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Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

This study aims to estimate the quality-adjusted changes in residential mobile consumer prices by controlling for the changes in the relevant service characteristics and quality, in a case study on Hungary between 2015 and 2021; compare the results with changes measured by the traditionally calculated official telecommunications price index of the Statistical Office; and discuss separating the hedonic price changes from the effect of a specific government intervention that occurred in Hungary, namely, the significant reduction in the value added tax rate (VAT) levied on internet services.

Since the price of commercial mobile offers does not directly reflect the continuous improvements in service characteristics and functionalities over time, the price changes need to be adjusted for changes in quality. The authors use hedonic regression analysis to address this issue.

The results show significant hedonic price changes over the observed seven-year period of over 30%, which turns out to be primarily driven by the significant developments in the comprising service characteristics and not the VAT policy change.

This paper contributes to the literature on hedonic price analyses on complex telecommunications service plans and enhances this methodology by using weights and analysing the content-related features of the mobile packages.

The global financial crisis (GFC) of 2007–2008 had far-reaching consequences for the global economy, triggering widespread economic turmoil. We use the event-study method to investigate whether investors priced the effect of significant events before the Lehman Brothers' bankruptcy in European and Asia-Pacific banks. Abnormal returns on the event days range from −4.32% to 5.03% in Europe and −5.13% to 6.57% in Asia-Pacific countries. When Lehman Brothers went bankrupt on September 15, 2008, abnormal returns averaged the lowest at −4.32% in Europe and −5.13% in Asia-Pacific countries. The significant abnormal returns show that Lehman Brothers' collapse was a turning point, and investors paid attention to the precrisis events as warning signs of the oncoming crisis.

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency is determined by the configuration of factor prices. A dynamic model of the firm is developed under the assumption that managerial skill contributes to technical efficiency. Dynamic analysis shows that the firm can never be technically efficient if it maximizes profits, the steady state is always inefficient, and it is locally stable. In terms of empirical analysis, we show how likelihood-based methods can be used to uncover, in a semi-non-parametric manner, important features of the inefficiency-management relationship using a flexible functional form accounting for the endogeneity of inputs in a production function. Managerial compensation can also be identified and estimated using the new techniques. The new empirical methodology is applied in a data set previously analyzed by Bloom and van Reenen (2007) on managerial practices of manufacturing firms in the UK, US, France and Germany.

The purpose of this paper is to critically examine the multinational oil companies’ (MOCs) corporate social responsibility (CSR) initiatives in Nigeria. Its special focus is to investigate the impact of the global memorandum of understanding (GMoU) on mainstreaming gender sensitivity in cash crop market supply chains in the Niger Delta region of Nigeria.

This paper adopts an explanatory research design with a mixed method to answer the research questions and test the hypotheses. A total of 1,200 rural women respondents were sampled across the Niger Delta region.

Results from the use of a combined logit model and propensity score matching indicate a significant relationship between the GMoU model and mainstreaming gender sensitivity in cash crop market supply chains in the Niger Delta.

This study implies that MOCs’ CSR interventions that improve women’s access to land and encourage better integration of food markets through improved roads and increased mobile networks would enable women to engage in cash crop production.

This implies that improving access to credit through GMoU cluster farming targeted at female farmers would improve access to finance and extension services for women in cash crop production in the Niger Delta.

This research contributes to the gender debate in the agricultural value chain from a CSR perspective in developing countries and is rational for demands for social projects by host communities. It concludes that businesses have an obligation to help solve problems of public concern.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

To elaborate the nature of fact-checking in the domain of political information by examining how fact-checkers assess the validity of claims concerning the Russo-Ukrainian conflict and how they support their assessments by drawing on evidence acquired from diverse sources of information.

Descriptive quantitative and qualitative content analysis of 128 reports written by the fact-checkers of Snopes – an established fact-checking organisation – during the period of 24 February 2022 – 28 June, 2023. For the analysis, nine evaluation grounds were identified, most of them inductively from the empirical material. It was examined how the fact-checkers employed such grounds while assessing the validity of claims and how the assessments were bolstered by evidence acquired from information sources such as newspapers.

Of the 128 reports, the share of assessments indicative of the invalidity of the claims was 54.7%, while the share of positive ratings was 26.7%. The share of mixed assessments was 15.6%. In the fact-checking, two evaluation grounds, that is, the correctness of information and verifiability of an event presented in a claim formed the basis for the assessment. Depending on the topic of the claim, grounds such as temporal and spatial compatibility, as well as comparison by similarity and difference occupied a central role. Most popular sources of information offering evidence for the assessments include statements of government representatives, videos and photographs shared in social media, newspapers and television programmes.

As the study concentrated on fact-checking dealing with political information about a specific issue, the findings cannot be extended to concern the fact-checking practices in other contexts.

The study is among the first to characterise how fact-checkers employ evaluation grounds of diverse kind while assessing the validity of political information.

The purpose of this empirical study is to enable a better understanding of the construct sustainability-oriented entrepreneurial intentions (SEI) and thereby promote sustainable entrepreneurship. It aims to examine the significance of work values (extrinsic rewards, intrinsic rewards and job security) as antecedents of SEI and to test the mediating effect of three constructs derived from the theory of planned behaviour – attitude towards sustainability, perceived entrepreneurial desirability and perceived entrepreneurial feasibility on the relationships between work values and SEI.

Confirmatory factor analysis and exploratory factor analysis were performed using analysis of moment structures v27 and statistical package for social science v28 on data obtained from the survey of young individuals of India. The respondents were students enrolled in higher education programmes.

All the identified antecedents (extrinsic rewards, intrinsic rewards, job security and theory of planned behaviour constructs) were found to be statistically significant. The partial mediating effect of the theory of planned behaviour constructs was also reported.

This empirical work leads to the theoretical advancement of the emerging construct, SEI, by presenting evidence of the significant individual-level antecedents of the construct. The results lead to recommendations for policymakers and educators to design strategies to strengthen SEI, thereby expanding the adoption of sustainable entrepreneurship.