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In the present knowledge economy, intellectual capital (IC) is regarded as one of the significant determinants of efficiency, profitability, and ultimately value of a firm. This chapter empirically investigates the ramifications of the IC on the level of efficiency of the firm. In addition, exploration of the changing dynamics in the relationship between IC and firm level efficiency in the face of global economic crisis is of special interest of this chapter. In attaining the objectives of the study, a comprehensive database of 299 manufacturing firms (chosen randomly from a stratification of six BSE manufacturing industry subsectors) were utilized during the period from 1999–2000 to 2013–2014. Firm level efficiency scores and implications of IC (as measured by employing Pulic's Value Added Intellectual Capital Model) on the level of efficiency of the firms were examined simultaneously using Stochastic Frontier Analysis. Empirical results revealed that IC significantly determines the efficiency of the manufacturing firms during the period of study. However, the impact of financial crisis was not robust in changing the synergy between efficiency and IC. Size, age, and leverage were also found to be significant determinants of efficiency during the period of study.

World economies including India have been moving toward recession. To combat this recession more employment generation through investment is required in a highly populated economy like India. Since unorganized manufacturing enterprises (UMEs) provide employment to a huge mass in India, therefore its growth and productivity is a matter of concern in the Indian economy. The present study analyzes the growth and productivity of UMEs on the basis of the latest two rounds of NSSO unit level data incorporating all states and union territories (UTs) of India. It reveals that the growth of UMEs, employment, gross value added (GVA) and fixed assets widely varied across states/UTs, and these growth rates were substantially high in a number of states during 2010–11 and 2015–16. In most of the states/UTs the labor productivity of UMEs has increased significantly but not the capital productivity. Our analysis supports the theoretical relationship among growth of employment, GVA, and labor productivity. Therefore, the government has to make deliberate attempts to increase the growth of UMEs on one side and raise productivities of UMEs through skill developments on the other side to overcome the problem of unemployment in particular and expedite the growth of the Indian economy in general to combat the global economic recession.

The unorganised manufacturing sector contributes one third share of overall manufacturing employment and one fifth share of gross value added of the manufacturing sector. Despite its important role in large-scale employment generation, this sector is neglected by the researchers as well as by the policy makers as compared to the focus given on the organised manufacturing sector. The issues of energy intensity, environment emissions and growth of unorganised manufacturing enterprises (UMEs) remain unexplored. The present chapter attempts to estimate the CO₂ emission and emission intensity (EI) across UMEs on the basis of NSSO Unit Level data of 62nd, 67th and 73rd rounds. It also analyses the growth of UMEs in relation to CO₂ emission and EI. The nature of the sector is very much dispersed. Our study reveals that a portion of unorganised enterprises did not use any energy in their production activities and used manually operated instruments like – handlooms, weaving machines, hand-operated oil and rice mills, etc. The main energy inputs of UMEs are electricity and fuel & lubricants. The CO₂ emission is relatively less in UMEs compared to organised manufacturing enterprises. Across the unorganised manufacturing industries, the higher CO₂ emission are observed in manufacturing of food product industry and other non-metallic mineral industry. The study found that CO₂ EI of UMEs depends on firm-level characteristics like perennial nature, establishment type, urban location and expanding growth status. However, capital intensive UMEs are more polluting.

The purpose of this study is to measure the technical efficiency of 20 Algerian insurance companies from 2016 to 2020, by using slacks-based measure (slacks-based measure [SBM] data envelopment analysis [DEA]) model. This research aims to provide a comprehensive assessment of this companies' efficiency, taking into account both the desirable and undesirable outputs.

The study uses a nonoriented, SBM model with the assumption of constant returns to scale to estimate the technical efficiency of commercial insurance companies over a five-year period. The inputs used are labor expense, agent expense and investments, while the outputs included are gross premiums and investment income as desirable outputs and gross claims as undesirable output.

Among 20 insurance companies evaluated, only 5 companies consistently achieved technical efficiency during the study period (Caisse Nationale de Mutualité Agricole [CNMA], MACIR, CARDIF, MUTUALISTE and AGLIC); so they represent the best practices in the Algerian insurance sector, with overall average of the technical efficiency is 81%. However, the reference sets analysis showed that CNMA and AGLIC had high robustness. Also, the results demonstrate the impact of ignoring the undesirable outputs on the accuracy of the assessment.

The sample of the study consists of the active insurance companies in Algeria, based on the Annual Insurance Reports of Algeria; there are 20 companies as shown in the table. The data are taken from the annual reports of insurance companies during the 2020 period, issued by the Algerian Ministry of Finance.

The challenge for insurance company is how to find a balance between reducing claims paid and simultaneously improving the quality of insurance services. In fact, it is observed that studies evaluating their efficiency ignore claims in the analysis process. Therefore, the study highlights the importance of considering undesirable outputs within the DEA framework; this allows for a more accurate assessment of the company's performance and helps in improvement. Furthermore, although the insurance sector plays a crucial role, it has not received enough research attention compared to other financial sectors, especially in Arab and developing countries.

The literature on efficiency assessment in the insurance companies shows a lack of addressing undesirable outputs (such as claims) within the DEA framework; so this study aims at bridging this research gap. Also, the study provides an overview of the efficiency of Algerian insurance companies.

The objective of this work is to determine the relationship between human capital and artisanal innovation. Nowadays, in Tonalá Jalisco, artisanal pieces are produced in an innovative way, either by using ceramic or any variant of the mud technique, but a substantial part of the business is what makes innovative business thinking possible. The Intellectus Model, created by Eduardo Bueno in 2011, is used as a reference, distinguishing intellectual capital in three types of capital. But for the purpose of this study, we have only analyzed the relationship of human capital with respect to artisanal innovation. The study was conducted in 2018 on 73 craft economic units. Using the Pearson chi-square technique and applying the Statistical Package for the Social Sciences (SPSS) program, the qualitative relationship between innovation and human capital was analyzed. The result shows a positive relationship between human capital and innovation.

Existing studies about airline productivity and cost competitiveness are focusing on combination carriers, transporting both passengers and cargo in the same aircraft and with the same inputs. Scientific research about the cost structure and productive performance of all-cargo carriers is very limited. However, the importance of air cargo and express transport in our globalized economy, the high volatility of all-cargo carriers (especially since the 2008 economic crisis), and the success of integrators show the need for more scientific attention to this industry. This chapter aims at benchmarking the productivity and cost competitiveness of US integrated and non-integrated cargo carriers, based on total factor productivity and unit cost competitiveness analyses. The results unveil a positive correlation between productivity on the one hand and the size of the carrier and its average stage length on the other hand, indicating economies of scale. Correcting the results for such factors beyond managerial control and input prices allows us to measure the impact of the crisis and the consequences for the management of the individual carriers.

This chapter examines the impact of banking competition, bank regulation, and the global financial crisis (GFC) of 2008–2009 on banks’ productivity changes. For the empirical analysis, I apply a semi-parametric two-step approach of Malmquist index estimates and bootstrap regression to a cross-country panel data of 8,451 commercial banks from 82 countries over the period 2004–2012. Empirical results show that (1) banking competition and capital regulation significantly enhance bank productivity, (2) a tighter bank supervision have a positive impact on bank productivity, and (3) bank productivity decreases during the GFC, but starts to increase as the GFC recovers. I also present consistent evidence that commercial banks in countries with better national governance have higher productivity growth before, during and after the GFC.

This study is an attempt to estimate the output growth and total factor productivity growth (TFPG) in Indian manufacturing industry. Most of the developed nations have been facing economic depression in its output and employment growth frequently which led to several worldwide recessions and developing nations have also been affected by these. Our objective is to examine a possible way of mitigating economic recession in the light of Indian experience. In these connections we have tried to establish a link between TFPG and indicators of economic growth like export, GDP, employment, etc. We have computed TFPG of Indian manufacturing industry for last 30 years. On an average TFPG of Indian manufacturing industry has been found negative with a declining trend. Time series analysis of our study reveals that all the variables are stationary at first difference. They are also found to be co-integrated. On the basis of volumes of India's exports of manufacturing products in 2017, we have selected top 27 destination countries. More than 60% of Indian's manufacturing products were exported to these countries in this year. We have conducted panel data analysis to find the relation between TFPG and growth of India's export. The result shows that there has been a positive and significant relation between these two. This study also found that there has been a positive relation between growth of gross value added and employment growth in Indian manufacturing industry. So, TFPG may be a useful way to mitigate economic recession.

The study estimates total factor productivity growth (TFPG) and its components of the 4-digit manufacturing industries of chemical and chemical products in India from 1998–1999 to 2017–2018, pre-economic crises period (from 1998–1999 to 2007–2008) and post-economic crises period (from 2008–2009 to 2017–2018) using frontier approaches, that is, data envelope analysis DEA and stochastic frontier approach (SFA). The components of TFPG are technological progress (TP), technical efficiency change (TEC) and economic scale change (SC). It is found that the growth rates of total factor productivity (TFP) in most of the 4-digit industries of chemical and chemical products in India increased during the post-economic crises period (from 2008–2009 to 2017–2018) and the increase in TFPG of them during that period is mainly accounted for by the increase in TP of the same during that period. The TEC of almost all the industries remains the same, however, declined during the post-economic crises (from 2008–2009 to 2017–2018) and SC of them remains very low or even negative during the aforementioned study periods.

To address management issues in the development of flexible production systems in the enterprises of knowledge-intensive industries, this chapter considers four basic approaches to planning production processes. Based on these approaches, the methodology of the agent-based approach, which satisfies the fundamental requirements of today's production systems, is formulated, with much attention paid to the rules of dispatching as a key tool of operational control over the production plan and its implementation. The advantage of simulation-based approaches is that they can dynamically adjust the ongoing integration of planning, depending on the state of flexible production systems, in the use of combined approaches and methods of management of production processes.