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This paper investigates the short-term market impact of the beginning of the military conflict between Russia and Ukraine (February 24, 2022) on a set of airline stocks listed.

This study uses an event study methodology, cross-section analyses and interaction effects to study the effect of the war on airline stock prices and firm-specific characteristics that explain the cumulative abnormal return.

The authors observe a negative and statistically significant stock price reaction at and around the beginning of the military conflict between Russia and Ukraine, for 74 listed airlines. These results are consistent with investment portfolio rebalancing and asset pricing perspective. Moreover, this study's results show a higher negative stock market reaction for airlines based in Europe. Empirical evidence suggests the existence of a “proximity penalty” for European companies. Finally, this study's results provide insights into which airline-specific characteristics emerge as value drivers. Larger, well-capitalized (high liquidity and low debt) and profitable airlines firms with less institutional ownership have superior stock market returns and show more able to handle with the losses resulting from the war.

This paper fills a gap in the literature about the impact of the Russia–Ukraine war on the airline industry.

This study investigates barriers to social impact bond (SIB) implementation through a review of academic and gray literature. A SIB is a type of public policy instrument that leverages payment for performance (P4P), contracting together with private investments in the delivery of welfare programs. Outcome-based contracts, such as SIBs, are gaining attraction for public service providers in developed countries, but research regarding their implementation remains underexplored both empirically and theoretically.

A literature review is conducted in which two types of documents are included: (1) empirical research papers and (2) evaluations of completed SIB projects. In total, 43 documents have been investigated. The study engages in a comparative design where insights across sectors (healthcare, social care and employment/education), are leveraged. The insights rest on evidence from the UK and US.

The investigation reveals five types of barriers to SIB implementation related to: (1) the SIB model, (2) organizational competencies, (3) data infrastructure, (4) stakeholder engagement and (5) the institutional context. The study discusses ways of managing these barriers and develops a conceptual framework for empirically investigating SIB implementation.

This study is the first academic paper to systematically assess insights regarding the implementation of SIBs. Also, the article proposes a conceptual framework for investigating SIB implementation.

At the virus' US epicenter, New York City, teachers experienced the impact of the pandemic firsthand in real time. Consistent with intensification (Apple, 1986), as school struggles to adapt to a rapidly changing social and educational landscape, socioemotional stressors and occupational responsibilities increase. Through the metaphoric (Craig, 2018) image of a candle, and using the tools of narrative inquiry (Connelly & Clandinin, 1990) – broadening, burrowing, storying, and restorying – we surface four teachers' lived experiences in a year filled with incredible grief and loss, socio-political-cultural trauma, racial strife, and personal-professional challenges to show their resolve and resiliency to persevere through and beyond burning out.

Since conducting agile strategies provides sustainable passenger satisfaction and revenue by replacing applied policies with more profitable ones rapidly, the focus of this study is to evaluate agile attributes for managing low-cost carriers (LCCs) operations by means of resources and competences based on dynamic capabilities built on resource-based view (RBV) theory and to achieve sustainable competitive advantage in a volatile and dynamic air transport environment. LCCs in Turkey are also evaluated in this study since the competition among LCCs is high to gain market share and they can adapt quickly to all kinds of circumstances.

Two well-known Multi-Criteria Decision-Making Methods (MCDM) named as the Stepwise Weight Assessment Ratio Analysis (SWARA) and multi-attributive border approximation area comparison (MABAC) methods by employing Picture fuzzy sets (PiFS) are employed to determine weight of agile attributes and superiority of LCCs based on agile attributes in the market, respectively. To check the consistency and robustness of the results for the proposed approach, comparative and sensitivity analysis are performed at the end of the study.

While the ranking orders of agile attributes are Strategic Responsiveness (AG1), Financial Management (AG4), Quality (AG2), Digital integration (AG3) and Reliability (AG5), respectively, LCC2 is selected as the best agile airline company in Turkey with respect to agile attributes. SWARA and MABAC method based on PiFS is appropriate and effective method to evaluate agile attributes that has important reference value for the airline companies in aviation industry.

The findings of this study will support managers in the airline industry to conduct airline operations more flexibly and effectively to take sustainable competitive advantage in unexpected and dynamic environment.

To the author' best knowledge, this study is the first developed to identify the attributes necessary to increase agility in LCCs. Thus, as a systematic tool, a framework is developed for the implementation of agile attributes to achieve sustainable competitive advantage in the airline industry and presented a roadmap for airline managers to deal with crises and challenging situations by satisfying customer and increasing competitiveness.

The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN).

To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers.

The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%).

This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions.

This study enhances understanding of COVID-19’s impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts.

The purpose of this paper is to investigate the potential synergy between companies’ sustainable supply chain management (SSCM) activities and their supply chain resilience (SCRES). The authors propose hypotheses about the impact of buying companies SSCM activities on the inflicted damage by unexpected supply chain disruptions and the recovery time afterwards and test these empirically using data from companies during the global COVID-19 pandemic.

The authors investigate a sample of 231 of the largest publicly traded companies in the European Union with 4.158 firm-year observations. For the analysis, the authors generate variables capturing the companies’ intensity and years of experience of their SSCM activities targeted at the supply chain and run regression analyses on the inflicted damage due to the COVID-19 pandemic and the recovery time after the disruption.

Buying companies’ SSCM activities have a positive effect on their SCRES. The damage inflicted by unexpected supply chain disruptions is lower when companies have higher levels of SSCM and longer experience with it. The recovery time afterwards is significantly reduced by longer experience with SSCM efforts.

The authors suggest SCRES is reinforced by transparency, situational awareness, social capital and collaboration resulting from companies SSCM activities translate into increased SCRES.

The authors show that companies with superior SSCM are more resilient in a crisis and conclude that, therefore, companies should invest in SSCM to prevent future supply disruptions.

To the best of the authors’ knowledge, this is the first empirical study analyzing a data set of multi-industry companies, linking their SSCM activities to SCRES during the pandemic.

The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.

Despite extensive research on supply chain management (SCM), the literature lacks a perspective to empirically assess the importance of poverty alleviation in social business. Using resources dependence theory, the purpose of this study is to analyze to ascertain whether financial innovation has a powerful solution for business sustainability and, hence, poverty alleviation in developing countries. This study reviews the financial innovations offered by Dompet Dhuafa Republika in integrated supply chain management (ISCM) of smallholder livestock business through Tebar Hewan Kurban (Spreading Sacrificial Animals) program to overcome capital and marketing problems at the farmer level and distribute Qurban meat to the recipients.

This study was conducted using descriptive qualitative method. The data were obtained through a field survey, by interviewing two crowdfunding-based investment companies, 250 partner farmers, program managers and assistants, marketing partners, donors/consumers/person who sacrifice and Mustahik (recipients of Qurban meat) involved in program implementation, using purposive sampling method. Focus group discussion was conducted with selected panelists to validate the results of the field survey.

The results of this study showed that the Tebar Hewan Kurban program provides greater benefits to farmers, while increasing the distribution of Qurban meat to be more equitable. The role of moneylenders and middlemen can also be eliminated. Donors feel satisfied because their goals are fulfilled in the Qurban ritual. Program implementers and investors also got decent returns. ISCM is very feasible to be developed on a wider scale, to improve the welfare of farmers or fishermen.

This study used a set of samples of the assisted areas from only one institution, which may lead to institution-specific results. Although the sample is small, the results of this study are expected to provide new insights into the implementation of the Qurban, which will provide more profits and benefits for partner farmers. In broader practice, the program flow is worth considering compared to similar programs in other institutions, in Indonesia or abroad. Because of the COVID-19 pandemic situation, the field survey and focus group discussion were carried out online.

The results show that ISCM is able to increase the income of farmers. Practically, this program can be duplicated in similar institutions, as well as in government or non-government organizations, in Indonesia and abroad, that have the same context and activity.

This study offers several social contributions by exploring how and why ISCM can eliminate the role of moneylenders and middlemen, increasing the small farmers' income, providing reasonable profits to parties involved in marketing and satisfying donors and equitable distribution of Qurban meat.

This study contributes to the literature by confirming the higher impact of ISCM in social business on poverty alleviation. Therefore, this paper provides an alternative solution to increase the income of small farmers through the supply of animals for Qurban or other religious rituals through ISCM arrangements.