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This study aims to examine the reaction of anchor investors (AIs) to pre-IPO earnings management (EM). The authors use the unique detailed bid data from the Indian anchor experiment. The authors also study the reputed AIs’ EM detection ability and pricing behavior in response to pre-IPO EM.

The authors use unique AI bid data for 169 Indian IPO firms. Utilizing the logistic regression and Tobit regression models with industry and year-fixed effects, the authors examine the relationship between various measures of AI participation and proxies of short-term and long-term discretionary accruals.

The authors document that pre-IPO EM is positively associated with the likelihood of anchor backing but negatively related to the likelihood of reputed anchor backing. The findings indicate that AIs are misled by pre-IPO EM, but reputed AIs are not. The authors also observe that reputed AIs, compared to the non-reputed, pay less than the upper band with increasing EM. The findings are robust to using various AI measures and EM proxies.

The findings have significant implications for regulators in the implementation of AI concept in non-anchor markets and better implementation of policies in existing anchor settings. Findings can also be relevant for non-institutional investors in the IPO domain.

This is one of the few studies on institutional investors' IPO bidding behavior in response to pre-IPO EM. However, this is the first study to analyze AIs' IPO bidding behavior in response to pre-IPO EM.

The study seeks to evaluate the extent and quality of environmental reporting following a longitudinal analysis and covering a wide spectrum of industries in a single frame. The study also attempts to identify the set of most favored environmental reporting items by firms and items which are least disclosed. Furthermore, the study attempts to test whether certain corporate attributes such as firm size, age of the firm, leverage ratio, profitability, presence of independent directors in the board and gender diversity have any influencing power over environmental disclosure practices. The whole study has been carried out from legitimacy theory setting.

The study follows longitudinal analysis to identify the extent and quality of environmental disclosures. A self-constructed checklist of 12 environmental reporting items has been developed analyzing the annual report and content analysis method is followed to measure the extent and quality of environmental disclosures and identify environmental reporting items which are mostly disclosed and which are least disclosed. The study further uses panel data regression analysis to investigate whether certain corporate attributes have any impact on environmental disclosures using multiple linear regression. Total of 345 annual reports of listed financial and nonfinancial institutions have been observed in this study ranging from 2015 to 2019.

The key finding suggests that strict enforcement of Green Banking Rules 2011 fosters country’s commercial banks to invest more to protect the environment and commercial banks encourage nonfinancial institutions for environmental performance and related disclosures through finance. Therefore, almost 50% of sample firms disclose their environmental performance through reporting in either narrative, quantitative or monetary format which was only 2.23% in the last decade. Findings also reveal that tree plantation is the most reported environment disclosure followed by investment in renewable energy and green infrastructural projects and the least reported items are fund allocation for climatic changes and carbon management policy. Further analysis shows that firm size and leverage ratio both have positive impact on environmental reporting.

An in-depth analysis may be conducted to identify why certain environmental items are least disclosed such as fund allotment for climatic changes, carbon management policy, etc. and how corporations may earn social appreciation and motivation by investing in those least preferred items in legitimacy theory setting. Future research may also take into consideration other corporate attributes which are not considered in the study.

The study conducted an in-depth analysis to understand the most favored form of environmental disclosures (narrative/quantitative/monetary) and their extent after incorporation of regulatory guidelines, which is the first of its kind in the research of environmental disclosures. The study indeed contributes to the documentation of environmental reporting in the context of a developing country where there is a lack of longitudinal analysis from the lens of legitimacy theory. Moreover, a wide spectrum of industries has been taken into consideration which facilitates the generalized findings on the environmental disclosure practices of corporations in Bangladesh.

本研究擬評估公司報告環境方面的程度和質量, 以及對就環境報告披露而言、最受青睞和最不受歡迎的項目加以處理。研究亦擬測試企業屬性對實踐環境信息披露的影響。

研究使用內容分析法、去測量環境信息披露的程度和質量。研究使用多元回歸分析、去探討企業屬性對環境信息披露的影響。研究涵蓋孟加拉國上市公司共345個年度報告, 涵蓋的年期為2015年至 2019年。

研究結果似乎顯示綠色金融規則 - 2011 、成功鼓勵機構為保護環境而投放更多資源; 機構最樂於匯報的項目為植樹, 而披露最少的則為氣候變化和碳管理政策。進一步的研究分析顯示, 公司的規模和杠杆比率均會對環境匯報帶來正面的影響。

本研究豐富了關於發展中國家環境匯報的官方文件記錄, 而在這類國家, 透過合法化理論而進行的縱貫性分析研究頗為缺乏。本研究以深度分析法、去瞭解環境信息披露方面最受青睞的信息披露方式 (故事形式的敘述/定量形式/金融形式), 也去瞭解納入強制的規管指引後環境信息披露的程度; 就此而言, 本研究為這類環境信息披露研究的首個研究。

This study proposes strategies for vaccine center allocation for coronavirus disease (COVID) vaccine by determining the number of vaccination stations required for the vaccination drive, location of vaccination station, assignment of demand group to vaccination station, allocation of the scarce medical professional teams to station and number of optimal days a vaccination station to be functional in a week.

The authors propose a mixed-integer nonlinear programming model. However, to handle nonlinearity, the authors devise a heuristic and then propose a two-stage mixed-integer linear programming (MILP) formulation to optimize the allocation of vaccination centers or stations to demand groups in the first stage and the allocation of vaccination centers to cold storage links in the second stage. The first stage optimizes the cost and average distance traveled by people to reach the vaccination center, whereas the second stage optimizes the vaccine’s holding and storage and transportation cost by efficiently allocating cold storage links to the centers.

The model is studied for the real-world case of Chandigarh, India. The results obtained validate that the proposed approach can immensely help government agencies and policymaking body for a successful vaccination drive. The model tries to find a tradeoff between loss due to underutilized medical teams and the distance traveled by a demand group to get the vaccination.

To the best of our knowledge, there are hardly any studies on a vaccination program at such a scale due to sudden outbreaks such as Covid-19.

Perceptions of climate change are strongly influenced by visual cues and images. Many universities have made significant steps towards decarbonisation, yet these often remain hidden from the campus community. This study aims to explore the hidden curriculum of climate change on campus and compare participants’ images of sustainability on campus with those on university websites.

This research was underpinned by a critical realist perspective using innovative visual research methods including auto-photography and photo-elicitation to enable deep understanding of perceptions of sustainability and climate change on campus. Grounded visual pattern analysis (GVPA) was used to analyse campus photos and compare them to images used on university websites.

Findings suggest that staff and student images more strongly encapsulated tensions between humans and nature than website photos, but that the latter included more evidence of social sustainability. Neither image set expressed climate change issues effectively; the invisibility of university decarbonisation activities represents a lost opportunity for learning.

This research uses novel visual methodologies and analysis (GVPA) with potential for wider use in sustainability research. This study offers new insights into the importance of the hidden curriculum of sustainability in higher education and the difficulties of making climate change visible on campus.

The accessibility of housing for many purposes is more influenced by the functioning of housing market. As access to housing is an expensive and long-term exertion of household, looking for appropriate housing fund is necessary whether the source of fund is private saving or mortgage. However, insufficient finance in Ethiopia is a reason for inaccessible of land and housing by the low- and middle-income people. This study aims to identify the barriers to access finance in the study area.

This study adopted a qualitative and quantitative research approach to investigate the barriers of housing finance. To undertake and increase the relevance of this study, primary and secondary, qualitative and quantitative data were used. Primary data were collected from respondents; focal person’s and key informants. Both descriptive statistical analysis and relative importance index analysis was deployed for this study. In addition, the quantitative data were analyzed using logistic regresion model.

The result of this study found that in Ethiopia at all, there is no enough mortgage and long-term lending banks. The result of this study inspects some variables significantly affect the access to finance. The result of this study will help the government in buildup of financial institutions in many perspectives. Financial institutions and clients may also be beneficiary through stiffen housing finance system.

The barriers of access to finance were not sufficiently studied in Ethiopia. Therefore, this study may be a pioneer for the researchers, as it did not cover the whole area of the country to study and also appoint the government to reform the financial sector based on the findings of the researches.

Purpose: Green computing is a way of using the computer resource in an eco-friendly while maintaining and decreasing the harmful environmental impact. Minimising toxic materials and reducing energy usage can also be used to recycle the product.

Need for the Study: The motivation of the study is to use green computing resources to decrease carbon emissions and their adverse effect on the environment.

Methodology: The study uses a qualitative method of collecting resources and data to address the opportunities, challenges, and future trends in green computing for Sustainable Future Technologies. The study focusses on multiple kinds of cloud computing services collected and executed into single remote servers. The service demand processor offers these services to the client per their needs. The simultaneous requests to access the cloud services, processing and expertly managing these requests by the processors are discussed and analysed.

Findings: The findings suggest that green computing is an upcoming and most promising area. The number of resources employed for green computing can be beneficial for lowering E-waste so that computing can be environmentally friendly and self-sustainable.

Practical Implications: Green computing applies across all industries and service sectors like healthcare, entertainment, tourism, and education. The convergence of technologies like Cloud Computing, AI, and Internet of Things (IoT) is greatly impacting Green Supply Chain Management (GSCM) market.

Community gardens are increasingly used as interventions during the resettlement of refugees and other migrants. Little is known about how garden programs might support their mental health and wellbeing. Given the links between climate change and forced migration, community gardens are especially relevant, as they can also support climate change mitigation. This study aims to document psychosocial outcomes of gardening programs for refugees and migrants, and mechanisms leading to these outcomes.

The authors searched major databases and the grey literature up to 2021, resulting in the inclusion of 17 peer-reviewed and 4 grey literature articles in a thematic, qualitative analysis.

Four consistent themes arose from the analysis: community gardening programs promoted continuity and adaptation (81% of articles), social connectedness (81%), overall wellbeing (95%) and a sense of meaning and self-worth (67%). The results suggest that community gardens can strengthen psychosocial pillars that are key to the recovery and resettlement of refugees and migrants. The land-based and social nature of community gardening may enable connections to the land and others, nurture a sense of belonging in the host country and provide a link to the past for those from agricultural backgrounds.

Further participatory action research is needed to develop guidelines for the successful implementation of community gardens by resettlement organisations.

This review indicates that community gardens can be effective psychosocial interventions as part of a network of services supporting the resettlement of refugees and migrants.

The purpose of the study is to evaluate the relationship of Journal Publication Timeline (submission to first decision and submission to final decision) with various Journal Metrics (citing half-life, article influence score, the immediacy index, the acceptance rate, the impact factor (IF), five years IF, Eigenfactor and cited half-life) of top 600 journals retrieved from Journal Citation Report (JCR) 2020 under the tag, Elsevier Unified.

Top 600 journals in the decreasing order of the IFs under the tag, “Elsevier Unified” were retrieved from JCR 2020 of Clarivate Analytics. Information about “Journal Metrics” was ascertained using “Customized Service” of JCR, while information about the “Publication Timeline” of each journal was obtained using Elsevier's “Journal Insights Service.” It was found that only 177 journals provided the complete information regarding the “Publication Timeline” and hence considered for the study. Descriptive statistics and correlation analysis was conducted to test the different hypotheses.

It was found that submission to first decision has a significant relationship with the immediacy index, citing half-life and the acceptance rate. Submission to final decision has a significant relationship with Journal Impact Factor (JIF), the immediacy index, Eigenfactor, citing half-life and the acceptance rate.

The study will provide the authors with sound and valuable information to support their selection of journals. Inferences in light of fluctuations in the scholarly communication process in terms of Publication Timelines and Journal Metrics can be deeply understood with the aid of the current study's findings. What considerations authors have to take before submitting their papers is the main implication of the study. Journal administrators can also benefit from the findings of the current study as it can help recruit and manage reviewers, which will ensure a successful publication timeline.

The study correlates Publication Timeline Indicators with Journal Metrics Indicators using secondary cross-sectional data. Though most previous studies only examine the relationship of the Publication Timeline with the Journal Impact Factor (JIF), there is very scarce literature that deciphers the influence of Publication Timeline indicators on different Journal Metrics indicators (including JIF).

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2022-0108.

Household food insecurity and poor well-being have increased during the coronavirus disease 2019 (COVID-19) pandemic and resulting lockdown measures. Home food growing has been associated with improved food access and well-being, but it is unknown what role it plays during food supply crises and lockdown. It is also unclear how home food growing and social restrictions may affect opinions about growing food in urban areas (i.e. urban agriculture; UA).

A cross-sectional online survey was conducted during the UK national lockdown in March-April 2020 to measure home food growing, perceived food insecurity, well-being, and opinions of UA. The participants were 477 UK-based adults (369 female, mean age 39.57 years ± 13.36); 152 participants were engaged in home food growing prior to the pandemic. Responses were compared to data collected from a separate sample of participants before the pandemic (N=583) to explore potential shifts in opinions about UA.

Participants who engaged in home food growing had lower levels of food insecurity (U_­=19894.50, z=−3.649, p<0.001, r=−0.167) and higher well-being (U=19566.50, z=−3.666, p<0.001, r=−0.168) than those not engaged in home food growing. Perceived food insecurity partially mediated the relationship between home food growing and well-being; home food growing was associated with less food insecurity, which in turn was associated with better well-being. There were no differences in opinions of UA compared to the sample of participants from before the pandemic.

Home food growing may have had a protective effect over perceived food security and well-being in the early stages the pandemic. Opinions of UA were positive and unchanged compared to data collected pre-pandemic. Policies that support home food growing and access to suitable growing spaces and resources may be beneficial for food system resilience and well-being.

Small and medium enterprises (SMEs) play a crucial role in national economies worldwide, generating employment and contributing to innovation. This study tries to investigate the performance of the newly started IPO platform for the SMEs in India through a two-staged framework developed to measure pre-market and post-market underpricing separately and the impact of economic policy uncertainty (EPU) on the IPO returns using the EPU index which is based on newspaper coverage frequency. Further, the long-run performance of SME IPOs and the factors affecting the same have also been analyzed. The two-staged framework is helpful in capturing the impact of different factors separately on the two distinctive markets and providing effective investment strategies to the investors.

A sample of 384 SME IPOs issued during 2012–2018 has been analyzed using robust regression analysis.

The study highlights the fact that there are differences in the factors affecting pre-market and post-market underpricing and reports that investors subscription rate, issue expenses, lead manager reputation and EPU are positively associated, whereas the age of the firm is negatively associated with the pre-market underpricing, and lead manager reputation positively impacts the post-market underpricing whereas issue premium and pre-market underpricing are negatively associated. Pre-market underpricing subsumes all the impact of EPU (publicly available information) in it, hence providing credence to the semi-strong market hypothesis of the Efficient Market Hypothesis (EMH). The long-run performance of SME IPOs increases with time, and lead manager reputation, pre-market and post-market underpricing are positively related to the one-year return whereas issue size, turnover and issue expense are negatively related.

This paper is believed to be the first attempt to analyze the performance of SME IPOs by disaggregating IPO underpricing. The findings of this study will have a great insight for the investors and policymakers.