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We consider a joint optimization problem of product platform design and scheduling on unrelated additive/subtractive hybrid machines, and seek to find efficient solution approaches to solve such problem.

We propose a mathematical formulation for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines, and develop a simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length to solve the problem.

The simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length (SAHH-osla) that we proposed can be quite efficient in solving the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

To the best of our knowledge, we are one of the first to consider both cost-related and time-related criteria for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

Due to the influence of complex and intersecting factors, self-governed public open spaces (POSs) (managed by local communities) are subject to collective action dilemmas such as tragedy of the commons (overexploitation), free-riding, underinvestment and mismanagement. This review paper adopts a multi-dimensional and multi-tier social-ecological system (SES) framework proposed by McGinnis and Ostrom, drawing on collective action theory to explore the key institutional-social-ecological factors that impact POS self-governance.

In this paper, Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was utilized to systematically screen and review the relevant literature for the period from 2000 to 2023 in three databases: Web of Science, Scopus and Google Scholar. A total of 57 papers were chosen for in-depth analysis.

The literature review identified and categorized several variables associated with the self-organizing system of POS; consequently, an SES-based POS management framework was developed for the first time, consisting of 114 institutional-social-ecological sub-variables from different dimensions and three levels. Compared to ecological factors, among others, governance organizations, property-rights systems, socioeconomic attributes and actors' knowledge of SES have been commonly and primarily studied.

There is still room for the refinement of the conceptual SES-based POS collective action framework over the time (by adding in new factors), and indefinitely empirical research validating those identified factors is also worth to be undertaken, particularly testing how SES factors and interaction variables affect the POS quality (collective action).

The findings of this study can provide local policy insights and POS management strategies based on the identification of specific SES factors for relevant managers. Moreover, this research makes significant theoretical contributions to the integration of the SES framework and collective action theory with POS governance studies.

The outbreak of the coronavirus pandemic (COVID-19) has severely disrupted businesses around the world. To address the impact of operational and strategic business disruptions, this paper contributes to the practice of a firm's management in terms of identifying the determinants of organizational resilience (OR) and creating a hierarchical model of the potential sources of a firm's adaptive capability.

A novel research framework integrating Pareto analysis, grey theory and total interpretive structural modeling (TISM) has been applied to, first, identify the sources of a company's resilience and, second, to determine contextual relations among these sources of OR.

The findings of the survey highlight three primary sources that allow companies to build companies' resilience: access to financial resources, digitization level and supply chain (SC) collaboration. The authors' model shows that resilience cannot be viewed as a particular feature but rather as a dynamic intertwined network of different co-dependent sources.

The proposed hierarchical model indicates that the most crucial sources of company's resilience in the recent pandemic are access to financial resources, digitization level and SC collaboration.

The study takes an original investigation on cognitive grounds, touching on the problem of firms' resilience to the unique nature of the crisis caused by the COVID-19 pandemic. The study also represents one of the few attempts to use integrated Pareto analysis, grey theory and TISM to examine this critical area of firm management.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

This paper examines gender diversity in the Australian valuation industry from the perspective of valuers in senior management and leadership roles and discusses gender diversity policies and practices in their organisations. Then, it explores the initiatives that can be implemented to improve gender diversity in the Australian valuation industry.

A focus group discussion was conducted with valuers in senior management and leadership roles from selected large valuation firms and government valuation agencies in Melbourne, Australia. Data collected through the focus group discussion was combined with secondary data sourced from journals, online articles and archival materials.

The findings reveal that whilst gender diversity in the Australian valuation industry has improved over the years, females remain underrepresented. Nonetheless, whilst some valuation companies have recognised the need to address the underrepresentation of women and introduced specific gender-focussed human resource policies and practices, these initiatives are not streamlined and implemented across the industry.

The study highlights the need for closer collaboration between key stakeholders such as universities, professional associations, valuation companies and government agencies in devising strategies to attract female talents into the valuation industry.

The paper is the first empirical study to assess gender diversity in the Australian valuation industry from the perspective of valuers in management and leadership roles. The proposed policies can inform future initiatives to improve gender diversity in the valuation industry.

For almost half a century, society has been aware of the existence of a glass ceiling, a term that describes the invisible barriers that hinder women’s access to power positions despite having equal or greater qualifications, skills and merits than their male counterparts. Nowadays, although there are signs of slow progress, women are still underrepresented in the upper echelons of large corporations and the risk of reversing the progress made in gender parity has increased because of the effects of the COVID-19 pandemic. This paper contributes to previous literature by analysing the impact that the uncertainty and cognitive effects associated with COVID-19 in 2020 had on the presence of women on the board of directors and whether this impact has been moderated by the regulatory and policy system on gender quotas in place at the time.

To test the authors' research hypotheses, the authors selected the major global companies worldwide with economic-financial and non-financial information available in the Thomson Reuters EIKON database over the 2015–2020 period. As a result, the authors' final sample is made up of 1,761 companies from 52 countries with different institutional settings that constitute an unbalanced data panel of 8,963 observations. The nature of the dependent variables requires the use of logistic regressions. The models incorporate the terms to control for any unobservable heterogeneity and the error term. Any endogeneity issues were addressed by considering the explanatory variables with a time lag.

The authors find that almost 30% of the companies downsized their boards in 2020. This decision resulted in more female than male directors being made redundant, causing a reversal in the fulfilment of gender quotas focussed on ensuring balanced boards with a female presence of 40% or more. This effect was enhanced in countries with hard-law regulation because the penalty for non-compliance with gender quotas had led to a significant increase in the size of these bodies in previous years through the inclusion of the required number of female directors. In contrast, the reduction in board size in soft-law countries does not differ from that in laissez-faire countries, lacking any moderating effect or impact on the number of female board members dismissed as a result of the pandemic.

This paper aims to contribute to current knowledge by analysing the impact that the countries' regulatory and normative systems on gender parity on boards of directors have had on the decisions made in relation to leadership positions, moderating the effects of the COVID-19 pandemic on gender equality at a global level.

This study aims to examine how environmental, social and governance (ESG) initiatives and ISO 14001, which is an internationally agreed standard to set out the requirements for an environmental management system, affect firm performance in the context of the Industry 4.0 supply chain.

The authors develop a new chance-constrained network data envelopment analysis (DEA) in the presence of non-positive data to estimate innovation, operational and profitability performances for three main relation groups (suppliers, partners and customers) in Microsoft's supply chain.

Results of this study show the following: (1) the application of ISO 14001 will reduce profitability but increase overall performance (OP); (2) ESG implementation has a convex U-shaped influence on profitability and OP, which means that firms will benefit when ESG investment goes beyond a particular level; (3) the nonlinear U-shape is presented in the E and G components, but not in the S of the individual ESG initiatives, and (4) only specific subcomponents of S and G in the subcomponent of individual ESG initiatives are nonlinearly connected to OP. Research's results reveal that the customer group has a higher performance value than the other two groups, which suggests that this group will create competitive advantages for Microsoft.

Overall, the authors provide an insightful viewpoint into supply chain management by examining the ESG initiatives, ISO 14001 and performances of Microsoft's supply chain.

Accounting scandals and earnings management problems at large firms such as Global Crossing and Enron have resulted in lots of wealth loss not only to corporate investors but also led tremendous damage to societies. Hence, policymakers and academic researchers have started to explore mechanisms to prevent improprieties in financial reporting and further enhance firm value. Using data from United States (US)-listed companies between 2000 and 2018, this article explores the effect of ex-military executives on earnings quality, the role of financial analysts in their interplay and the firm value implication of earnings quality driven by ex-military executives.

This study employs a firm fixed-effects model to validate the main conjecture and adopts the weighted least squares, Granger causality analysis, instrumental variable approach, propensity score matching, entropy balancing approach and dynamic system Generalized Method of Moments (GMM) estimator to address robustness and endogeneity issues.

Authors reveal that companies run by ex-military senior executives exhibit lower levels of accruals-based and real earnings management than those without. The effect of management military leadership on constraining earnings management is more prominent for companies with low analyst coverage, suggesting that the military experience of executives could be a substitute for external monitoring. Authors also find that these ethical managers alleviate the negative impact of earnings management on firm value and that companies managed by these managers exhibit higher firm performance.

This study highlights the importance of the intrinsic motivation behind the effect of military experience on senior managers' personalities and offers essential stakeholder-related implications regarding the effect of military experience. The military experience of senior managers helps facilitate the attainment of broader corporate governance and economic objectives.

This article adds new insights to the literature on the role of managerial military experience in decision-making processes, financial reporting outcomes and firm performance by employing the upper echelons and imprinting theoretical perspectives.

This study aims to document the time varying risk premia for market, size, value and momentum factors for an emerging market using a sophisticated conditional asset pricing model. The focus of this study is Turkish stock market denominated in local currency with its peculiar risk premia.

The authors employ Gagliardini et al.'s (2016) econometric method that uses cross-sectional and time series information simultaneously to infer the path of risk premia from individual stocks.

Using this methodology, the authors assess several conditioning information and conclude that local dividend yield, inflation and exchange rates have the most explanatory power. The authors document the time varying risk premia in Turkey over three decades.

Existing studies on dynamic estimation of risk premia lack a consensus as to which state variables should be included and to what extent they impact the magnitude of the premium. The authors extend the conditioning information set beyond the ones existing in the literature to determine variables that are specifically important for an emerging market.

This study empirically explores the intraday price discovery mechanism and volatility transmission effect between the dual-listed Indian Nifty index futures traded simultaneously on the onshore Indian exchange, National Stock Exchange (NSE) and offshore Singapore Exchange (SGX) and its spot market by using high-frequency data.

This study applies the vector error correction model to analyze the lead-lag relationship in price discovery among three markets. The contributions of individual markets in assimilating new information into prices are measured using various measures, Hasbrouck's (1995) information share, Lien and Shrestha's (2009) modified information share and Gonzalo and Granger's (1995) component share. Additionally, the Granger causality test is conducted to determine the causal relationship. Lastly, the BEKK-GARCH specification is employed to analyze the volatility transmission.

This study provides robust evidence that Nifty futures lead the spot in price discovery. The offshore SGX Nifty futures consistently ranked first in contributing to price discovery, followed by onshore NSE Nifty futures and finally by the spot. Empirical results also show unidirectional causality and volatility transmission from Nifty futures to spot, as well as bidirectional causal relationship and volatility spillovers between NSE and SGX Nifty futures. These novel findings provide fresh insights into the informational efficiency of the dual-listed Indian Nifty futures, which is distinct from previous literature.

These findings can potentially help market participants, policymakers, stock exchanges and regulators.

Unlike previous studies in this area, this is the first study that empirically examines the intraday price discovery mechanism and volatility spillover between the dual-listed futures markets and its spot market using 5-min overlapping price data and trivariate econometric models.