Stock price reaction to patent related news: a study of indian manufacturing sector

Stockholder and Bondholder Wealth Effects of CEO Incentive Grants

Purpose The purpose of this paper is to examine the psychometric properties of the positive and negative affect schedule (PANAS) in a sample of employees working in Indian manufacturing and service sector organisations. Design/methodology/approach The data were collected through self-administered structured questionnaire from 53 employees for the pilot study and 383 employees for the final study. For the psychometric evaluation of the PANAS, item analysis, reliability, exploratory factor analysis, convergent–discriminant validity and confirmatory factor analysis were performed. Findings Results reveal that the two-factor model of affect (positive and negative affects) is valid in the Indian manufacturing and service sector organisations. Originality/value Despite being the largest skilled labour facilitator for the work economy and second largest populated country, India lags behind in studies evaluating affect at work when compared to western nations. The present study was taken up to validate an instrument to measure affect at work in Indian manufacturing and service sector organisations, which is a new contribution in the field. Validation of this instrument would help in promoting studies on affect at work in India and comparative studies across cultures.

Stock Price Effects Associated with Index Replacements in Germany

An Empirical Analysis of the Effects of Online Trading on Investor Reactions to Earnings Announcements

Despite the presence of a large chunk of manufacturing firms in the informal sector in India, we know very little about their characteristics and evolution over time in a period when the Indian economy has been increasingly globalized. What constrains firm growth, productivity and wages in the informal manufacturing sector in India? How different are the characteristics of firms in the Indian informal manufacturing sector across the different types of firms that populate this sector, across household and non-household enterprises? How have firm characteristics including firm size and firm productivity changed in the 2000s, a period of rapid globalization in India? In this chapter, we attempt to address this gap in the literature by conducting a detailed investigation of informal manufacturing firms in India, using rich unit record data on these firms from the NSSO for the years 2000–01, 2005–06, 2010–11 and 2015–16. To be specific, we first look at the evolution of firm size across the three different categories of firms in the Indian informal manufacturing sector—own account manufacturing enterprises (OAMEs), non-directory manufacturing enterprises (NDMEs) and directory manufacturing enterprises (DMEs), first in the aggregate and then by state and industry. We then look at firm size and productivity by different sets of firms’ characteristics (location of the firm, age and gender and social group of the owner) to see if there are observable differences in firm size and productivity across firms of different characteristics. We note the presence of the ‘missing middle’ problem in Indian manufacturing. One important concern about firms in the informal sector is that they pay less wages to their workers than firms in the formal sector. We capture this by examining the differences in wages paid to workers by specific characteristics of firms—by firm type, ownership, social group of owner and firm size. Our findings suggest the need to enhance firm productivity in the Indian informal sector, as a means to improve the living standards of the workers employed in the informal sector. We also notice that there exist significant social and economic barriers to informal firms in increasing their productivity, which is a matter of major policy concern.

Purpose: With a rapid growth in the Indian manufacturing sector, the assessment of the sector is necessary for various aspects. The present study focused on identifying and assessing the drivers and challenges pertaining to current practices of lean-green deployment in Indian manufacturing based on the recent literature and experts in the manufacturing space. Design/methodology/approach: The study was conducted in three phases. Phase 1 involved literature review and expert consultation. Phase 2 includes a three-step data collection procedure whereby 44 experts provided responses that formed the basis for the assessment of the factors. Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) was used to rank the drivers and challenges with respect to the perspective of the consumer, industry, and the government. Phase 3 involved validating the relevance of our study based on the experts and literature. Outcome: The top-ranked driver and top-ranked challenge was identified. Insight into the present scenario of lean-green deployment in manufacturing is facilitated by factors identified from recent literature. Originality: There is very little literature assessing the factors pertaining to lean-green deployment in Indian manufacturers. Most work focus specifically on SMEs or MSME, and not the entire manufacturing sector. Accordingly, respondents selected for the study were those with diverse experience in the sector.KeywordsLean-green manufacturingSustainabilityIndian manufacturing sector

PurposeThis study highlights the trends of qualitative intellectual capital disclosures and patent statistics in the Indian manufacturing context by considering the numerous patent applications, patent grants, forward citations and backward citations. Furthermore, the study investigates the relation among qualitative disclosures, patent statistics and firm performance.Design/methodology/approachAll manufacturing companies of CNX 500 Index of National Stock Exchange of India Limited are considered. Based on data availability, 243 manufacturing firms spanning across seven major manufacturing sectors are included. Secondary data were obtained from the annual report of companies and patent databases from 2004 to 2005 to 2013–2014, generating a sample of 2,430 firm years. Content analysis and citation analysis are used for collecting the relevant data.FindingsOverall, the study results indicated increasing trends for all types of intellectual capital disclosures. Similar trends are observed for patent applications and patent grants, indicating a surge in patenting activities across the manufacturing sector. However, increasing trends in patenting activities are not reflected for forward and backward citations. In addition, significant differences in means and trend coefficients for qualitative disclosures and patent statistics indicated industry specificity within the Indian manufacturing sector. Furthermore, industry specificity is observed when translating intellectual capital to firm performance. The measure of firm performance, that is, Tobin's Q, is having a significant positive association with qualitative disclosures and patent statistics.Research limitations/implicationsAs the study is based on secondary data, its accuracy is limited by the accuracy of the data sources such as the annual reports of companies and patent databases.Practical implicationsThe study findings imply that policymakers should devise and execute sector-specific policy interventions. Moreover, managers and policymakers should emphasize the qualitative aspect of patenting activities.Originality/valueThe study is an original work that highlights the trends in qualitative disclosures in the Indian manufacturing context. The value relevance of intellectual capital and patent statistics has been established.

The present study was undertaken to explore the evolution of the impact of firm-level performance on employment level and wages in the Indian organized manufacturing sector over the period 1989-90 to 2013-14. One of the major components of the economic reform package was the deregulation and de-licensing in the Indian organized manufacturing sector. The impact of firm-level performance on employment and wages were estimated for Indian organized manufacturing sector in major sub-sectors in India during the period from 1989-90 to 2013-14 of the various variables namely profitability ratio, total factor productivity change, technical change, technical efficiency, openness (export-import), investment intensity, raw material intensity and FECI in total factor productivity index, technical efficiency, and technical change. The study exhibited that all explanatory variables except profitability ratio and technical change cost had a positive impact on the employment level. Out of eight variables, four variables such as net of foreign equity capital, investment intensity, TFPCH, and technical efficiency change showed a positive impact on wages and salary ratio and rest of the four variables such as openness intensity, technology acquisition index, profitability ratio, and technical change had negative impact on wages and salary ratio. In this context, the profit ratio should be distributed as per the marginal rule of economics such as the marginal productivity of labour and capital.

From the first industrial revolution to the era of Industry 4.0 (I4.0), Indian manufacturing sectors have undergone significant transformations. The global market’s competitiveness has surged due to the rising demand for customized consumer goods, prompting industries to adopt advanced manufacturing models to maintain their edge. This paper introduces a novel Conceptual Framework-Based Architecture (CFA) using a real-life case study of an Indian commercial vehicle manufacturing plant. The proposed CFA aims to minimize barriers to implementing I4.0 technologies by developing a standardized architecture customized to the Indian manufacturing context. It addresses existing technological requirements and implementation challenges in three phases, considering existing production systems, current technologies, and system needs. The CFA enhances productivity, and transparency through real-time data monitoring, automated system communication, and responsiveness. It also tackles I4.0 implementation challenges between physical and cyber systems, employee adaptability to new technologies, the absence of global standards, and the need for uniform standards in tools, equipment, systems, and data services. The CFA elements were validated for system readiness in an existing manufacturing plant. This framework serves as a reference tool for industrial strategists, decision-makers, policymakers, and researchers, aiding in the integration and configuration of I4.0 technologies in the Indian manufacturing sector.

In this abstract, Total Quality Management (TQM) in India's manufacturing sector is conceptually analyzed. TQM is a well-known methodology that emphasizes ongoing development, client happiness, and organizational excellence. TQM is essential for boosting competitiveness and tackling the issues brought on by international markets in the context of Indian manufacturing. The main TQM components—leadership commitment, workforce engagement, process improvement, and customer centricity—are examined in this examination. It investigates how these components fit into the Indian manufacturing sector while taking into account regional cultural, economic, and regulatory concerns. The abstract also analyses how TQM implementation has affected several facets of the manufacturing sector, including customer loyalty, operational effectiveness, product quality, and supply chain management. It also emphasizes the difficulties that Indian manufacturers may have adopting TQM practices successfully. This paper contributes to a better understanding of the function of TQM in promoting sustainable growth, quality improvement, and competitive advantage for Indian manufacturers by evaluating the conceptual framework of TQM and its application in the Indian manufacturing industry.

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.

The Indian manufacturing sector provides livelihood to more than 14 million people (43.4% of the workforce) and contributes ~16% to India’s GDP. The Indian government has prioritized growing the manufacturing sector over the last ten years with several policy initiatives introduced under the "Make in India" campaign. Besides, major economies across the globe are diversifying their supply chains away from China. This is the result of global supply chain disruption that the world experienced as an after-effect of the COVID-19 pandemic and due to over reliance on China in the manufacturing space. This has opened new ways for the Indian manufacturing industry to prosper. The Indian government, aware of the situation, plans to boost the manufacturing sector’s contribution to the economic output by up to 25% by 2025. In this case study we discuss the key factors and government policies that is likely driving the growth of manufacturing in India. Key Words: Manufacturing Sector, Growth, GDP and Make in India.

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: "Times New Roman","serif"; text-shadow: none;"><span style="font-size: x-small;">The current study extends theory developed by Malatesta and Thompson (1985) to the area of corporate downsizing, and finds that the magnitude of the stock price reaction to announcements of corporate layoffs is a function of two factors, (1) the economic impact of the announced layoff, and, (2) the degree to which the announcement and signal about the underlying conditions related to the announcement have been anticipated by investors and incorporated previously into the stock price (predisclosure information).</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: "Times New Roman","serif"; text-shadow: none;"><span style="font-size: x-small;"> </span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: "Times New Roman","serif"; text-shadow: none;"><span style="font-size: x-small;">For firms experiencing a negative overall stock price reaction at the date of a layoff announcement, the larger the layoff (proxy for economic impact), the more <strong style="mso-bidi-font-weight: normal;"><span style="color: black;">negative</span></strong> the stock price reaction.<span style="mso-spacerun: yes;">  </span>Also for these firms, the smaller the firm size (proxy for the level of predisclosure information), the more <strong style="mso-bidi-font-weight: normal;"><span style="color: black;">negative</span></strong> the stock price reaction. This provides evidence that for some firms, the financial distress effect dominates, and the market incorporates previously unknown negative information into the stock price, which results in the negative stock price reaction.<span style="mso-spacerun: yes;">  </span>For these firms, the larger the impact and the less the event is anticipated, the more negative is the stock price reaction.</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: "Times New Roman","serif"; text-shadow: none;"><span style="font-size: x-small;"> </span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: "Times New Roman","serif"; text-shadow: none;"><span style="font-size: x-small;">For firms experiencing a positive overall stock price reaction at the date of a layoff announcement, the larger the layoff (proxy for economic impact), the more <strong style="mso-bidi-font-weight: normal;"><span style="color: black;">positive</span></strong> the stock price reaction.<span style="mso-spacerun: yes;">  </span>Also for these firms, the smaller the firm size (proxy for level of predisclosure information), the more <strong style="mso-bidi-font-weight: normal;"><span style="color: black;">positive</span></strong> the stock price reaction. This provides evidence that for some firms, the potential benefit effect dominates.<span style="mso-spacerun: yes;">  </span>The market has previously incorporated negative information associated with the conditions leading up the layoff, and is now incorporating positive information about the benefits to be achieved by the layoff, which results in the positive stock price reaction.<span style="mso-spacerun: yes;">  </span>For these firms, the larger the impact and the less the event is anticipated, the more positive is the stock price reaction.</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: "Times New Roman","serif"; text-shadow: none;"><span style="font-size: x-small;"> </span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: "Times New Roman","serif"; text-shadow: none;"><span style="font-size: x-small;">In this study, hypotheses are developed which combine the effects of both economic impact and predisclosure information with the financial distress and potential benefit hypotheses developed in prior research in corporate downsizing.<span style="mso-spacerun: yes;">  </span>Instead of offering the these two hypotheses as competing and mutually exclusive, evidence is provided that supports the conclusion that these hypotheses simultaneously explain <span style="color: black; mso-bidi-font-style: italic;">concurrent</span> and <span style="color: black; mso-bidi-font-style: italic;">additive</span><span style="color: black;"> effects on the stock price reaction to announcements of company layoffs.<span style="mso-spacerun: yes;">  </span>Finally, results indicate that the relationship between economic impact, predisclosure information and stock price reaction to layoff announcements depends on the relative dominance of the signals provided by the layoff about both financial distress and potential benefit.</span></span></span></p>

PurposeThe purpose of this paper is to examine the propagation of benchmarking concepts among Indian manufacturing companies after liberalization of Indian economy.Design/methodology/approachTo determine the propagation of benchmarking concepts in the Indian manufacturing sector, first, a postal survey was conducted on 500 Indian manufacturing companies. Only 97 companies participated in the survey. Subsequently, interviews with 20 managers of six manufacturing companies were undertaken.FindingsResearch showed that benchmarking in Indian manufacturing sector is still in the nascent stage, but there is a positive attitude towards adoption of benchmarking concepts. The industry sectors, which typically show above average levels of benchmarking activity, are motor vehicle, electric and electronic industries. By contrast, it is the process sectors, which record the lowest incidences of benchmarking. Identification of suitable benchmarking partner was considered to be the most important problem among Indian manufacturing companies.Research limitations/implicationsA limitation of research is the number of respondents, which precludes the generalization of findings.Practical implicationsThe study can help managers of manufacturing companies understand the problems and inhibitors to successful benchmarking.Originality/valueThe paper provides an attempt to find out propagation of benchmarking concepts in Indian context. The paper should be of interest to those researching or managing in the Indian manufacturing sector. This is one of the first studies on dissemination of benchmarking in developing countries and should encourage further research in these countries.

Corporate governance in the Indian manufacturing industry plays a crucial role in ensuring transparency, accountability, and ethical business practices. This abstract explores the significance of corporate governance within the context of Bajaj Auto, a leading automobile manufacturer in India. It highlights how Bajaj Auto has implemented robust governance frameworks to maintain investor confidence, comply with regulatory requirements, and foster sustainable growth. By focusing on board composition, stakeholder engagement, and risk management strategies, the study underscores Bajaj Auto's commitment to high governance standards, contributing to its reputation and operational efficiency in a competitive market. The findings demonstrate that effective corporate governance not only enhances corporate performance but also mitigates risks and promotes long-term stakeholder value in the Indian manufacturing sector. Corporate governance encompasses the systems, principles, and processes by which companies are directed and controlled. In the context of the Indian manufacturing industry, effective corporate governance is crucial for ensuring transparency, accountability, and sustainable growth. This study focuses on the role of corporate governance in the Indian manufacturing sector, with a special emphasis on Bajaj Auto, a leading player in the industry. In the manufacturing sector, robust corporate governance practices are essential for maintaining investor confidence, managing risks, and fostering innovation. Good governance helps companies navigate complex regulatory environments, adhere to ethical standards, and improve operational efficiencies.