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Conflict and violence are the main drivers of globally escalating humanitarian needs. Local grassroots initiatives are pivotal in distributing humanitarian supplies in the acute response phase until more established humanitarian aid organizations can enter. Nevertheless, scant research exists regarding the role of grassroots associations in providing humanitarian assistance during a military conflict. The purpose of this paper is to understand the role of grassroots associations and identify important themes for effective operations.

This paper adopts a case-study approach of three Ukrainian grassroots associations that began operating in the immediate days of the full-scale invasion of Ukraine. The findings are based on analyzing primary sources, including interviews with Ukrainian volunteers, and are supported by secondary sources.

Grassroots associations have local contacts and a contextual understanding of population needs and can respond more rapidly and effectively than large intergovernmental agencies. Four critical themes regarding the operations of grassroots associations emerged: information management, inventory management, coordination and performance measurement. Grassroots humanitarian response operations during conflict are challenged by personal security risks, the unpredictability of unsolicited supplies, emerging volunteer roles, dynamic transportation routes and shifting demands.

Grassroots responses are central to humanitarian responses during the acute phase of a military conflict. By examining the operations of grassroots associations in the early months of the 2022 war in Ukraine, the authors provide a unique perspective on humanitarian logistics. Nonetheless, more inclusive models of humanitarian responses are needed to harness the capacities and resilience of grassroots operations in practice.

To investigate the influence of logistics and transportation workers’ perceptions of their management’s simultaneous safety and operations focus (or lack thereof) on related worker safety and operational perceptions and behaviors.

This multi-method research consisted of two studies. Study 1 aimed to establish correlational relationships by evaluating the impact of individual-level worker perceptions of operationally focused routines (as a moderator) on the relationship between worker perceptions of safety-related routines and workers’ self-reported safety and in-role operational behaviors using a survey. Study 2 aimed to establish causal relationships by evaluating the same conceptual relationships in a behavioral-type experiment utilizing vehicle simulators. After receiving one of four pre-task briefings, participants completed a driving task scenario in a driving simulator.

In Study 1, the relationship between perceived safety focus and safety behavior/in-role operational behavior was strengthened at higher levels of perceived operations focus. In Study 2, participants who received the balanced pre-task briefing committed significantly fewer safety violations than the other 3 treatment groups. However, in-role driving deviations were not impacted as hypothesized.

This research is conducted at the individual (worker) level of analysis to capture the little-known perspectives of logistics and transportation workers and explore the influence of balanced safety and operational routines from a more micro perspective, thus contributing to a deeper understanding of how balanced routines might influence worker behavior when conducting dynamic tasks to ensure safe, effective outcomes.

The purpose of this study is to address a critical gap in enterprise resource planning (ERP) implementation process for small and medium-sized enterprises (SMEs) by acknowledging and countering cognitive biases through a cognitive bias awareness matrix model. Cognitive biases such as temporal discounting and optimism bias often skew decision-making, leading SMEs to prioritize short-term benefits over long-term sustainability or underestimate the challenges involved in ERP implementation. These biases can result in costly missteps, underutilizing ERP systems and project failure. This study enhances decision-making processes in ERP adoption by introducing a matrix that allows SMEs to self-assess their level of awareness and proactivity when addressing cognitive biases in decision-making.

The design and methodology of this research involves a structured approach using the problem-intervention-comparison-outcome-context (PICOC) framework to systematically explore the influence of cognitive biases on ERP decision-making in SMEs. The study integrates a comprehensive literature review, empirical data analysis and case studies to develop the Cognitive Bias Awareness Matrix. This matrix enables SMEs to self-assess their susceptibility to biases like temporal discounting and optimism bias, promoting proactive strategies for more informed ERP decision-making. The approach is designed to enhance SMEs’ awareness and management of cognitive biases, aiming to improve ERP implementation success rates and operational efficiency.

The findings underscore the profound impact of cognitive biases and information asymmetry on ERP system selection and implementation in SMEs. Temporal discounting often leads decision-makers to favor immediate cost-saving solutions, potentially resulting in higher long-term expenses due to the lack of scalability. Optimism bias tends to cause underestimating risks and overestimating benefits, leading to insufficient planning and resource allocation. Furthermore, information asymmetry between ERP vendors and SME decision-makers exacerbates these biases, steering choices toward options that may not fully align with the SME’s long-term interests.

The study’s primary limitation is its concentrated focus on temporal discounting and optimism bias, potentially overlooking other cognitive biases that could impact ERP decision-making in SMEs. The PICOC framework, while structuring the research effectively, may restrict the exploration of broader organizational and technological factors influencing ERP success. Future research should expand the range of cognitive biases and explore additional variables within the ERP implementation process. Incorporating a broader array of behavioral economic principles and conducting longitudinal studies could provide a more comprehensive understanding of the challenges and dynamics in ERP adoption and utilization in SMEs.

The practical implications of this study are significant for SMEs implementing ERP systems. By adopting the Cognitive Bias Awareness Matrix, SMEs can identify and mitigate cognitive biases like temporal discounting and optimism bias, leading to more rational and effective decision-making. This tool enables SMEs to shift focus from short-term gains to long-term strategic benefits, improving ERP system selection, implementation and utilization. Regular use of the matrix can help prevent costly implementation errors and enhance operational efficiency. Additionally, training programs designed around the matrix can equip SME personnel with the skills to recognize and address biases, fostering a culture of informed decision-making.

The study underscores significant social implications by enhancing decision-making within SMEs through cognitive bias awareness. By mitigating biases like temporal discounting and optimism bias, SMEs can make more socially responsible decisions, aligning their business practices with long-term sustainability and ethical standards. This shift improves operational outcomes and promotes a culture of accountability and transparency. The widespread adoption of the Cognitive Bias Awareness Matrix can lead to a more ethical business environment, where decisions are made with a deeper understanding of their long-term impacts on employees, customers and the broader community, fostering trust and sustainability in the business ecosystem.

This research introduces the original concept of the Cognitive Bias Awareness Matrix, a novel tool designed specifically for SMEs to evaluate and mitigate cognitive biases in ERP decision-making. This matrix fills a critical gap in the existing literature by providing a structured, actionable framework that effectively empowers SMEs to recognize and address biases such as temporal discounting and optimism bias. Its practical application promises to enhance decision-making processes and increase the success rates of ERP implementations. This contribution is valuable to behavioral economics and information systems, offering a unique approach to integrating cognitive insights into business technology strategies.

This study aims to investigate tourists’ attitudes and intentions regarding the usage of Chat Generative Pre-trained Transformer (ChatGPT) for accessing tourism information. Furthermore, by integrating the perceived risks associated with ChatGPT and the theory of planned behavior (TPB), this research examines the impact of three types of perceived risks, such as privacy risk, accuracy risk and overreliance risk, on tourists’ behavioral intention.

Data were gathered for this study by using two online survey platforms, thus resulting in a sample of 536 respondents. The online survey questionnaire assessed tourists’ perceived risks, attitude, subjective norm, perceived behavioral control, behavioral intention and demographic information related to their usage of ChatGPT.

The structural equation modeling analysis revealed that tourists express concerns about the associated risks of using ChatGPT to search for tourism information, specifically privacy risk, accuracy risk and overreliance risk. It was found that perceived risks significantly influence tourists’ attitude and intention toward the usage of ChatGPT, which is consistent with the hypotheses proposed in previous literature regarding tourists’ perceived risks of ChatGPT.

This work is a preliminary empirical study that assesses tourists’ behavioral intention toward the use of ChatGPT in the field of tourism. Previous research has remained at the hypothetical level, speculating about the impact of ChatGPT on the tourism industry. This study investigates the behavioral intention of tourists who have used ChatGPT to search for travel information. Furthermore, this study provides evidence based on the outcome of this research and offers theoretical foundations for the sustainable development of generative AI in the tourism domain. This study has limitations in that it primarily focused on exploring the risks associated with ChatGPT and did not extensively investigate its range of benefits.

First, to address privacy concerns that pose significant challenges for chatbots various measures, such as data encryption, secure storage and obtaining user consent, are crucial. Second, despite concerns and uncertainties, the introduction of ChatGPT holds promising prospects for the tourism industry. By offering personalized recommendations and enhancing operational efficiency, ChatGPT has the potential to revolutionize travel experiences. Finally, recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises.

Recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises. As their interest in adopting ChatGPT grows, increased investments and resources will be dedicated to developing and implementing ChatGPT solutions. This enhancement may involve creating customized ChatGPT solutions and actively engaging in training and development programs to empower employees in effectively using ChatGPT’s capabilities. Such initiatives can contribute to improved customer service and overall operations within the tourism industry.

This study integrates TPB with perceived risks in ChatGPT, thus providing empirical evidence. It highlights the importance of considering perceived risks in tourists’ intentions and contributes to the sustainable development of generative AI in tourism. As such, it provides valuable insights for practitioners and policymakers.

本研究旨在调查游客对使用ChatGPT获取旅游信息的态度和意向。此外, 通过将与ChatGPT相关的感知风险与计划行为理论（TPB）相结合, 本研究探讨了三种感知风险（隐私风险、准确性风险和过度依赖风险）对游客行为意向的影响。

本研究通过两个在线调查平台收集了536名受访者的数据。在线调查问卷评估了游客对ChatGPT使用的感知风险、态度、主观规范、感知行为控制、行为意向以及与其使用ChatGPT相关的人口统计信息。

结构方程建模分析显示, 游客对使用ChatGPT搜索旅游信息的相关风险表示关切, 特别是隐私风险、准确性风险和过度依赖风险。发现感知风险显著影响游客对使用ChatGPT的态度和意向, 与先前有关游客对ChatGPT感知风险的文献中提出的假设一致。

本研究将TPB与ChatGPT中的感知风险相结合, 提供了实证证据。它强调了在考虑游客意向时考虑感知风险的重要性, 并为旅游中生成AI的可持续发展提供了贡献。因此, 它为从业者和政策制定者提供了宝贵的见解。

The purpose of this paper is to evaluate the performance of Microfinance Institutions (MFIs) offering FinTech services. This study contributes to the existing literature on microfinance digitalization, financial inclusion and sustainable development. The study also takes into consideration a behavioral perspective through the efficiency evaluation process of MFIs offering FinTech services.

The following study employs the Stochastic Frontier Analysis approach to estimate the operational and social efficiency scores of the 387 MFIs over the period 2005–2019. Then, it tries to consider factors influencing MFIs' efficiency and assess their effects. Hence, two separate models for operation and social efficiency introducing a set of factors, including FinTech proxies and overconfidence proxies, are tested. The first model for operational efficiency uses a random-effects estimator while the second one for social efficiency uses a fixed-effects estimator.

The results show that innovative MFIs have weaker averages of operational efficiency than non-innovative ones but higher averages of social efficiency. This was justified by the fact that innovative MFIs are more socially oriented. Further, findings of this study depict that the proxies of FinTech affect negatively the level of operational efficiency of MFIs. They also depict a negative relationship between FinTech proxies and the level of social efficiency. These results hold through robustness tests.

The highlight of this study is that it takes heed of the indirect effect of technological innovation on the efficiency of MFIs. It has been proved that it moderates the impact of managerial overconfidence (manifested by excessive risk-taking, viz., high levels of PAR30, LGR and NIM) on the level of both operational and social efficiencies.

本文旨在對提供金融科技服務的微型金融機構的表現作出評價。我們的研究, 就現有之學術文獻而言, 在以下課題之探討上作出了貢獻: 微型金融的數字化、普惠金融、以及可持續發展。本研究亦以行為主義觀點, 對微型金融機構提供之金融科技服務的效率作出評價。

本研究使用隨機邊界分析法的理念, 去估計有關的387間微型金融機構於2005年至2019年期間、經營方面和社會方面的效率分數; 繼而嘗試找出影響微型金融機構效率的因素, 並評估這些因素的影響。為此目的, 研究人員分別測試兩個模型, 一個是探究運作方面的效率, 另一個則探究社會方面的效率。兩個模型內均放入一系列的因素, 其中包括金融科技代理和過度自信代理。探究運作方面的效率的模型使用了隨機效果估算器, 而探究社會方面的效率的模型則使用了固定效果估算器。

研究結果顯示、具創新精神的微型金融機構, 在運作方面的效率的平均值上,較沒具創新精神的為弱, 而社會方面的效率的平均值卻較高。這個結果是合理的, 因為具創新精神的微型金融機構會更著眼於社會。另外, 研究結果描繪了一個現象, 就是: 金融科技代理會對微型金融機構的運作效率水平產生負面影響; 我們也看到、金融科技代理與社會方面的效率水平之間的關聯是負面的; 這些研究結果、均通過穩健性檢驗。

本研究最突出之處為研究人員關注科技之創新會間接影響微型金融機構的效率。研究人員證明了於微型金融機構整合金融科技服務是會緩和管理上的過度自信給運作和社會兩方面的效率水平帶來的影響 (管理上的過度自信、顯露於過度的風險承擔, 即是, PAR30(貸款組合風險-30日)、LGR(貸款增長率) 和NIM(淨息差) 處於高水平)。

Sports marketing and sponsorship research is located at the intersection of behavioral and design research, which means that it analyzes the current world and shapes a future world. This dual focus poses challenges for formulating and testing theories of sports marketing.

This article develops criteria for categorizing theoretical concepts as either behavioral or formed as different ways of expressing ideas of sports marketing research. It emphasizes the need for clear concept categorization for proper operationalization and applies these criteria to selected theoretical concepts of sports marketing and sponsorship research.

The study defines three criteria to categorize theoretical concepts, namely (1) the guiding idea of research, (2) the role of observed variables, and (3) the relationship among observed variables. Applying these criteria to concepts of sports marketing research manifests the relevance of categorizing theoretical concepts as either behavioral or formed to operationalize concepts correctly.

This study is the first in sports marketing to clearly categorize theoretical concepts as either behavioral or formed, and to formulate guidelines on how to differentiate behavioral concepts from formed concepts.

The present study aims to examine the scope and contribution of behavioural investigative advice (BIA) reports from the National Crime Agency (NCA).

The 77 BIA reports reviewed were written between 2016 and 2021. They were evaluated using Toulmin’s (1958) strategy for structuring pertinent arguments, current compliance with professional standards, the grounds and backing provided for the claims made and the potential utility of the recommendations provided.

Consistent with previous research, most of the reports involved murder and sexual offences. The BIA reports met professional standards with extremely high frequency. The 77 reports contained a total of 1,308 claims of which 99% were based on stated grounds. A warrant and/or backing was provided for 73% of the claims. Most of the claims in the BIA reports involved a behavioural evaluation of the crime scene and offender characteristics. The potential utility of the reports was judged to be 95% for informative behavioural crime scene analysis and 40% for potential new lines of enquiry.

The reports should serve as a model for the work of behavioural investigative advisers internationally.

To the best of the authors’ knowledge, this is the first study to systematically evaluate BIA reports commissioned by the NCA; it adds to previous similar studies by evaluating the largest number of BIA reports ever reviewed, and uniquely provides judgement of overall utility.

The purpose of this study is to extend the research on fashion renting (FR) by investigating how personal and social motives (i.e. “subjective norms”, “perceived behavioural control”, “sustainable orientation” and “FR benefits”) affect consumers’ attitudes and intentions towards it. In addition, personality traits are investigated as potential antecedents of FR, resulting in the proposal of an overall framework that combines the theory of planned behaviour with the trait theory approach.

Data were collected in Italy from a sample of 694 consumers, mainly females (88%), with an average age of 28.8 years and coming from all over the country. The collected data were then processed via structural equation modelling.

The results indicated that intention towards FR is influenced by attitude, which, in turn, is affected by social norms, perceived behavioural control, sustainable orientation and FR benefits. Furthermore, only fashion leadership acts as a direct antecedent of FR attitude, while the need for uniqueness and materialism plays critical roles as predictors of personal and social motives. Subjective norms and perceived behavioural control also serve as mediators of the significant relationships between personality traits and attitudes towards FR.

The study provides useful implications for fashion rental companies in attracting consumers and offers a foundation for further research on transforming traditional consumption into a more sustainable one.

The study presents new knowledge on the rental phenomenon in the fashion sector by responding to the call to deepen the analysis of factors that influence consumers’ adoption of FR from the perspectives of personal and social motives and personality traits.

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.

This empirical study explores the profound impact of management functions on the productivity of yard cargo handling equipment within container terminals.

By closely examining crucial management aspects such as planning, organizing, leading and controlling, a comprehensive managerial behavior framework was developed through focus group studies (FGS) and focal interviews. These qualitative methods were complemented by the distribution of questionnaires to practitioners in Vietnam. To validate the concept of management functions and analyze their influence on effective management practices for equipment efficiency, a structural equation model (SEM) technique was employed using partial least-squares estimation (PLS).

The findings of this study demonstrate that planning (PL), organizing (OR) and controlling (CT) significantly contributes to the productivity of yard cargo handling equipment, while leading (LD) does not exhibit a direct positive impact.

Theoretically, this study contributes by providing clarity to the definition, purpose and value of management functions in the field of cargo handling equipment management. Furthermore, these research findings offer valuable insights to terminal operators and managers, enabling them to optimize their management strategies and enhance productivity levels, ultimately resulting in improved operational outcomes.