Rakesh Kumar Verma and Rohit Bansal
This paper aims to identify various macroeconomic variables that affect the stock market performance of developed and emerging economies. It also investigates the effect of these…
Abstract
Purpose
This paper aims to identify various macroeconomic variables that affect the stock market performance of developed and emerging economies. It also investigates the effect of these factors on the stock markets of both economies. The impact of these variables on broad market indices and sectoral indices is investigated and compared too.
Design/methodology/approach
The publications for the study were retrieved from databases such as Emerald Insight, EBSCO, ScienceDirect and JSTOR using the keywords “Macroeconomic variables” and “Stock market” or “Stock market performance.” The result demonstrated a growing corpus of scholarly work in the domain of stock market. The study was carried out separately for each macroeconomic indicator. Given a large number of articles under consideration, the authors began by reading the titles and abstracts of all publications to identify those that were relevant. The papers are evaluated in Excel and the articles for review range from 1972 to 2021.
Findings
The authors found that gross domestic product (GDP), FDI (Foreign Direct Investment) and FII (Foreign Institutional Investment) have a positive effect on both emerging and developed economies’ stock market while gold price has a negative effect. Interest rates had a negative impact on both economies except for a few developing countries. The relationship with oil prices was positive for oil exporting countries while negative for oil importing countries. Inflation, money supply and GDP are the macroeconomic variables that have the same effect on sectoral indices as they do on broad market indices. The impact was sector-specific for the remaining variables.
Research limitations/implications
This paper gives an overview of relation and effect covering variety of macroeconomic variables and stock market indices. Still, there is a scope for further research to analyze the effect on thematic, strategy and sectoral indices. A longer time horizon with new variables, such as bank deposit growth rate, nonperforming assets of banks, consumer confidence index and investor sentiment, can be studied using high-frequency data. This research may help stakeholders adopt and manage their policies during a crisis or economic slump.
Practical implications
This study will assist investors, researchers and educators in the fields of economics and finance in understanding how macroeconomic factors affect the stock market. Furthermore, this study can guide in portfolio diversification strategy across multiple sectors by examining the impact of macroeconomic factors specific to sectoral indices. This paper provides insight into society and researchers since it integrates a number of macroeconomic variables and their interaction with the stock market. It may also help pension funds and mutual fund firms to hedge their funds and allocate equity portfolios.
Originality/value
With respect to India, this study looked at new macroeconomic variables and sectors. It contrasted the impact of these variables in developed and developing economies. The effect of broad and sectoral stock indexes was also investigated and compared. The authors examined how these variables responded during crisis and economic downturns by using articles from a longer time frame. This research also looked into how changing the frequency of data for the variables altered stock performance. This paper emphasized the need for more research into thematic, strategy and broad market indices, such as small-cap and mid-cap indices.
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Rakesh Kumar, Shailesh Kumar Kaushal and Kishore Kumar
This paper aims to explore the role of source credibility while purchasing environment-friendly products using Ajzen’s (1991) theory of planned behavior as underpinning model.
Abstract
Purpose
This paper aims to explore the role of source credibility while purchasing environment-friendly products using Ajzen’s (1991) theory of planned behavior as underpinning model.
Design/methodology/approach
The proposed theoretical model was empirically tested with the data collected from 334 respondents using structural equation modeling.
Findings
The results gave empirical support to the addition of source credibility to the original theory of planned. Moreover, consumer attitude was found mediating the effect of corporations’ credibility on purchase intention. Also, attitude and perceived behavioral control were found as the most important predictors of consumer’s intention to purchase environment-friendly products.
Practical implications
This study provides valuable insights for the marketers engaged in sustainable business practices. Amid, ever-increasing carbon emission, promoting the use of environment-friendly products has become the need of the time. Credibility plays a crucial role while promoting and communicating an organization’s sustainable practices among its stakeholders including consumers. Therefore, the marketer should formulate appropriate marketing communication strategy to communicate the consumer about the green practices and environment-friendly products they produce. The results suggest that corporation’s credibility shapes consumer attitude and influences intention to purchase environment-friendly products. Earning trust of the consumer is pivotal to achieve success in the market. Therefore, results may help the marketers to better understand consumer’s response toward their marketing strategies and further convince and persuade them to buy their products.
Social implications
The findings of this study may be useful for marketers, strategists, policymakers and government while formulating promotional strategies to make consumer aware, educate and persuade them to purchase products which do not cause harm to the environment.
Originality/value
The study is novel in terms of exploring role of source credibility and extending theory of planned behavior in the context of sustainable consumption.
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The purpose of this study is to investigate the role of ethical obligation and environmental concern in young consumers’ green purchase behaviour using Ajzen’s (1991) theory of…
Abstract
Purpose
The purpose of this study is to investigate the role of ethical obligation and environmental concern in young consumers’ green purchase behaviour using Ajzen’s (1991) theory of planned behaviour as underpinning theoretical model.
Design/methodology/approach
Data collected from 253 college students of a major higher education institution in Northern India were analysed by using structural equation modelling and moderated mediation analysis in AMOS 22.0 and SPSS 20.0.
Findings
Investigating why environmental concern does not significantly translate into green purchase intention, the study demonstrates that the effect of environmental concern was mediated through attitude and ethical obligation. In addition, the study also found that the effect of environmental concern on attitude was positively moderated by ethical obligation. Moreover, subjective norms were found to exhibit no direct effect on green purchase intention; rather, this effect was indirect and mediated through attitude and perceived behavioural control. The results of moderated mediation analysis further demonstrated that the indirect effect of subjective norms on green purchase intention through attitude was found conditional on the values of perceived behavioural control.
Originality/value
The study offers a valuable contribution by signifying the moderating role of ethical obligation in green purchase behaviour. It also contributes to the existing knowledge by assessing the conditional indirect effect of subjective norms on green purchase intention which is rarely examined in the literature.
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Bikram Jit Singh, Rippin Sehgal, Ayon Chakraborty and Rakesh Kumar Phanden
The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology…
Abstract
Purpose
The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.
Design/methodology/approach
After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.
Findings
The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.
Research limitations/implications
The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.
Practical implications
The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.
Originality/value
The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.
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Kumar Mukul and Gordhan K. Saini
The purpose of this paper is to explore the talent acquisition practices adopted by startups and understand how small entrepreneurs leverage social capital to address the talent…
Abstract
Purpose
The purpose of this paper is to explore the talent acquisition practices adopted by startups and understand how small entrepreneurs leverage social capital to address the talent acquisition challenges faced by them, and; identify some of the unique parameters adopted by startups in talent acquisition.
Design/methodology/approach
This study uses a multiple case study method to explore the talent acquisition practices in startups in India. The study included six case studies on startups in Hubli city of North Karnataka in India.
Findings
This paper finds that startups (especially in smaller cities) face challenges such as lower quality of talent pool, absence of a brand name, inability to provide competitive salary and other benefits as per industry standards and locational disadvantages in talent acquisition. Thus, entrepreneurs leverage their social capital for talent acquisition by handpicking talent on the basis of familiarity or credible networks and recommendations. Incubation centres provide institutionalized sources of social capital to help them attract good talent. This study finds that employee-culture fit and trust play important role in acquiring talent in startups.
Practical implications
The study has implications for startup entrepreneurs, recruitment service providers, incubation centres, trainers, policymakers, etc. The study provides useful insights to the startups with regard to their recruitment practices.
Originality/value
This study contributes to the literature in the domains of talent acquisition, startups and social capital by describing hiring challenges faced by startups and exploring the mechanisms used by them in overcoming such challenges.
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India started economic reforms at a rapid pace to catch up the world economy by following the services-led-growth model during the post-liberalisation period. Over the years, the…
Abstract
Purpose
India started economic reforms at a rapid pace to catch up the world economy by following the services-led-growth model during the post-liberalisation period. Over the years, the growing unemployment rate posits a re-look into the dynamics of growth model for wider work force participation. In this backdrop, the paper aims to examine the dynamics of structural changes in employment pattern in view of economic growth led by services-led growth model in India.
Design/methodology/approach
The study employs a non-linear autoregressive model (NARDL) to examine the effect of the growth rates in three broad economic sectors namely agriculture and allied, services and industry on work force participation representing the employment opportunities in India.
Findings
The results highlight that the rapid expansion of the service sector has not occurred with enough employment opportunities by the same rate. By contrast, the growth in the industrial sector significantly creates employment opportunities in the short and long run. These results support the industry led growth model over the services for sustainable and inclusive economic growth in the country.
Research limitations/implications
The study relies on combined labour force participation rates rather than gender-specific rates. Further, the regulatory, working conditions and economic incentives may affect the gender-specific engagement of the labour force in three broad sectors.
Practical implications
The results offer important insight into changing patterns in employment with policy lessons. A wider workforce force participation calls for expansion of manufacturing activities through pro-industry programmes.
Originality/value
The study makes pioneer efforts to examine the dynamics of labour force participation with respect to the growth of three broad economic sectors of the Indian economy. The results provide new insights with policy implications for the changing employment pattern and policy response.
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Rakesh Kumar Phanden, Ajai Jain and Rajiv Verma
The purpose of this paper is to optimise the job shop scheduling problem using simulation and genetic algorithm.
Abstract
Purpose
The purpose of this paper is to optimise the job shop scheduling problem using simulation and genetic algorithm.
Design/methodology/approach
The paper presents a simulation‐based genetic algorithm approach for the job shop scheduling problem. In total, three cases have been considered to access the performance of the job shop, with an objective to minimise mean tardiness and makespan. A restart scheme is embedded into regular genetic algorithm in order to avoid premature convergence.
Findings
Simulation‐based genetic algorithm can be used for job shop scheduling problems. Moreover, a restart scheme embedded into a regular genetic algorithm results in improvement in the fitness value. Single process plans selected on the basis of minimum production time criterion results in improved shop performance, as compared to single process plans selected randomly. Moreover, availability of multiple process plans during scheduling improves system performance measures.
Originality/value
The paper presents a simulation‐based genetic algorithm approach for job shop scheduling problem, with and without restart scheme. In this paper the effect of multiple process plans over single process plans, as well as criterion for selection of single process plans, are studied. The findings should be taken into account while designing scheduling systems for job shop environments.
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Rakesh Raut, Vaibhav Narwane, Sachin Kumar Mangla, Vinay Surendra Yadav, Balkrishna Eknath Narkhede and Sunil Luthra
This study initially aims to identify the barriers to the big data analytics (BDA) initiative and further evaluates the barriers for knowing their interrelations and priority in…
Abstract
Purpose
This study initially aims to identify the barriers to the big data analytics (BDA) initiative and further evaluates the barriers for knowing their interrelations and priority in improving the performance of manufacturing firms.
Design/methodology/approach
A total of 15 barriers to BDA adoption were identified through literature review and expert opinions. Data were collected from three types of industries: automotive, machine tools and electronics manufacturers in India. The grey-decision-making trial and evaluation laboratory (DEMATEL) method was employed to explore the cause–effect relationship amongst barriers. Further, the barrier's influences were outranked and cross-validated through analytic network process (ANP).
Findings
The results showed that “lack of data storage facility”, “lack of IT infrastructure”, “lack of organisational strategy” and “uncertain about benefits and long terms usage” were most common barriers to adopt BDA practices in all three industries.
Practical implications
The findings of the study can assist service providers, industrial managers and government organisations in understanding the barriers and subsequently evaluating interrelationships and ranks of barriers in the successful adoption of BDA in a manufacturing organisation context.
Originality/value
The paper is one of the initial efforts in evaluating the barriers to BDA in improving the performance of manufacturing firms in India.
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Ramin Rostamkhani and Thurasamy Ramayah
This chapter of the book aims to achieve sustainability and productivity in light of the interaction between managers and engineers in a lean and agile supply chain management…
Abstract
This chapter of the book aims to achieve sustainability and productivity in light of the interaction between managers and engineers in a lean and agile supply chain management system in today’s organizations. The main innovation of this chapter is the use of the balanced scorecard (BSC) model and fuzzy analysis network process (FANP) to create a suitable platform for the realization of this interaction between managers and engineers and to identify exactly which expert system is ideal for the main purpose. Indeed, this chapter introduces its readers to the application of strategic management tools such as the BSC accompanied by FANP in the elements of supply chain management where data analysis of lean and agile networks in supply chain management can create a competitive advantage in the organization.
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Rakesh Kumar, Vibhuti Tripathi, Vibha Yadav, Gaurav Ashesh and Richa Mehrotra
The study seeks to explore why despite growing concern for the environment, consumers’ intention to purchase organic foods remains relatively low. In addition, the study also…
Abstract
Purpose
The study seeks to explore why despite growing concern for the environment, consumers’ intention to purchase organic foods remains relatively low. In addition, the study also seeks to investigate the role of perceived marketplace influence (PMI) and moral norms in organic food consumption.
Design/methodology/approach
Data collected from 330 young consumers chosen with non-probability sampling were analysed using structural equation modelling in Amos 22.0.
Findings
The results of the parallel mediation analysis confirmed that environmental concern influences purchase intention indirectly through attitude, subjective norms, perceived behavioural control and perceived marketplace influence. In addition, moral norms were found to moderate the effect of perceived behavioural control on purchase intention. Moreover, the results also indicated that the impact of environmental concern on consumers’ attitude toward organic foods was also moderated by moral norms. Further, the results of moderated mediation showed that the indirect effect of environmental concern on purchase intention (through attitude and perceived behavioural control) was moderated by moral norms.
Research limitations/implications
The study contributes to the existing literature by investigating the inconsistency between environmental concern and purchase intention. In addition, the study also investigate role of perceived marketplace influence and moral norms in stimulating organic food consumption intentions.
Practical implications
The emergence of perceived marketplace influence as an important determinant of organic food consumption shows that every individual needs to realise the importance of their environment friendly actions to promote organic food consumption. In addition, the study also highlights the pivotal role of moral norms in the promotion of organic food consumption. Thus, markets, policy-makers, family, friends, society all should promote and inculcate the spirit of contributing in the cause of safeguarding the environment to the young children specially by promoting consumption of organic foods.
Originality/value
The study examines the role of perceived marketplace influence as predictor of purchase intention towards organic foods which is rarely explored specially in the domain of organic food consumption. In addition, the results also produced some novel insights into the moderating role of moral norms.