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In this article, I answer the call to normalize and discuss how ethnographers navigate failure in the field by sharing my own experiences from long-term fieldwork in Malawi. I highlight, particularly, my own struggles with feelings of failure and the role of my interlocutors in helping me navigate and understand these situations.

My argument is based on more than 18 months of ongoing in-depth ethnographic fieldwork in Malawi, where I study the everyday practices of civil servants active in disaster governance, focusing on those working for the Malawi Government Department of Disaster Management Affairs (DODMA).

I use ethnographic vignettes to show how my interlocutors tried to teach me what being a Malawian civil servant is all about, which often came most forcefully to the fore in moments where either I or they deemed that I had failed to behave like one.

This adds new empirical data to the discussions on the various manifestations and roles of failure in ethnographic research, underlining how frictions and feelings of failure are a difficult yet productive and central part of fieldwork and ethnographic data creation.

This research is aimed at preparing landslide susceptibility using spatial analysis and soft computing machine learning techniques based on convolutional neural networks (CNNs), artificial neural networks (ANNs) and logistic regression (LR) models.

Using the Geographical Information System (GIS), a spatial database including topographic, hydrologic, geological and landuse data is created for the study area. The data are randomly divided between a training set (70%), a validation (10%) and a test set (20%).

The validation findings demonstrate that the CNN model (has an 89% success rate and an 84% prediction rate). The ANN model (with an 84% success rate and an 81% prediction rate) predicts landslides better than the LR model (with a success rate of 82% and a prediction rate of 79%). In comparison, the CNN proves to be more accurate than the logistic regression and is utilized for final susceptibility.

Land cover data and geological data are limited in largescale, making it challenging to develop accurate and comprehensive susceptibility maps.

It helps to identify areas with a higher likelihood of experiencing landslides. This information is crucial for assessing the risk posed to human lives, infrastructure and properties in these areas. It allows authorities and stakeholders to prioritize risk management efforts and allocate resources more effectively.

The social implications of a landslide susceptibility map are profound, as it provides vital information for disaster preparedness, risk mitigation and landuse planning. Communities can utilize these maps to identify vulnerable areas, implement zoning regulations and develop evacuation plans, ultimately safeguarding lives and property. Additionally, access to such information promotes public awareness and education about landslide risks, fostering a proactive approach to disaster management. However, reliance solely on these maps may also create a false sense of security, necessitating continuous updates and integration with other risk assessment measures to ensure effective disaster resilience strategies are in place.

Landslide susceptibility mapping provides a proactive approach to identifying areas at higher risk of landslides before any significant events occur. Researchers continually explore new data sources, modeling techniques and validation approaches, leading to a better understanding of landslide dynamics and susceptibility factors.

This study aims to understand client food preferences and how pantry offerings can be optimized by those preferences.

This study develops and administers customized surveys to study three food pantries within the Second Harvest Food Bank of Northwestern North Carolina network. This study then categorizes food items by client preferences, identifies the key predictors of those preferences and obtains preference scores by fitting the data to a predictive model. The preference scores are subsequently used in an optimization model that suggests an ideal mix of food items to stock based upon client preferences and the item and weight limits imposed by the pantry.

This study found that food pantry clients prefer fresh and frozen foods over shelf-friendly options and that gender, age and religion were the primary predictors. The optimization model incorporates these preferences, yielding an optimal stocking strategy for the pantry.

This research is based on a specific food bank network, and therefore, the client preferences may not be generalizable to other food banks. However, the framework and corresponding optimization model is generalizable to other food aid supply chains.

This study provides insights for food pantry managers to make informed decisions about stocking the pantry shelves based on the client’s preferences.

An emerging topic within the humanitarian food aid community is better matching of food availability with food that is desired in a way that minimizes food waste. This is achieved by providing more choice to food pantry users. This work shows how pantries can incorporate client preferences in inventory stocking decisions.

This study contributes to the literature on food pantry operations by providing a novel decision support system for pantry managers to aid in stocking their shelves according to client preferences.

Although scholars in strategic management have identified innovating and exit as firms’ two sequential strategic responses to long-run crisis, the potential interdependency has yet remained implicit. Specifically, in the context of Chinese Privately Owned Enterprises (POEs), this study investigates the interrelationship of these two strategic responses during long-run crisis. Building on resource redeployment perspective, the authors propose that firms tend to simultaneously leverage innovating and exit responses.

The authors use the data from the 2010 Chinese POEs survey to verify how firms in the long-term crisis made strategic responses after the 2008 financial crisis. Besides, the authors utilize Probit regressions as the basic analysis and further employ bivariate Probit regressions to conduct robustness tests.

This study provides empirical evidence confirming that firms in the long-run period of the crisis tend to adopt both exit and innovating strategies at the same time, that is, the strategy of resource redeployment. Moreover, this study further finds that government subsidies, the degree of marketization and firm’s organizational capability could all accentuate the decision-making of firms’ resource redeployment.

The authors thus contribute to the study of strategic responses to crisis in strategic management by dynamically find out the interdependency of two responses and enrich the research on resource redeployment perspective by identifying three influential positive antecedents, adding to the ongoing investigation on positive drivers of resource redeployment.

People donate to charities with the aim of improving society. Yet, many charities fail to use donations efficiently or have ineffective interventions. The authors explore the strategic operational priorities and processes that enable charities to efficiently implement their interventions and have a positive impact on society.

The authors first review the literature on charities to gain a deeper understanding of the current state of knowledge on charity operations. The authors then employ the lens of paradox theory and perform a qualitative investigation of six case studies to explore various aspects of the operations of charities that are known for being cost-effective.

The authors reveal how the strategic operational decisions of charities, as well as the processes they implement, help them resolve the tensions arising from the cost-effectiveness paradox. The authors show that cost-effective charities make strategic operational decisions that help maintain two diverging priorities: prioritizing the status quo and prioritizing change in how they deliver value. Another set of strategic decisions helps balance these two diverging priorities. The authors then show how these charities create and then maintain cost-effective operations.

The authors address recent calls for research on non-profit organizations in the field of operations management. To authors’ knowledge, it is the first in-depth study of exemplary charity operations. The results can be used by charity executives as a benchmarking tool when they develop and implement their charitable interventions and by government agencies and potential donors when they select charities for their donations. Finally, the results should have implications for other organizations trying to have a positive societal impact.

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

This paper aims to review research on mental health and well-being (MHW) in tourism, which the United Nations addresses in Sustainable Development Goal No. 3 (SDG 3). The authors also pinpoint future directions regarding how tourism can contribute to this goal from theoretical and practical standpoints.

The authors review the literature on MHW in tourism from the perspectives of tourists, residents and tourism workers.

Researchers have predominantly analysed tourists’ MHW outcomes through the lenses of positive psychology and tourism therapy; only a small number of studies have focused on MHW-related benefits and challenges in terms of tourism development for residents and tourism workers. Investigations of MHW in tourism require interdisciplinary approaches to reveal how tourism promotes diverse stakeholders’ mental health. Practically, there is an urgent need to incorporate tourism products and services into mental health care, and design tourism experience with positive psychology principles.

This study offers insights into fostering MHW through tourism. It specifically proposes theoretical and practical ways in which tourism might enhance MHW for various industry stakeholders, contributing to SDG 3.

本文基于联合国可持续发展目标中的第三个目标（SDG 3）, 对旅游中的心理健康和幸福感研究进行了回顾, 并就旅游如何助推这一目标的实现指明了未来的研究和实践方向。

本文从游客、居民和旅游从业者的角度对与旅游中的心理健康和幸福感相关的文献进行了回顾和评估。

当前研究主要从积极心理学和旅游疗法的视角分析了游客的心理健康和幸福感, 有关旅游业发展对居民和旅游从业者心理健康和幸福感的积极影响及挑战的研究尚不多见。因此, 需采用跨学科进路来揭示旅游业对不同利益相关者心理健康的促进作用。在实践方面, 亟需将旅游产品和服务纳入到心理健康护理体系中, 并依据积极心理学原理来开展旅游体验设计。

本文为通过旅游发展来促进心理健康与幸福感这一主题提供了见解。本文为旅游业如何提高各利益相关者的心理健康与幸福感提供了理论方面和实践方面的进路, 从而助推联合国可持续发展目标中第三个目标的实现。

Este artículo revisa los estudios y las investigaciones sobre la salud mental y el bienestar en el turismo (MHW por sus siglas en inglés, basándose en el Objetivo de Desarrollo Sostenible 3 (ODS 3) de las Naciones Unidas, y explora las futuras direcciones de investigación y práctica en el impulso del logro de este objetivo a través del turismo.

Se revisa la literatura relevante sobre la salud mental y el bienestar en el turismo desde la perspectiva de los turistas, residentes y trabajadores del sector turístico.

Actualmente, las investigaciones se centran principalmente en el análisis de la salud mental y el bienestar de los turistas desde la perspectiva de la psicología positiva y la terapia de turismo. Sin embargo, hay una falta de investigación sobre el impacto positivo y los desafíos del desarrollo turístico en la salud mental y el bienestar de los residentes y trabajadores del turismo. Por lo tanto, se requiere un enfoque interdisciplinario para revelar el papel del turismo en la promoción de la salud mental para diferentes partes interesadas. En cuanto a la práctica, se debe explorar activamente la integración de productos y servicios turísticos en el cuidado de la salud mental y diseñar actividades turísticas basadas en los principios de la psicología positiva.

Este estudio ofrece perspectivas sobre el papel del turismo en la promoción de la salud mental y el bienestar. Al proponer rutas teóricas y prácticas para mejorar la salud mental y el bienestar de las partes interesadas en el turismo, este artículo tiene como objetivo contribuir al logro del Objetivo de Desarrollo Sostenible 3 (ODS 3) de las Naciones Unidas.

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.