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This paper argues for the need to use multiple sources and methods that respond to research challenges presented by new forms of war. There are methodological constraints and contention on the superiority given to positivist and interpretivist research designs when doing fieldwork in war situations, hence there is a need to use integrated data generation techniques. The combined effect of severe limitations of movement for both the researcher and researched fragmented data because of polarized views about the causes of the war and unpredictable events that make information hard to come by militate against systematic, organised and robust data generation. The purpose of this paper, therefore, is to make fieldwork researchers understand significant research problems unique to war zones.

This research was guided by the postmodernist mode of thought which challenges standardised research traditions. Fieldwork experiences in Cabo suggest the need to use the composite strategies that rely on the theoretical foundation of integrative and creative collection of data when doing research in violent settings.

The fieldwork experiences showed that the standardised, conventional and valorised positivist and ethnographic research strategies may not sufficiently facilitate understanding of the dynamics of war. There should not be firm rules, guidelines or regulations governing the actions of the researcher in conflict. As such, doing research in violent settings require reflexivity, flexibility and creativity in research strategies that respond to rapid changes. Research experiences in Mozambique show the need to use blended methods that include even less structured methodologies.

Fieldwork experiences in Cabo challenges researchers who cling to standardised research traditions which often hamper awareness of new postmodernist mode of thought applicable to war settings. It is essential to study the nature of African armed conflicts by combining creativity and flexibility in the selection of research strategies.

To date, to the best of the authors’ knowledge, the use of implicit measures in the service research domain is limited. This paper aims to introduce implicit measures and explain why, or for what purpose, they are worthwhile to consider; how these measures can be used; and when and where implicit measures merit the service researcher’s consideration.

To gain an understanding of how implicit measures could benefit service research, three promising implicit measures are discussed, namely, the implicit association test, the affect misattribution procedure and the propositional evaluation paradigm. More specifically, this paper delves into how implicit measures can support service research, focusing on three focal service topics, namely, technology, affective processes including customer experience and service employees.

This paper demonstrates how implicit measures can investigate paramount service-related subjects. Additionally, it provides essential methodological “need-to-knows” for assessing others’ work with implicit measures and/or for starting your own use of them.

This paper introduces when and why to consider integrating implicit measures in service research, along with a roadmap on how to get started.

Corporations are confronted with growing demands to take a stand on socio-political issues, i.e. corporate social advocacy (CSA), which affects their reputation in the public. Companies use different CSA message strategies, including calling the public to support and act on the issue they advocate. Using reactance theory, the authors investigate the impact of CSA messages with a call to action on corporate reputation in the case of a company's gender equality initiative.

A one-factorial (CSA message with or without a call to action) between-subjects experiment was conducted by surveying 172 individuals living in Switzerland. The CSA messages were created in the context of gender equality.

The authors' study indicates that CSA messages with a call to action compared to those without overall harmed corporate reputation due to individuals' reactance, which is higher for CSA messages with a call to action, negatively affecting corporate reputation. The impact of the CSA message strategy with a call to action on corporate reputation remains significant after controlling for issue alignment and political leaning.

Communicating about socio-political issues, especially taking a stand, is a significant challenge for corporations in an increasingly polarized society and has often led to backlash, boycotts and damage to corporate reputation. This study shows that the possible adverse effects of advocating for socio-political issues can be related to reactance. It emphasizes that companies advocating for contested issues must be more cautious about the message strategy than the issue itself.

Recent high-profile ethical scandals in start-up organizations have made people wonder whether entrepreneurship may cultivate a work environment with less emphasis on ethics. This study examined a psychological process about how an organization’s entrepreneurial orientation (EO) can affect its treatment of probationary employees, a vulnerable yet understudied group of workers.

The authors recruited 241 participants through Amazon Mechanical Turk. They answered an online survey about their experiences as probationary employees.

This study found that job feedback and meaning moderated the relationship between EO and ethical climate, such that this relationship was statistically significant and positive only among participants who reported high levels of feedback and job meaning. Ethical climate, in turn, was found to be related to a reduction in workplace incivility experienced by probationary employees. The indirect effect of EO on incivility via ethical climate was contingent on job feedback and meaning.

This study extends the discussion on the entrepreneurial context, adds to EO literature with findings on its indirect effect on nonfinancial performance and reinforces institutional theory through job characteristics’ moderating roles. However, a methodological limitation is conducting a cross-sectional single-source survey due to limited access to firms and probationary employees, considering the hidden population involved.

This study found no evidence of probationary employee exploitation in high EO organizations. Job seekers should embrace probationary work at start-ups. Entrepreneurial leaders should balance being proactive, innovative and caring toward employees.

It is debatable whether entrepreneurship leads to unethical organizational conduct. By studying a vulnerable group of employees, the authors discovered that EO, when paired with favorable job design factors, can create a more ethical workplace where temporary talents are treated with dignity and respect.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

Research on online user privacy shows that empirical evidence on how privacy literacy relates to users' information privacy empowerment is missing. To fill this gap, this paper investigated the respective influence of two primary dimensions of online privacy literacy – namely declarative and procedural knowledge – on online users' information privacy empowerment.

An empirical analysis is conducted using a dataset collected in Europe. This survey was conducted in 2019 among 27,524 representative respondents of the European population.

The main results show that users' procedural knowledge is positively linked to users' privacy empowerment. The relationship between users' declarative knowledge and users' privacy empowerment is partially supported. While greater awareness about firms and organizations practices in terms of data collections and further uses conditions was found to be significantly associated with increased users' privacy empowerment, unpredictably, results revealed that the awareness about the GDPR and user’s privacy empowerment are negatively associated. The empirical findings reveal also that greater online privacy literacy is associated with heightened users' information privacy empowerment.

While few advanced studies made systematic efforts to measure changes occurred on websites since the GDPR enforcement, it remains unclear, however, how individuals perceive, understand and apply the GDPR rights/guarantees and their likelihood to strengthen users' information privacy control. Therefore, this paper contributes empirically to understanding how online users' privacy literacy shaped by both users' declarative and procedural knowledge is likely to affect users' information privacy empowerment. The study empirically investigates the effectiveness of the GDPR in raising users' information privacy empowerment from user-based perspective. Results stress the importance of greater transparency of data tracking and processing decisions made by online businesses and services to strengthen users' control over information privacy. Study findings also put emphasis on the crucial need for more educational efforts to raise users' awareness about the GDPR rights/guarantees related to data protection. Empirical findings also show that users who are more likely to adopt self-protective approaches to reinforce personal data privacy are more likely to perceive greater control over personal data. A broad implication of this finding for practitioners and E-businesses stresses the need for empowering users with adequate privacy protection tools to ensure more confidential transactions.

As women’s position in the economy and society is often explained by cultural factors, this study aims to verify whether the observed changes in female empowerment in the region of Central and East European (CEE) countries of the European Union (EU) are associated with masculinity as a cultural trait.

The authors apply the k-means clustering method to group CEE countries into clusters with similar levels of female empowerment in two time points – 2013 and 2019. Next, the authors examine the clusters and cross-reference them with the national culture’s masculinity to explore the interrelations between female empowerment and cultural traits in the CEE countries and their development in time.

The analyses reveal that female empowerment is not uniform or stable across the CEE countries. The masculinity level is not strongly related to women’s position in these countries, and changes in female empowerment are not closely linked to masculinity.

Despite the tumultuous history of women’s empowerment in the CEE countries, the issues related to gender equality and cultural traits pertaining to the region are relatively understudied in the literature. By focusing on the CEE region, the authors fill the gap in examining the independencies between female empowerment and cultural masculinity.

Four reputed leaders for the coming years in the field of special education for individuals with emotional and behavioral disorders (EBD) each with a slightly different perspective on the field were asked to respond independently to a prompt asking what does special education mean for students with EBD and what is being done and how do we maintain tradition? The contributors' responses to the prompt are presented and then summarized across the essays. A remarkable consistency emerges across the independent essays. In addition to the tradition of providing a free and appropriate education in the least restrictive environment, the contributors identify needs to support teachers serving this population. Needs in teacher training and the expertise required to meet the needs of individuals with EBD are outlined as well as potential contributions of technology to carry out specific tasks. We conclude with a call for increased advocacy for use of the knowledge that we currently possess and that which will soon be discovered to support students with EBD as well as their teachers. We also note that the contributors' names are listed alphabetically to acknowledge the equality of each person to the final product.

Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.