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This systematic literature review analyzes the academic literature to understand SC risk and resilience across different organizational sizes and industries. The academic literature has well discussed the causes of supply chain (SC) risk events, the impact of SC disruptions, and associated plans for SC resilience. However, the literature remains fragmented on the role of two fundamental elements in achieving SC resilience: the firm's size and the firm's industry as firms' contingent factors. Therefore, it is important to investigate and highlight SC resilience differences by size and industry type to establish more resilient firms.

Building upon the contingent resource-based view of the firm, the authors posit that organizational factors such as size and industry sector have important roles in developing organizational resilience capabilities. This systematic literature review and analysis is based on the structural and systematic analysis of high-ranked peer-reviewed journal papers from January 2000 to June 2021 collected through three global scientific databases (i.e. ProQuest, ScienceDirect, and Google Scholar) using relevant keywords.

This systematic literature review of 230 high-quality articles shows that SC risk events can be categorized into demand, supply, organizational, operational, environmental, and network/control risk events. This study suggests that the SC resilience plans developed by startups, small and mdium-sized enterprises (SMEs), and large organizations are not necessarily the same as those of large enterprises. While collaboration and networking and risk management are the most crucial resilience capabilities for all firms, applying lean and quality management principles and utilizing information technology are more crucial for SMEs. For large firms, knowledge management and contingency planning are more important.

This study provides a comprehensive review of the literature on SC resilience plans across different organizational sizes and industries, offering new insights into the nature and dynamics of startups', SMEs', and large enterprises' SC resilience in different industries. The study highlights the need for further investigation of SC risk and resilience for startups, SMEs, and different industries on a more detailed level using empirical data. This study’s findings have important implications for researchers and practitioners and guide the development of effective SC resilience strategies for different types of firms.

While previous operations management literature acknowledges the positive influence of Lean and Industry (I4.0) on performance, recent studies examining the synergy between these two factors have produced inconsistent and contradictory results. Therefore, this study aims to provide a comprehensive understanding of the effect of Lean and I4.0 synergy on firm performance.

This study utilised a meta-analysis approach, examining 23 empirical studies exploring multiple effects of the Lean and I4.0 synergy on firm performance. Multiple subgroup analyses were conducted to assess the contradictory outcomes and identify in what conditions such synergy may achieve performance.

The results affirm the prevailing positivist perspective among most scholars regarding the positive influence of the Lean and I4.0 synergy on firm performance. However, the overall effect size derived from the studies indicates a weak relationship, suggesting that this synergy alone is not the sole determinant factor of firm performance. In addition, the subgroup analyses reveal the presence of contingent conditions that may affect the performance outcomes when integrating Lean and I4.0, as most effects exhibit a weak relationship.

This study represents the first meta-analysis investigating the relationship between the Lean and I4.0 synergy on firm performance. By shedding light on the contradictory effects often depicted in the operations management literature, this study provides a critical reflection for researchers who tend to adopt an overly optimistic view of such synergy.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.

Purpose: The research determines how the COVID-19 pandemic affected India’s burgeoning education technology sector and how the new normal responded to this advancement worldwide.

Need for Study: India’s education sector saw a boom in Ed-Tech funding during the pandemic. The Indian Education industry adopted technology as a partner and succeeded in being called as the Ed-Tech capital of the world. The country has a strategic edge in online education that, if explored and researched upon, can be deployed for market growth at a global level.

Research Methodology: The researcher prioritised rigorous original quantitative and qualitative methods of investigation on technology applications in educational contexts during COVID-19 pandemic and drew its conclusions after conducting a comprehensive literature review and collecting and analysing the data from numerous journals and published expert articles on the sector.

Findings: The study found that despite the global pandemic, the Ed-Tech industry was an expanding marketplace for start-ups in India. After the pandemic, the market expanded rapidly, and by 2025, it is expected to have quadrupled in size, expenditure, and investment. It is expected that the global e-learning business, which the outbreak of the COVID-19 pandemic has bolstered, will grow to over 400 billion US dollars by 2026.

Practical Implications: The study sets forth the various Ed-Tech categories, outlining their user bases, growth projections, and the innovative technologies employed in developing these products. The research’s long-term investment projections are envisioned to aid consultants in positioning themselves for profitable operations in the era of digital Ed-Tech disruption worldwide.

The authors' work aims to identify the employer-specific drivers of the college (or university) wage gap, which has been identified as one of the major determinants of the dynamics of overall wage and income inequality in the past decades. The authors focus on three employer-level features that can be associated with asymmetries in the employment relation orientation adopted for college and non-college-educated employees: (1) size, (2) the share of standard employment and (3) the pervasiveness of incentive pay schemes.

The authors' establishment-level analysis (data from the Basic Survey on Wage Structure (BSWS), 2005–2018) focusses on Japan, an economy characterised by many unique economic and institutional features relevant to the aims of the authors' analysis. The authors use an adjusted measure of firm-specific college wage premium, which is not biased by confounding individual and establishment-level factors and reflects unobservable characteristics of employees that determine the payment of a premium. The authors' empirical methods account for the complexity of the relationships they investigate, and the authors test their baseline outcomes with econometric approaches (propensity score methods) able to address crucial identification issues related to endogeneity and reverse causality.

The authors' findings indicate that larger establishment size, a larger share of regular workers and more pervasive implementation of IPSs for college workers tend to increase the college wage gap once all observable workers, job and establishment characteristics are controlled for. This evidence corroborates the authors' hypotheses that a larger establishment size, a higher share of regular workers and a more developed set-up of performance pay schemes for college workers are associated with a better capacity of employers to attract and keep highly educated employees with unobservable characteristics that justify a wage premium above average market levels. The authors provide empirical evidence on how three relevant establishment-level characteristics shape the heterogeneity of the (adjusted) college wage observed across organisations.

The authors' contribution to the existing knowledge is threefold. First, the authors combine the economics and management/organisation literature to develop new insights that underpin the authors' testable empirical hypotheses. This enables the authors to shed light on employer-level drivers of wage differentials (size, workforce composition, implementation of performance-pay schemes) related to many structural, institutional and strategic dimensions. The second contribution lies in the authors' measure of the “adjusted” college wage gap, which is calculated on the component of individual wages that differs between observationally identical workers in the same establishment. As such, the metric captures unobservable workers' characteristics that can generate a wage premium/penalty. Third, the authors provide empirical evidence on how three relevant establishment-level characteristics shape the heterogeneity of the (adjusted) college wage observed across organisations.

Following the COVID-19 outbreak, there are concerns whether economies are becoming farther from equality and competency. While this matters to every economy, it is more crucial for developing ones who already suffer from income inequalities and lack of competency. The purpose of this paper is to address this issue.

This study uses an administrative data from the Iran's Social Security Organization (ISSO) that provides insurance to workers entitled to the Labor Law of Iran. The data contain more than 7,000,000 workers. The authors assess heterogeneous impact of the first wave of the pandemic by firms' size and average payment.

The authors’ estimation results indicate that, following the initiation of the pandemic, the workers whose corresponding firms are smaller, overall, are more prone to the pandemic and are more likely to submit a request for unemployment benefits. However, the relation is neither homogeneous across sectors nor linear among micro-sized firms. Few sectors indicate a positive relationship between size and likelihood of request submission, including cultural activity, shoemaking and clothing sectors. Besides the size, the authors investigate whether pay grades could explain the probability of becoming unemployed after the pandemic. Results show that workers whose corresponding firms pay less are more likely to submit a request. This is robust within different sectors.

The ISSO dataset is not a panel, so the authors cannot employ methods of causal inferences. The authors’ results should be seen as correlation; however, due to exogeneity and sharpness of the pandemic the result infers to some degree of causality. The data does not cover the informal sector, so the estimates are at lower boundary.

Administrative data on unemployment benefits during COVID-19 show that the pandemic interferes with competition by forcing low-paid workers and small firms to exit the market. This is an alarm for the competition in every economy, specially developing ones.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

The purpose is to examine the relationship between entrepreneurs’ exit strategies and modes of entry. The topic of exit strategies in the context of approaching retirement warrants further attention.

We apply logistic regression to analyse 1,192 responses to an online survey of firms with entrepreneurs aged over 55.

Family successors are more likely to choose family succession and buyers to choose to sell, but the association between founding and exit mode cannot be confirmed. Firm size is also significant. Our findings suggest that entry and exit via a business transfer are linked. Entrepreneurs might be influenced by their form of entry when choosing their exit strategy.

The data were collected from a single European country, limiting generalisation. Future research should incorporate intervening variables not controlled for here, such as, entrepreneurial experience. Future studies should also seek to test the existence of imprinting directly, as it is implied rather than verified here.

If the entry mode has a lasting effect on the entrepreneur as our results suggest, thus influencing the exit strategy selected, entrepreneurs could benefit from greater awareness of the imprinting mechanism. Increasing awareness of imprinted biases could unlock the benefits of exit strategies previously overlooked.

The study is the first to consider sale, family succession and liquidation as exit strategies in relation to the original entry mode of ageing owners. It contributes to the understanding of exit strategies of ageing entrepreneurs and proposes using entrepreneurial learning and imprinting as lenses to clarify the phenomenon.

This study investigates the extent to which performance measures (PMs) are used, the relationship between multidimensional PMs and firm performance and the factors related to firms' PM use.

The authors surveyed a sample of Malaysian manufacturing firms. Participants responded to a questionnaire indicating their use of PMs, firm performance, level of managerial commitment, degree of environmental uncertainty and firm's use of technology.

The results indicate a high degree of PM use related to financial indicators, internal efficiency and customer-related metrics. The results also demonstrate that firm performance has significant positive relationships with use of PMs related to quality and customers, efficiency, innovativeness and social responsibility, as well as comprehensive PM use. Industry variation, firm size, technology use and environmental uncertainty are also significantly related to PM use.

Performance measurement systems (PMSs) are an important tool for improving organisational strategy in rapidly changing markets. These findings underscore the significant role of PMSs in manufacturing firms' performance, including emerging economies. The results suggest that individual PMS approaches should align with each firm's evolving needs and the characteristics of the sector and environment in which each firm operates.

This study advances understandings of the contingency approach to PMSs in manufacturing environments.

This paper presents an analytical framework for modeling and measuring strategic alignment. The resource-product-market (RPM) model is introduced as a means of representing the alignment of the firm's internal resources with its product lines and external markets. A strategic alignment index is defined to measure the degree of alignment represented by a model.

The RPM model is derived as an extension of prior research on diversification indexes. The strategic alignment index is mathematically defined and the properties of the model are characterized using graph theory. The approach is illustrated for two example firms.

The RPM model is flexible and can be used with different types and measures of resources, products and markets. The model represents strategy in a structural manner addressing a vertical type of alignment. The index ranges continuously from 0 to 1.0, providing a useful scale for measurement and comparison.

Practitioners may use RPM modeling to assess the current alignment of their respective firms and to identify strategic alternatives which increase alignment through a taxonomy of 13 strategic moves. The results of applying the model to ten firms are summarized.

The paper contributes to the literature by providing a new method for modeling firm strategy which integrates resource and industry views, thereby enabling a measurement of their alignment. The paper is also novel in the application of graph theory to management.