intensity: evidence from Indian firms.

The topmost challenge for Indian manufacturing industries is to reduce the pace of energy intensity to deal with environmental degradation and climate change problems. In this light, we examine the firm-specific determinants influencing energy intensity of Indian manufacturing firms and suggest measures to minimize the energy intensity. To do so, we use aggregate firm-level data ranging between 2010 and 2021 and employ panel quantile regression. We found that the determinants, namely LI, RMPMI, PMI, and OI, have a statistically positive and significant impact on energy intensity. Other factors such as RMSSI, PATI, TDI, SI, and LNTA were found to show mixed results. Besides, we observed RMPMI as the most dominant factor driving energy intensity among Indian manufacturing firms. The findings of this paper endorse effective policymaking pertaining to energy intensity for Indian manufacturing firms and necessitates the modifications in energy conservation regulations.

Key performance indicator based dynamic decision-making framework for sustainable Industry 4.0 implementation risks evaluation: reference to the Indian manufacturing industries.

Global corporate giants are keen to adopt Industry 4.0 (I4.0) owing to its continuous, impactful, and evident benefits. However, implementing I4.0 remains a significant challenge for many organizations, mainly due to the absence of a systematic and comprehensive framework. The risk assessment study is key to the flawless execution of any project is a proven fact. This paper aims to develop a KPIs-based sustainable integrated model to assess and evaluate risks associated with the I4.0 implementation. This research paper has developed the I4.0 risks evaluation model through fifteen expert interventions and an extensive systematic literature review. This research, based on sixteen KPIs evaluates six risks impacting the organization’s decision to adopt I4.0. Initially, the Fuzzy Decision-Making Trial and Evaluation Laboratory method is used to map the causal relationship among the KPIs. Further, the additive ratio assessment with interval triangular fuzzy numbers method is used to rank the risks. The study revealed that information technology infrastructure and prediction capabilities are the most crucial prominence and receiver KPIs. Simultaneously, technological and social risks are found to be highly significant in the I4.0 implementation decision-making process. The developed model meticulously supports the manufacturer’s, policymaker, and researchers’ viewpoint toward I4.0 implementation in the present and post COVID-19 pandemic phases in manufacturing companies. The comprehensive yet simple model developed in this study contributes to the larger ambit of new knowledge and extant literature. The integrated model is exceptionally based on the most prominent risks and a wider range of KPIs that are further analyzed by aptly fitting two fuzzy MCDM techniques, which makes the study special as it perfectly takes care of the uncertainties and vagueness in the decision-making process. Hence, this study is pioneering and unique in context to I4.0 risks prioritization aiming to accelerate I4.0 adoption.

A descriptive statistical analysis of barriers to the adoption of integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS) in Indian manufacturing industries

PurposeScarcity of resources and ever-changing demand have attracted the government and manufacturers for an integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS). Many organizations failed to adopt ISGLSAMS due to various barriers. The purpose of this paper is to identify and rank the various barriers to ISGLSAMS and to analyze the correlations among the various barriers to ISGLSAMS so that the adoption of ISGLSAMS can be implemented in manufacturing organizations for more sustainable development of the industries, and industrial ecology.Design/methodology/approachA three tiers methodology is used to analyze the barriers to the adoption of ISGLSAMS. First, a total of 24 ISGLSAMS barriers are identified through a comprehensive literature review. Then data are collected with a structured questionnaire from 108 Indian manufacturing industries. Then, the sign test is used to check the relevance and significance of barriers. Then ISGLSAMS barriers are ranked based on the median and standard deviation. Spearman's correlations between the ISGLSAMS barriers are identified and studied to strengthen the in-depth understanding of correlations among the barriers.FindingsThe result shows that most of the Indian manufacturing industries agreed with the selected barriers to the adoption of ISGLSAMS. Low supplier commitment, uncertain financial benefits, the misconception of high cost, difficulty in evaluation of system performance throughout the life cycle, complexity in ISGLSA process design, the complexity of management of ISGLSAMS, complexity in ISGLSA system design, lack of updated information, complexity in ISGLSA product design and uncertain future legislation are found the major barriers for the ISGLSAMS in Indian manufacturing industries. While lack of leadership, low top management commitment, lack of government support, organizational structure, low employees' commitment, technological risk and low public pressure are considered minor barriers for the ISGLSAMS. Inter-relationships study of the barriers further contributes to the methodology to overcome the barriers.Practical implicationsThe study contributes to a better understanding of ISGLSAMS barriers. Through this study, government, stakeholders and policymakers may plan the policy, roadmap and strategies to overcome the barriers to the ISGLSAMS. This will lead to the successful adoption of ISGLSAMS for more sustainable development of manufacturing industries in India.Originality/valueThis work contributes to identifying the barriers to a more sustainable manufacturing system, i.e. ISGLSAMS (7Rs based), and prioritizing them in Indian manufacturing industries. The research also contributes to the (1) study of inter-relationships among the ISGLSAMS barriers for analyzing the effect of one barrier over another barrier, and (2) ISGLSAMS literature because the sustainable manufacturing literature still lags the achievement of sustainability goals due to 6Rs focus.

Measuring the Factors Affecting Annual Turnover of the Firms: A Case Study of Selected Manufacturing Industries in India

The manufacturing sector works as an engine of growth as it creates the conducive path for socio-economic development. In the said perspective, numerous studied have empirically proved the positive contribution of manufacturing sector in social – economic development. However, limited studies could examine the factors affecting manufacturing sector in different industries in India. Thus, this study assessed the determinants of the annual turnover of the firms in the Indian manufacturing sector. For aforementioned investigation, it used financial statistics of 154 selected Indian manufacturing firms which were operating in seven different industries (i.e., automobile and auto component, chemicals and petrochemicals, construction, electronics, industrial equipment & machinery, pharmaceuticals, and textiles and apparels) from nine states of India. Log-linear regression model under the stochastic frontier production function technique was considered to examine the impact of specific factors on the annual turnover of the firms. It highlighted that annual turnover of the firms was significantly reflected with labour intensity; firm's age and size, R&D expenditure, and technology up-gradation; investment on machinery; annual salary of workers, skilled and un-skilled manpower. The findings of this study also indicate that India is required to adopt strict intellectual property rights (IPRs) policy to reduce the imitation rate of technologies for further improvement in technology transfer and commercialization. Effective education system, science & technology (S&T) and conducive research & development (R&D) ecosystem would be supportive to increase the performance of firms in the Indian manufacturing sector. It also provides the research direction to validate the empirical findings of this study.

Impact of COVID-19 on the footwear industry of India: With special reference to Bata India Ltd

India is the second largest consumer and producer of shoes in the world after China and it is estimated that this industry in India will see 8 fold increases by 2030. India contributes 13% in production of footwear in the world accounting to 16 billion pairs annually. India stands on 3rd position after China and USA, when it comes to largest footwear consuming countries of the world. India stands far lower than the other global leaders of the world when it comes to having number of footwear per person. Indian consumes nearly 1.66 pairs of footwear on an average while the global consumption stands at 3.0 pairs of footwear annually. There are almost 18,000 units working in footwear manufacturing industry in India, accumulating an estimated total turnover of about Rs. 50,000 crores out of which Rs. 32,000 crores are from the domestic market while rest 18,000 crores comes from the exports. But all this was affected by a pandemic, a pandemic that the world has been witnessing since last 2 years. Each and every industry got affected due to this pandemic and footwear was not an exception to this. Our research paper on this title emphasises the impact of the pandemic (COVID-19) on the footwear industry in India by narrowing article’s circumference to Bata India Ltd. Our paper tries to show the effect of pandemic on the company’s revenue, net profit, its comparison with other footwear companies, etc. Descriptive research design has been implemented in this research paper, while the data was collected from secondary sources.

Causal modelling of the enablers of CPFR for building resilience in manufacturing supply chains

Supply chain resilience is widely receiving attention during the past decade. Collaboration and visibility enhancement in supply chains is a key to achieve resilience and robustness in supply chains. Collaborative Planning, Forecasting and Replenishment (CPFR) is always been one of the difficult, yet powerful tool for collaboration in supply chains. Companies, in general attempt to address the technological side of changes, but avoid addressing the non-technological side of it, while implementing CPFR. This paper aims to explore the technological and non-technological enablers of CPFR, separately considering the Indian manufacturing industries and study their causal relations, using the Interpretive Structural Modeling (ISM). The results are beneficial, as managers can concentrate on causal enablers, while implementing CPFR. The success factors for implementation can slightly vary across different industries, but the applicability of the result is wider due to several common issues that arise during its implementation. Thus, the paper aims to provide directions for considering the most influencing enablers that can act as critical factors in the successful implementation of the CPFR. These influential enablers can be given much focus to reduce the vulnerabilities and to enhance the resilience capabilities of firms and their supply chains.

Effect of microwave assisted hot-air drying temperatures on drying kinetics of dried black gram papad (Indian snack food): Drying characteristics of black gram papad

In this study, suitable drying techniques were evaluated for drying black gram papad using sun, tray and microwave assisted hot-air drying (MAHD). Drying of black gram papad in MAHD consumes less time (100-175 min) compared to tray (240 min) and sun (355 min) drying methods. Therefore, the drying characteristics of black gram papad were evaluated with MAHD using varying temperatures ranges of 40, 50 and 60 °C and validation was performed with fifteen thin-layer drying models. The suitability of different models was estimated using the coefficient of determination (R2), standard error of estimation (SEE), root mean square error (RMSE), relative mean error (P0) and chi-square (χ2). The ‘Weibull distribution model’ showed the best fit with the highest R2 (0.99) and lowest SEE (0.0002-0.0003), RMSE (0.0026-0.0047), P0 (6.40-7.49 %) and χ2 (0.0448-0.0677) values for drying black gram papad using varying temperatures of MAHD. The moisture diffusivity for varying temperatures (40 to 60 °C) of MAHD ranged from 4.60×10-09 to 6.28×10-09 m2/s and the activation energy was found to be 13.50 kJ/mol. The drying of black gram papad using the MAHD method will be beneficial and time-consuming for the papad manufacturing industries in India.

Fuzzy AHP approach for barriers to implement LSS in the context of Industry 4.0

PurposeThe purpose of the present work is identification and prioritization of barriers to Lean Six Sigma (LSS) implementation in Indian manufacturing industries in the context of Industry 4.0 (I4.0) to surmount the impediments in the path of successful implementation.Design/methodology/approachIn total, 27 barriers identified through critical review of literature and expert's opinion are evaluated with Cronbach's alpha values including item-total correlations or corrected item-total correlations (CITC) using statistical tool. Finally, 20 barriers were analyzed and ranked employing Fuzzy Analytical Hierarchy Process (FAHP).FindingsThe study depicts that “Lack of leadership, advisory and monitoring,” “Lack of clarity about economic benefits” and “Lack of integration of LSS with smart tools/I4.0” are potential barriers to drive the path for proper implementation of LSS in Industry 4.0 with due consideration of its technologies in Indian manufacturing industries.Practical implicationsThe study provides better knowledge platform for academicians and researchers about hidden aspects of LSS implementation barriers in view of advanced manufacturing technologies. This research will help the practitioners to design their business plans in implementing new quality improvement tools to get advantage in current competitive environment.Originality/valueThe barriers are selected based on literature and opinion from industry and academic experts. Five major criteria are decided after incorporating inputs. The ranking of the barriers is attained by well standard mathematical technique. This will enable the practitioners to design strategies to eliminate the hindrances in order to shape the right path for effective implementation of LSS approach in view of advanced manufacturing technologies.

The Relationship of Organizational Ambidexterity and Organizational Virtuousness in the Automobile Industry of India

The present study measures the impact of organizational ambidexterity on organization virtuousness in the context of the car manufacturing industries in India. 363 employers' representatives were selected from automotive manufacturing car units across India to gain an understanding of their perspectives on handling organizational ambidexterity and virtuousness for new diploma/degree/postgraduate employees. The purposive sampling technique was used. Data were collected using the survey questionnaire method. The collected data were analyzed using structural equation modeling. Organizational ambidexterity has a significant effect on organizational virtuousness, according to the study's results. Exploration orientation and exploitation orientation are two sub-constructs of organizational ambidexterity. Exploratory orientation has shown a dominant significant impact on organizational virtuousness than the exploitation orientation.

STUDY OF IMPACT OF COVID 19 ON SMALL SCALE INDUSTRIES IN INDIA

India has been combating the corona virus disease also known as COVID - 19 pandemic for two years. This pandemic has affected not only India but also the entire world around. Several measures were imposed by the Government in order to stop the spread of this pandemic. During the first , second and third wave of COVID – 19 pandemic, strict lockdown was imposed in India. In order to stop the spread of the covid 19 many small scale industries were shut down.This protocol had a very bad impact on small scale Industries. This research paper highlights the impact of the corona virus disease pandemic on the small scale manufacturing industries in India. The present paper starts with the introduction followed by research objectives, research type and the method of data collection have been stated. The analysis of challenges faced by the small businesses has also been discussed followed by the conclusion.

An analysis of drivers for the adoption of integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS) in Indian manufacturing industries

PurposeScarcity of resources and ever-changing customer demand has driven the manufacturing organization to opt for an integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS). The purpose of this study is to identify and rank the various drivers for the adoption of ISGLSAMS for the more sustainable development of the industries.Design/methodology/approachUsing a survey questionnaire, data were collected for the 14 ISGLSAMS drivers, identified through the literature review, from 108 Indian manufacturing industries. The sign test is used to check the relevance and significance of drivers. ISGLSAMS drivers are ranked based on the median and standard deviation. A multiple regression model was employed to investigate the effects of other drivers on the highest-ranked driver to strengthen the understanding of the drivers.FindingsCompetition, customer demand, technological changes, supply chain pressure, cost benefits, incentives, top management commitment and future legislation are found the strongest drivers for ISGLSAMS. For administering the competition for ISGLSAMS policymakers must focus on the availability of organization resources, customer demand, future legislation, incentives, supply chain pressure and technological developments.Practical implicationsThe study contributes to a better understanding of ISGLSAMS drivers. Through this study government, stakeholders and policymakers may plan the policy, roadmap and strategies to drive the manufacturing organizations for the adoption of ISGLSAMS for more sustainable development of industries in India.Originality/valueThis work contributes to the identification and prioritization of the drivers for the more sustainable manufacturing system, i.e. ISGLSAMS (7 Rs based, i.e. 6 Rs of sustainability with 7th R, reconfiguration). The research also contributes to the (1) ISGLSAMS literature (2) the awareness and demand of (a) ISGLSAMS (b) reconfigurable, sustainable and modular products (c) redesign, recovery and refurbishing of the product to increase the product life cycle.

Assessment of Agile manufacturing impact on business performance of Indian manufacturing industry: A PLS-SEM approach

A limited number of previous studies investigated the impact of agile manufacturing on overall business performance, especially in the Indian context. The study investigates the influence of agile manufacturing attributes, namely: Leadership support, Human related issues, customer-related issues, and Information technology on business performance. The data was collected from 154 manufacturing industries and analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The results show a positive and significant influence of agile manufacturing attributes on the manufacturing industry's business performance.