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To remain competitive, efficient and productive, organisations need to ensure that their employees continuously learn and develop. This is even more challenging and critical in times characterised by volatility, uncertainty, complexity and ambiguity (VUCA). Hence, several technological applications have been introduced with the promise to make organisational training and development (T&D) more efficient and targeted through digitisation and automation. However, digitising and automating processes in the sensitive field of T&D also poses challenges and perils for employees and organisations as a whole.

Structured by the T&D process of (1) assessment/planning, (2) design/implementation and (3) evaluation, the authors present different digitisation and automation possibilities and discuss the specific opportunities and challenges they pose. Subsequently, the authors identify and discuss overarching themes of opportunities and challenges of technology use in T&D via a meta-review.

This synthesis revealed three central topics that decision-makers in T&D should carefully consider when it comes to the implementation of technological applications: opportunities and challenges of (1) data collection, (2) decision-making and (3) the value of human contact.

This review integrates previously fragmented research on specific technologies applied to specific T&D functions and provides researchers and practitioners with a fuller picture of the opportunities and challenges of technology applied in T&D.

This paper examines the relationship between marketing automation emergence and the marketers' use of heuristics in their decision-making processes. Heuristics play a role for the integration of human decision-making models and automation in augmentation processes, particularly in marketing where automation is widespread.

This study analyzes qualitative data about the impact of marketing automation on the scope of heuristics in decision-making models, and it is based on evidence collected from interviews with twenty-two experienced marketers.

Marketers make extensive use of heuristics to manage their tasks. While the adoption of new automatic marketing tools modify the task environment and field of use of traditional decision-making models, the adoption of heuristics rules with a different scope is essential to defining inputs, interpreting/evaluating outputs and control the marketing automation system.

The paper makes a contribution to research on the relationship between marketing automation and decision-making models. In particular, it proposes the results of in-depth interviews with senior decision makers to assess the impact of marketing automation on the scope of heuristics as decision-making models adopted by marketers.

This paper aims to explore how accounting is fostering neoliberal citizenship through the participants of Australia’s National Disability Insurance Scheme (NDIS). More specifically, this paper aims to understand how accounting discourse and the management accounting technique of budgeting, when intertwined with automated administrative processes of the NDIS, are giving rise to a pastoral form of power that directs people’s behaviour toward certain ends.

Publicly available data has been crafted into an autoethnographic case study of one fictitious person’s experiences with the NDIS – Mina. Mina is an amalgam created from material submitted to the Joint Parliamentary Standing Committee on the NDIS. Mina’s experiences are then analysed through the lens of Foucault’s concept of pastoral power to explore how accounting has contributed to marketising and digitising public disability services.

Accounting rhetoric appears to be a central part of rationalising the decision to shift to individualised disability funding. Those receiving payments are treated as self-governable, financially responsible subjects and are therefore expected to have knowledge of management accounting techniques and budgeting. However, NDIS’s strong reliance on the accounting concepts of funds, budgets, cost and price is limiting people’s autonomy and subjecting them to intervention and control.

This paper addresses calls to explore the interplay between accounting and current disability policies. The analysis shows that incorporating accounting into the NDIS’s algorithms serves to conceal the underlying ideology of the programs, subtly driving behaviours towards neoliberal objectives. Further, this research extends the Foucauldian accounting literature by revealing the contribution of accounting to reinforcing the authority of digital pastors in contemporary times.

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

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.

The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The topic of artificial intelligence (AI) has been expanding rapidly in recent years, gaining the attention of academics and practitioners. This study provides a structured literature review (SLR) on AI and management decisions (MDs) by analysing the scientific output and defining new research topics.

The study uses a rigorous methodological approach to summarise the state of the art of the past literature. The authors used Scopus as the database for data collection and utilised the Bibliometrix R package. In total, 204 peer-reviewed English articles were collected and analysed.

The results showed that literature in this field is emerging. Studies are focused on using AI as forecasting and classification for management decision-making, AI as a tool to improve knowledge management in organisations and extract information. The cluster analysis revealed the presence of five thematic clusters of studies on the topic.

The study’s originality lies in providing a new perspective on AI for MDs. In particular, the analysis reveals a new classification of research streams and provides fruitful research questions to continue research on the topic.

We studied the relationship between job engagement and systematic problem solving (SPS) among shop-floor employees and how lean production (LP) and Internet of Things (IoT) systems moderate this relationship.

We collected data from a sample of 440 shop floor workers in 101 manufacturing work units across 33 plants. Because our data is nested, we employed a series of multilevel regression models to test the hypotheses. The application of IoT systems within work units was evaluated by our research team through direct observations from on-site visits.

Our findings indicate a positive association between job engagement and SPS. Additionally, we found that the adoption of lean bundles positively moderates this relationship, while, surprisingly, the adoption of IoT systems negatively moderates this relationship. Interestingly, we found that, when the adoption of IoT systems is complemented by a lean management system, workers tend to experience a higher effect on the SPS of their engagement.

One limitation of this research is the reliance on the self-reported data collected from both workers (job engagement, SPS and control variables) and supervisors (lean bundles). Furthermore, our study was conducted in a specific country, Italy, which might have limitations on the generalizability of the results since cross-cultural differences in job engagement and SPS have been documented.

Our findings highlight that employees’ strong engagement in SPS behaviors is shaped by the managerial and technological systems implemented on the shop floor. Specifically, we point out that implementing IoT systems without the appropriate managerial practices can pose challenges to fostering employee engagement and SPS.

This paper provides new insights on how lean and new technologies contribute to the development of learning-to-learn capabilities at the individual level by empirically analyzing the moderating effects of IoT systems and LP on the relationship between job engagement and SPS.

The purpose of this study is to examine public perceptions and attitudes toward using artificial intelligence (AI) in the US criminal justice system.

The authors took a quantitative approach and administered an online survey using the Amazon Mechanical Turk platform. The instrument was developed by integrating prior literature to create multiple scales for measuring public perceptions and attitudes.

The findings suggest that despite the various attempts, there are still significant perceptions of sociodemographic bias in the criminal justice system and technology alone cannot alleviate them. However, AI can assist judges in making fairer and more objective decisions by using triangulation – offering additional data points to offset individual biases.

Other scholars can build upon the findings and extend the work to shed more light on some problems of growing concern for society – bias and inequality in criminal sentencing. AI can be a valuable tool to assist judges in the decision-making process by offering diverse viewpoints. Furthermore, the authors bridge the gap between the fields of technology and criminal justice and demonstrate how the two can be successfully integrated for the benefit of society.

To the best of the authors’ knowledge, this is among the first studies to examine a complex societal problem like the introduction of technology in a high-stakes environment – the US criminal justice system. Understanding how AI is perceived by society is necessary to develop more transparent and unbiased algorithms for assisting judges in making fair and equitable sentencing decisions. In addition, the authors developed and validated a new scale that can be used to further examine this novel approach to criminal sentencing in the future.