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The purpose of this paper is to examine the leadership role(s) of vice-principals in diverse, multi-ethnic schools and communities and understand the supervision and mentoring support they require to help them become more effective leaders within them. The research questions guiding this study were: what forms of mentoring do vice-principals, who serve in diverse schools in rapidly changing communities, require? Who is in the best position to provide mentoring for them?

The author used a qualitative case study methodology. Data that were analyzed for this paper were drawn from surveys, semi-structured interviews, one focus group interview and school and community documents from three data sets within two case studies in Canada. The first data set was part of the author’s doctoral research program in a diverse school in Alberta; the other case study was part of a larger collective case study that the author is currently involved with and leading in New Brunswick. Several vice-principals were part of both studies. The author then constructed a survey questionnaire specifically focused on mentoring vice-principals in diverse schools. Vice-principals in both provinces, who were part of the two studies, were invited to respond to the follow-up survey. Using a constant comparative analytical approach, the author coded and analyzed the data from all three sets together. The author formed several categories and ultimately collapsed the categories into five distinct themes that illustrated and confirmed the social realities of the vice-principals in their schools and communities.

Five key findings emerged from the analysis of the data sets. They were building leadership capacity, fostering positive relationships, increasing global awareness, reducing stress and anxiety and becoming a diversity champion and peace-builder.

To this researcher’s knowledge, this paper contributes to a significant gap in the literature on vice-principals who serve in diverse schools and communities.

The fiercely increasing dynamics in many industries, which are a result of globalization, are main reasons for the increasing number of alliances during the past decade. Firms foster the exploitation as well as the exploration processes by engaging in alliances. To do so, firms need specific capabilities, such as an alliance capability. This contribution aims at describing the development process of alliance capability. Alliance capability will be analyzed in this contribution on a theoretical and qualitative basis by performing a case study on a global acting financial institution, operating in a highly dynamic and coopetitive environment, the Deutsche Börse AG.

This paper aims to develop a conceptual framework on how the representativeness heuristic operates in the decision-making process. Specifically, the authors unbundle representativeness into its building blocks: search rule, stopping rule and decision rule. Furthermore, the focus is placed on how individual-level cognitive and behavioral factors, namely experience, intuition and overconfidence, affect the functioning of this heuristic.

From a theoretical standpoint, the authors build on dual-process theories and on the adaptive toolbox view from the “fast and frugal heuristics” perspective to develop an integrative conceptual framework that uncovers the mechanisms underlying the representativeness heuristic.

The authors’ conceptualization suggests that the search rule used in representativeness is based on analogical mapping from previous experience, the stopping rule is the representational stability of the analogs and the decision rule is the choice of the alternative upon which there is a convergence of representations and that exceeds the decision maker's aspiration level. In this framework, intuition may help the decision maker to cross-map potentially competing analogies, while overconfidence affects the search time and costs and alters both the stopping and the decision rule.

The authors develop a conceptual framework on representativeness, as one of the most common, though still poorly investigated, heuristics. The model offers a nuanced perspective that explores the cognitive and behavioral mechanisms that shape the use of representativeness in decision-making. The authors also discuss the theoretical implications of their model and outline future research avenues that may further contribute to enriching their understanding of decision-making processes.

Responding in a timely manner to product recalls emanating from the supply chain presents tremendous challenges for most firms. The source might be a supplier from the same industry located next door, or one from a completely different sector of the economy situated thousands of miles away. Yet the speed of the firm’s response is crucial to mitigating the consequences of the recall both for the firm, and consumer health and well-being. The purpose of this paper is to investigate the effects of geographic distance, industry relatedness and clustering on firm response time to a supplier-initiated product recall.

The authors test the theoretical framework via an examination of food recall announcements registered with the US Food and Drug Administration over a ten-year period. The authors develop a data set comprising 407 pairs of supplier and affected downstream manufacturing firms, and utilize cross-classified hierarchical linear modeling to understand the drivers of organizational responsiveness.

The results suggest that firm response time is lengthened by geographic distance but reduced when the supplier and affected firm operate in related industry sectors. The authors further find that as more firms in a given industry are affected by the same recall, response time deteriorates.

Product recalls in the agri-food industry are significant events initiated to protect consumer health and ensure the safety of the farm-to-fork food chain. The findings highlight how both geographic- and industry-related factors determine the speed of firm responsiveness to these events.

This paper aims to clarify the relationship between explicit and tacit knowledge in specific organizational environments. It seeks to explore processes and strategies currently being deployed as best practices in the military to see what can be learnt from them and to improve the use of knowledge assets in large‐scale organizations in high‐velocity and/or turbulent environments.

High velocity/turbulent environments are defined. The paper uses examples from the public sector and the private sector and provides a model for knowledge management in high velocity/turbulent environments (HVTE) and offers several propositions for further exploration.

The paper provides insights into how and why tacit knowledge is more important to decision making and strategic positioning in high velocity/turbulent environments. The complexity of knowledge management is enormous.

What the authors learned from the military can serve as lessons for businesses to improve their agility in high velocity/turbulent environments. Businesses can apply this knowledge in considering the types of environments they operate in and which methods of knowledge transfer would serve them best to remain competitive.

This paper addresses what the authors believe is missing in knowledge management research to date – how and when tacit knowledge is more critical to organizational success than the use of explicit knowledge. The analysis also provides an environmental framework that distinguishes the use of tacit and explicit knowledge.

The purpose of this paper is to report on a laboratory experiment in which the paper investigated how expert and novice users differ in their emotional responses during use of an enterprise resource planning (ERP) system in a decision-making context, and how such a difference affects information sourcing behavior.

In a simulated SAP business environment, participants’ emotional responses were physiologically measured based on electrodermal activity (EDA) while they made business decisions.

Results show that both expert and novice users exhibit considerable EDA activity during their interaction with the ERP system, indicating that ERP use is an emotional process for both groups. However, the findings also indicate that experts’ emotional responses led to their sourcing information from the ERP, while novices’ emotional responses led to their sourcing information from other people.

From an academic standpoint, this paper responds to the recent call for more research on the role of emotions for information systems behavior.

The paper discusses the implications of this finding for the development of ERP system trainings.

Because emotions often do not reach users’ awareness level, the paper used EDA, a neurophysiological measure, to capture users’ emotional responses during ERP decision making, instead of using self-report measures that depend on conscious perception. Based on this method, the paper found that emotions can lead to different behavioral reactions, depending on whether the user is an expert or novice.

The purpose of this paper is to draw on the naturalistic decision making and cognitive science literature to examine how experienced crisis managers utilize the intuitive and analytical strategies when managing complex incidents. A cognitive model that describes the interplay between strategies is presented and discussed, and the specific role that intuition plays in analytical decision making is addressed.

Designed as a conceptual paper, the extant literature is reviewed to advance discussions on the theme of intuitive and analytical decision making in the naturalistic environment. A new model of expert intuition – the information filtering and intuitive decision model – is presented and evaluated against existing cognitive models from the wider literature.

The paper suggests that experts’ ability to make intuitive decisions is strongly hinged on their information processing skills that allow irrelevant cues to be sifted out while the relevant cues are retained. The paper further revealed that experts generally employ the intuitive mode as their default strategy, drawing on the analytical mode only as conditions warrant.

Prior research has shown that experts often make important task decisions using intuitive or analytical strategies or by combining both, but the sequence these should typically follow is still unresolved. Findings from the intuition model reveal that although intuition often precedes analytical thinking in almost all cases, both strategies exist to offer significant values to decision makers if the basis of their application is well understood.