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More hotels are beginning to embrace green practices given increasing awareness of sustainable development. The purpose of this study is to examine factors contributing to hotels’ participation in TripAdvisor’s GreenLeaders program.

Based on a sample of 48,064 hotels from 328 destinations in 29 countries, the authors leverage a multi-level logit model to examine antecedents of GreenLeaders participation. A multi-level ordered logit model is then estimated to uncover factors influencing the ranking of this participation.

Empirical results indicate that hotels with a larger size, a higher class, a better online reputation, greater reliance on business travelers, fewer neighboring hotels and a more long-term-oriented culture are more apt to join the program. Online reputation factors, hotel size and the number of neighboring hotels explain GreenLeaders hotels’ rankings. A series of robustness checks reinforces the results.

The results shed light on green program design and promotion. These findings can help hotel practitioners identify ideal target markets and better use their organizational resources to establish green programs. Several strategies can be implemented to promote hotels’ commitment to sustainability and to encourage guests’ awareness of and involvement in green practices.

This study enriches knowledge of sustainable hospitality and tourism. The findings of this study also address corporate social responsibility by analyzing factors that can promote and inhibit GreenLeaders program participation. Further, as a complement to hotel- and location-specific factors, the authors scrutinize the effects of cultural features in shaping green strategies.

The outbreak of covid-19 has affected international migration and remittance and has also narrowed down the opportunities for internal labor migrants. The pandemic has also left internal migrants in a threatening situation due to the closure of job opportunities. Taking the migration of labor from the highland toward the sesame production belt into consideration, this study aims to examine the influencing factors of migration to the sesame belt amid covid-19 and ascertain the link between migration and translocal vulnerability.

The study followed a mixed approach that combines quantitative and qualitative methods. However, the quantitative approach tends to dominate due to the nature of the objectives of the study. The study was conducted in the central Gondar zone, using a cross-sectional survey design with a sample size of 150 households collected from January to March, 2021. Both descriptive and econometrics models such as binary logit model have been used.

Based on the study result, we came to understand that migration is part and parcel of the livelihoods of the farm household that accounts for 35% of migration status amid covid-19. Particularly, the study came to conclude that households’ decision to send family members heavily relied on their prior information and fear of transmission of the coronavirus to family members which are statistically significant. As a result, this piece of work can be a good witness for translocal vulnerability where studies are very limited in the area. For this, this study suggests that concerned bodies like social and labor affairs in consultation with the agriculture offices and bureaus at a different level and the investors in the migrant’s destination should facilitate the protection and awareness mechanisms so that the spread of covid-19 can be minimized and thereby both the migrants and the investors can be benefitted from the migrants’ work amid covid-19.

This study tries to connect the current spread of covid-19 with the translocal vulnerability context. Primarily, it empirically argued the translocal vulnerability factor is the main determinant for the farm households to send families’ labor as a livelihood diversification strategy. Very limited studies consider the translocal vulnerability implication of migration; notably to the best of the researchers’ knowledge, studies that linked covid-19 with translocal vulnerability context are scant. On top of that, many studies that link migration with covid-19 tend to be inclined to international migration with very limited attention to internal migration.

This article aims to examine the role of capital assets in rural household poverty transitions of poverty escape and poverty descent over periods of 2014–2016 and 2016–2018.

Based on the sustainable livelihood approach, this paper uses binary logit model to explore the influence of multidimensional capital assets on poverty transitions and use instrumental variable estimation to solve the endogeneity between total net asset and poverty transitions.

Capital assets have significant impacts on household poverty transitions. The role of capital assets in households' poverty escape and poverty descent are not symmetrical. The authors verify that rural households with rich total net asset are more likely to escape poverty and less likely to descend into poverty by using instrumental variable estimation. The authors verify that there is a mediation effect that total net asset can help households' escaping poverty and prevent them from falling into poverty through promoting rural households to engage in business activities.

This paper is the first to explore how capital assets affect poverty transitions in rural China based on the sustainable livelihood approach. The findings of this research can provide valuable policy implications for the pursuit of common prosperity in China and references for other developing countries.

The article investigates the patterns of asset impairment recognition in search of signs of “big bath” earnings management practices across an internationally diversified sample of public companies. It also elucidates the incentives that may underlie such practices and explores possible safeguards embedded in the existing corporate governance mechanisms.

The article applied static panel and binary logit models to an international firm-level panel dataset of 1045 public companies observed between 2003 and 2018.

Our empirical results suggest that recognition of asset impairment has no determinate impact on earnings volatility. Investigating the possibility of “big bath” earnings management practices, the authors found no impact of asset impairment recognition on total senior executive compensation in firms, which pay performance-based remuneration. The quality of corporate governance has appeared to impact the firms’ intertemporal proclivity to recognize asset impairment with those having the more entrenched and management-controlled boards being more likely to time impairment recognition by delaying it during exceptionally good and exceptionally bad years. While generally unlikely, recognition of asset impairment in a period with a recorded negative operating performance is found to be closely associated with key executive departures.

The article corroborates the salient role of corporate governance mechanisms in shaping the intertemporal patterns of asset impairment recognition. The possible remedies to the phenomenon should be derived therefrom.

Considering the speedy growth of Islamic finance and limited research work on Muslim behavior regarding Islamic Banking, this study aims to investigate to comprehend the stimulus of religiosity on customer’s behavior.

A conceptual model is developed on existing literature. The key dimensions of religiosity in the model include practice, knowledge, experience and consequences to capture the whole religiosity of customers. Model of the study investigates the impact of customer’s religiosity on their behavior in decision-making about selection of Islamic bank. Analysis of the study is based on the sample of 370 customers of Islamic banks from District Nowshera Khyber Pakhtunkhwa, Pakistan. The data for the study collected through random sampling by a comprehensive survey questionnaire. Binary logistic model is used to test the data for statistical analysis.

The key findings of the study suggest that religiosity influence customer behavior positively in decision-making regarding Islamic finance. Service standards of Islamic banking has also significant impact on customer perception, while the financial education of the customers has insignificant impact on customer behavior.

This study mainly focused on the curiosity of the customer religious commitment, so religiosity is a vast phenomenon; there are deep sections in each dimension of religiosity, so further study is suggested for the comprehensive capture of each dimension of religiosity.

The results of the study have a great importance for the managers of Islamic finance industry to identify and detect the potential customers and divide the target market of banking industry on the base of religiosity. Furthermore, the study may bring significant managerial suggestions for marketing planners and can help them in market segmentation strategies.

The study examined the association between Muslim religiosity and Islamic banking customer’s selection behavior. This study spread the understanding of religiosity and its impact on Islamic banking customer’s behavior. Furthermore, the study is valuable to discover the level to which religiosity determines the inclinations of customers. This study helps marketing practitioners and researchers to grow their knowledge about customer’s motives in terms of religious commitment.

This study aims to investigate the adaptation strategies they practice and the factors that influence their use of adaptation strategies.

The mixed-method sequential explanatory design was used to triangulate the data collected. Multistage sampling was used to select 400 sampled households for household surveys. Eight focus groups, each with eight to ten participants, and 24 key informants, were specifically chosen based on their farming experiences. Chi-square tests, one-way ANOVA and a binary logit model were used to analyze the data.

The majority of farmers used simple and low-cost adaptation strategies like changing planting dates, selling livestock and off-farm and nonfarm work. A minority of farmers used advanced adaptation strategies like crop diversification and water harvesting for irrigation. The result further revealed that: the age of the household head, educational status of household heads, farm size, livestock ownership, farming experiences, household income, access to credit and access to climate information significantly influenced the adoption of the adaptation strategies. Public policy should provide water harvesting and irrigation technology, climate-related information and the provision of microcredit facilities to enhance the farmers’ resilience to climate change risks.

Although several studies on climate change adaptation strategies are available, this paper is one of the few studies focusing on a particular agro-ecological zone, an essential precursor to dealing with current and projected climate change in the area. It provides helpful insights for developing successful adaptation policies that improve adaptive capacity and agricultural sustainability in southern Ethiopia’s lowlands.

The purpose of this study is to provide an optimal joint strategy of multi-period pricing and sales effort for a retailer with a logit choice demand in an integrated channel.

Customer demand is characterized by a logit choice model, it varies over time and is influenced by price and sales effort. The multi-period decision model for the retailer is constructed using a discrete-time dynamic programming method to determine the optimal price and sales effort in each period.

When the inventory level does not exceed a certain threshold, decreasing price and increasing sales effort over time or as inventory level increases are the optimal strategies. However, once the inventory level exceeds the threshold, the optimal strategy is to maintain both price and sales effort constant as the inventory level changes or to increase price and decrease sales effort over time. Additionally, the greater the influence of sales effort on demand or the higher the arrival rate of customers, the higher the optimal price and the greater the optimal sales effort level.

This study contributes to the existing research on dynamic pricing and sales effort in integrated channels by incorporating a logit choice model. Furthermore, it provides valuable management insights for retailers operating in an integrated channel to make pricing and sales effort decisions based on inventory level and time period.

This chapter investigates whether, and if so, how particular firms in a transition economy are involved in bribery. Built on pressure theories, we explain how the direct effects of firm characteristics and contextual characteristics determine firm bribery behavior. Entrepreneurs make choices based on perceptions of a specific pressure due to organizational characteristics (internal pressures) or due to context (external pressures). The relationship between firm characteristics, context, and bribery was estimated using unique data from a survey of 606 Vietnamese entrepreneurs. We controlled for various entrepreneurial, organizational, and industrial characteristics. The exploratory findings support firm attributes hypotheses, which is a negative relationship between firm size and bribery and a nonmonotonic U-shaped relationship between firm age and bribery. Besides, the effects of context on bribery are also found. Specifically, the result supports a positive relationship between competition and bribery and a negative relationship between the quality of the government and bribery.

Providing loans, particularly to small-scale farmers, is one of the roles of formal financial institutions. Lending to small farmers is risky. An institution's health is closely related to the institution's ability to manage credit and portfolio risk. Expanding smallholder farmers' access to finance while maintaining a sustainable financial system is essential; however, pandemics present additional challenges. Accordingly, as reported in the literature, the pandemic's high loan default rates and decreases in return on assets (ROAs) call for further credit risk management research. There have been limited studies on credit risk management during coronavirus disease 2019 (COVID-19), so this article aims to provide useful information on its influences.

Researchers used data from formal financial institutions in 2018 (before COVID-19) and in 2021 (during COVID-19) to accomplish the study's broad objective. Descriptive and inferential statistics were the main analytical tools. The credit risk management indicators were categorized into collateral management, loan management, loan recovery management, governance and Information and Communication Technology (ICT). Weights were assigned to each category based on the importance to credit risk management. A binary logit model was employed in assessing the factors influencing credit risk management as proxied to loan repayment, while Ordinary Least Square (OLS) was used to examine factors that influence ROAs.

One of the most noteworthy findings is that credit risk management is affected by different factors and magnitudes before and during the COVID-19 era. Loan recovery and ICT management indicators were most influential during the pandemic. In addition, the study noted that low agricultural productivity during the pandemic contributed to an additional challenge in loan default rates because of various COVID-19-containing measures. Additionally, there was a lack of governance and ICT management capacity to drive credit and portfolio risk management during the epidemic.

The paper presents new empirical findings on credit risk management during the COVID-19 era. The study used a methodology which has not been used previously in credit risk management in Nigerian financial institutions. Therefore, this research could become the cornerstone of further academic research in other developing countries using this methodology.

The present study addresses acceptance of in vitro meat (IVM) among a predominantly student sample in Germany. It is investigated to which extent food technology neophobia, the currently followed diet and information treatments impact acceptance of IVM measured via the construct willingness to buy (WTB).

A quantitative online-survey was conducted in August 2020 using a between-subject design with three different information treatments and one control group. Moreover, the Food Technology Neophobia (FTN) scale was employed, For the statistical analysis, the χ² and Kruskal–Wallis test were used. Additionally, a binary logit model was specified and estimated in order to investigate the determinants of willingness to buy IVM accounting for the effects of gender, age, vegetarianism/veganism, FTN, prior knowledge, information treatments and potential interaction effects.

Participants following a vegan or vegetarian diet exhibit a lower likelihood of IVM acceptance in comparison to participants following an omnivore diet. However, a considerable share of vegan and vegetarian participants expressed a positive WTB. Moreover, an increasing FTN score (i.e. an increase in food technology neophobia) goes along with a reduced likelihood of acceptance, while all three information treatments increase acceptance in comparison to the control group. The largest effect on acceptance could be found for the environmental benefit treatment.

The findings show that especially among a young and highly educated sample the stressing of environmental benefits of IVM has a substantial impact on acceptance. This might be taken up in information and marketing campaigns once the product becomes available on the European market.

So far the empirical evidence on German consumers' acceptance of IVM is scarce. The present study addressed this research gap by focusing on a young sample with a high percentage of vegetarians and vegans and analyzing the role of food technology neophobia and different information treatments in a between-subject design.