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What would a graduate program look like if its purpose was to create transformational leaders? How and what would we teach? How and what would students learn? How would students work together? What would be the role of the faculty? This paper describes the creation and delivery of a graduate program that develops students as transformational leaders. The paper also outlines the paradigmatic shifts in design principles used in the program to achieve our purpose. The outcome assessment of students’ leadership competencies at the conclusion of the program showed marked improvement. In a final reflection paper, students share the impact the program has had on transforming their lives.

In this article, we reflect on how smart technology is transforming service research discourses about service innovation and value co-creation. We adopt the concept of technology smartness’ to refer to the ability of technology to sense, adapt and learn from interactions. Accordingly, we seek to address how smart technologies (i.e. cognitive and distributed technology) can be powerful resources, capable of innovating in relation to actors’ agency, the structure of the service ecosystem and value co-creation practices.

This conceptual article integrates evidence from the existing theories with illustrative examples to advance research on service innovation and value co-creation.

Through the performative utterances of new tech words, such as onlife and materiality, this article identifies the emergence of innovative forms of agency and structure. Onlife agency entails automated, relational and performative forms, which provide for new decision-making capabilities and expanded opportunities to co-create value. Phygital materiality pertains to new structural features, comprised of new resources and contexts that have distinctive intelligence, autonomy and performativity. The dialectic between onlife agency and phygital materiality (structure) lies in the agencement of smart tech–enabled value co-creation practices based on the notion of becoming that involves not only resources but also actors and contexts.

This paper proposes a novel conceptual framework that advances a tech-based ecology for service ecosystems, in which value co-creation is enacted by the smartness of technology, which emerges through systemic and performative intra-actions between actors (onlife agency), resources and contexts (phygital materiality and structure).

Artificial intelligence (AI)-based chatbots have brought unprecedented business potential. This study aims to explore consumers' trust and response to a text-based chatbot in e-commerce, involving the moderating effects of task complexity and chatbot identity disclosure.

A survey method with 299 useable responses was conducted in this research. This study adopted the ordinary least squares regression to test the hypotheses.

First, the consumers' perception of both the empathy and friendliness of the chatbot positively impacts their trust in it. Second, task complexity negatively moderates the relationship between friendliness and consumers' trust. Third, disclosure of the text-based chatbot negatively moderates the relationship between empathy and consumers' trust, while it positively moderates the relationship between friendliness and consumers' trust. Fourth, consumers' trust in the chatbot increases their reliance on the chatbot and decreases their resistance to the chatbot in future interactions.

Adopting the stimulus–organism–response (SOR) framework, this study provides important insights on consumers' perception and response to the text-based chatbot. The findings of this research also make suggestions that can increase consumers' positive responses to text-based chatbots.

Extant studies have investigated the effects of automated bots' attributes on consumers' perceptions. However, the boundary conditions of these effects are largely ignored. This research is one of the first attempts to provide a deep understanding of consumers' responses to a chatbot.

The purpose of this paper is to investigate whether guests’ tipping motivations (i.e. server quality, social norm and food quality) and demographic characteristics (i.e. gender, age and income) influence loyalty to the server in a restaurant.

Based on a national online survey consumer panel comprised of 468 participants, the authors utilized decision tree using R statistical software. Predictor variables were tipping motivations and demographic characteristics (age, gender and income). Target variable was loyalty to the server.

The findings suggest that social norm, food quality and income influence customers’ loyalty toward the same server on future visits. Social norm turned out to be the strongest predictor. If consumers did not have high social norm on tipping, their loyalty toward a particular server was affected by the combination of determinants such as server quality, social norm, income and food quality.

Future research can identify or develop scales of tipping motivations with stronger reliabilities in the context of restaurants. Future research can also explore other demographic differences (e.g. ethnicity and sexual orientation) in tipping motivations and server loyalty.

Servers are indeed the primary contact point and they are in the most influential position with consumers. Overall, results of this study provide an interesting insight in that restaurant guests’ experience can be ruined by bad quality of food or can be mitigated by server quality. Thus, this research highlights a step-by-step process as to the actions that a server may perform and manage in order to enhance server loyalty.

Loyalty has been examined in the context of products, brands or service providers. This study focuses on loyalty toward a specific server, because the consideration of server–guest relationship provides both a compelling and timely area of study in that restaurants continue to look for unique ways to drive server–guest rapport and customer loyalty.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

This study aims to estimate the value of the impact from digital transformation (DX) focusing on its automation effect, looking at the time and cost savings coming from the substitution effect with an adoption of digital technologies. For example, cloud and artificial intelligence technologies such as ChatGPT have the potential to change ways of working, substituting and replacing several of the tasks that are currently carried out by public administration (PA) employees and labor processes underpinning PA services.

The paper outlines a new framework to estimate the potential impact of DX on the public sector. The authors apply this framework to estimate the value of the impact of DX on the Italian PA, defining the latter by the collection of the value of its labor (i.e. PA workforce salaries) and by the collection of the value of its outputs (i.e. public services’ costs).

This study ultimately maps out the magnitude and trends of how likely the PA occupations and services could be substituted in a wider process of DX. To do this, the authors apply their framework to the Italian PA, and they triangulate secondary data collection, from official accounts of the Italian Ministry of Economics and the National Statistical Institute, with methodological antecedents from the UK Office for National Statistics and experts’ insights. Results provide a snapshot on the type and magnitude of PA jobs and services projected to be affected by automation over the next 10 years.

To the best of the authors’ knowledge, this paper provides for the first time an approach to estimate the value of the impact of DX on the public sector in a data-constrained environment – or in the lack of the required primary data. Once applied to the Italian PA, this approach provides a granular map of the automatability of each of the PA occupations and of the PA services. Finally, this paper mentions preliminary insights on potential challenges related to equity in public sector jobs and implications on recruitment processes.

This article aims to trace the historical development of the behavioral strategy (BS) field, which implements psychology in strategic management. Mainly, it provides a contextual understanding of how this stream of research has historically evolved and what relevant future trajectories are. This work is part of the “over half a century of Management Decision” celebrative and informal Journal section.

We consider BS literature produced in management decision (MD), the oldest and longest-running scholarly publication in management, as a proxy for the evolution of management thought. Through a Systematic Literature Review (SLR) process, we collected – via the MD website and Scopus – a sample of 97 BS articles published in MD from its foundation (1967) until today (2024). Regarding the analysis, we adopted a Reflexive Thematic Analysis approach to synthesize the main BS topics, then read from a historical perspective regarding three “eras” over which the literature developed. Selected international literature outside the Journal’s boundaries was considered to complement this historical analysis.

Historically, within the BS field, the interest passed from the rules to rationally govern strategic decision-making processes, to studying what causes cognitive errors, to understanding how to avoid biases and to being prepared for dramatic changes. The article also identifies six future research trajectories, namely “positive heuristics,” “context-embedded mental processes,” “non-conventional thinking,” “cognitive evolutionary triggers,” “debiasing strategies” and “behavioral theories for new strategic challenges” that future research could investigate.

The limitation of the study lies in its exclusive focus on MD for investigating the historical evolution of BS, thereby overlooking critical contributions from other journals. Therefore, MD’s editorial preferences have influenced results. A comprehensive SLR on the BS field is still needed, requiring broader journal coverage to mitigate selection biases and enhance field appraisal.

This contribution is the first to offer a historical evolutionary view of the BS field, complementing the few other reviews on this stream of research. This fills a gap in the study of the evolution of management thought.

This paper aims to explore the intersection of artificial intelligence (AI) and marketing within the context of knowledge management (KM). It investigates how AI technologies facilitate data-driven decision-making, enhance business communication, improve customer personalization, optimize marketing campaigns and boost overall marketing effectiveness.

This study uses a quantitative and systematic approach, integrating citation analysis, text mining and co-citation analysis to examine foundational research areas and the evolution of AI in marketing. This comprehensive analysis addresses the current gap in empirical investigations of AI’s influence on marketing and its future developments.

This study identifies three main perspectives that have shaped the foundation of AI in marketing: proxy, tool and ensemble views. It develops a managerially relevant conceptual framework that outlines future research directions and expands the boundaries of AI and marketing literature within the KM landscape.

This research proposes a conceptual model that integrates AI and marketing within the KM context, offering new research trajectories. This study provides a holistic view of how AI can enhance knowledge sharing, strategic planning and decision-making in marketing.

This study aims to examine the scope and contribution of Forensic Clinical Psychology (FCP) advice from the National Crime Agency (NCA) to criminal investigations in the UK to address the gap in current knowledge and research.

The 36 FCP reports reviewed were written between 2017 and 2021. They were analysed using Toulmin’s (1958) application of pertinent arguments to the evaluation process. The potential utility of the reports was analysed in terms of the advice provided.

Most of the reports involved murder and equivocal death. The reports focused primarily on understanding the offender’s psychopathology, actions, motivation and risk to self and others using a practitioner model of case study methodology. Out of the 539 claims, grounds were provided for 99% of the claims, 91% had designated modality, 62% of the claims were potentially verifiable and 57% of the claims were supported by a warrant and/or backing. Most of the reports provided either moderate or high insight into the offence/offender (92%) and potential for new leads (64%).

The advice provided relied heavily on extensive forensic clinical and investigative experience of offenders, guided by theory and research and was often performed under considerable time pressure. Flexibility, impartiality, rigour and resilience are essential prerequisites for this type of work.

To the best of the authors’ knowledge, this study is the first to systematically evaluate forensic clinical psychology reports from the NCA. It shows the pragmatic, dynamic and varied nature of FCP contributions to investigations and its potential utility.

This study demonstrates how artificial intelligence (AI) shapes the strategic planning process in volatile, uncertain, complex and ambiguous (VUCA) business environments. Having adopted various domains of the Cynefin framework, the research explores AI's transformative potential and provide insights regarding how organisations can harness AI-driven solutions for strategic planning.

This conceptual paper theorises the role of AI in strategic planning process in a VUCA world by integrating extant knowledge across multiple literature streams. The “model paper” approach was adopted to provide a theoretical framework predicting relationships among considered concepts.

The paper highlights potential application of the Cynefin framework to manage complexities in strategic decision-making process, the transformative impact of AI at different stages of strategic planning, the required strategic planning characteristics within VUCA to be supported by AI and the attendant challenges posed by AI integration in the uncertain business landscape.

This study pioneers a theoretical exploration of AI's role in strategic planning within the VUCA business landscape, guided by the Cynefin framework. Thus, it enriches scholarly discourse and expands knowledge frontiers.