Let's be PALS: User‐Driven Organizational Change in Healthcare*

This paper explores user‐driven organizational change in the National Health Service (NHS). The NHS Plan ( Department of Health, 2000 ) created Patient Advice and Liaison Services (PALS) to provide information, solve problems and drive user‐led change. Evidence is drawn from a study of PALS in London acute, primary care, mental health and specialist trusts, drawing on discussion forums, interviews with PALS officers and documentation. From context and role profiles, two conclusions are evident. First, organizational instability, boundary disputes, variable management support, resource limitations, financial insecurity and multi‐site working characterize the context in which PALS operate, and the officer role is characterized by problem diversity, overlap with complaints systems, monitoring problems, relationship building and ‘serial users’. Second, these context and role attributes restrict PALS to ‘repair and maintenance’, ensuring that established systems work correctly. While PALS sit on the bottom rung of a ‘participation ladder’, their contribution is more than tokenistic. However, a processual perspective demonstrates how a fluid, networked, and diversified context isolates PALS structures from management decision‐making, constraining their power base, and inhibiting the promotion of substantive change agendas.     

A Multi‐level Dialectical–Paradox Lens for Top Management Team Strategic Decision‐Making in a Corporate Venture

This paper aims to critique the process of corporate‐owned, high‐tech start‐up strategizing through an inductive, longitudinal, case study of ‘UK‐Research‐Tech’. Insights are given through the combined ‘dialectical–paradox’ concept, thereby focusing on where ‘dialectic’ and ‘paradox’ theorizing overlap. This linked iterative, ‘dialogical–dialectic’ research approach also reflects chief executive officer/top management team (CEO/TMT) start‐up dynamics over time. These foci fill important gaps that impede better understanding of dialectical, dialogical and paradoxical forces within strategic decision‐making. As an interpretative tool, they illuminate CEO/TMT strategizing and changing interrelationships affected by broader, volatile, techno‐economic contexts and parent‐company influences on ventures. In this case study, it was found that the CEO's relatively autocratic, parent‐framed approach combined with TMT members' contradictory reactions to create ‘dialectical–paradox’ oppositional forces, eventually only resolved through ‘eleventh hour’ business strategy changes to rescue the venture. This research contributes to more nuanced understandings of corporate‐constrained ventures during early business development from start‐up strategic decisions at parent‐company level to subsequent conditions of more independent dynamic equilibrium. The ‘dialectical–paradox’ conceptual lens contributes an innovative critique of processes affecting strategic decision‐making dynamics. Another important contribution is the empirically inspired conceptual model, developed for use both to guide subsequent case‐study research analyses and as a reflective tool for CEO/TMT strategic decision‐making, especially within corporate‐inspired start‐ups.     

Collective Intuition: Implications for Improved Decision Making and Organizational Learning

This article establishes the foundation for research on collective intuition through a study of decision making and organizational learning processes in police senior management teams. We conceptualize collective intuition as independently formed judgement based on domain‐specific knowledge, experience and cognitive ability, shared and interpreted collectively. We contribute to intuition research, which has tended to focus its attention at the individual level, by studying intuition collectively in team settings. From a dual‐process perspective, we investigate how expert intuition and deliberation affect decision making and learning at various levels of the organization. Furthermore, we contribute to organizational learning research by offering an empirically derived elaboration of the foundational 4I framework, identifying additional ‘feed‐forward’ and ‘feedback’ loop processes, and thereby providing a more complete account of this organizational learning model. Bridging a variety of relevant but previously unconnected literatures via our focal concept of collective intuition, our research provides a foundation for future studies of this vitally important but under‐researched organizational phenomenon. We offer theoretical and practical implications whereby expert intuitions can be developed and leveraged collectively as valuable sources of organizational knowledge and learning, and contribute to improved decision making in organizations.     

Green supply‐chain management: A state‐of‐the‐art literature review

There is a growing need for integrating environmentally sound choices into supply‐chain management research and practice. Perusal of the literature shows that a broad frame of reference for green supply‐chain management (GrSCM) is not adequately developed. Regulatory bodies that formulate regulations to meet societal and ecological concerns to facilitate growth of business and economy also suffer from its absence. A succinct classification to help academicians, researchers and practitioners in understanding integrated GrSCM from a wider perspective is needed. Further, sufficient literature is available to warrant such classification. This paper takes an integrated and fresh look into the area of GrSCM. The literature on GrSCM is covered exhaustively from its conceptualization, primarily taking a ‘reverse logistics angle’. Using the rich body of available literature, including earlier reviews that had relatively limited perspectives, the literature on GrSCM is classified on the basis of the problem context in supply chain's major influential areas. It is also classified on the basis of methodology and approach adopted. Various mathematical tools/techniques used in literature vis‐à‐vis the contexts of GrSCM are mapped. A timeline indicating relevant papers is also provided as a ready reference. Finally, the findings and interpretations are summarized, and the main research issues and opportunities are highlighted.     

A Context‐sensitive Approach to Analysing Talk in Strategy Meetings

The talk of managers in meetings is central to organizational life and crucial to research in strategic management, as well as managerial and organizational cognition, sensemaking and decision‐making. To achieve full understanding, both the text and the context of discussion require systematic analysis, but most approaches treat context as everything that is known and observed beyond the immediate text. This obscures different readings of the text of meetings. To resolve this problem, the discourse historical approach (DHA) to critical discourse analysis is outlined as a framework within which researchers can analyse the text and context of talk in meetings. The primary contribution of this paper is to isolate four ‘levels of context’ as a heuristic framework within which discursive practices, strategies and texts can be located. By making explicit the levels of contextual analysis that are implicit in other methods, and illustrating the DHA using an episode of strategic discussion from a multinational company, this paper shows how researchers can use the approach to analyse the naturally occurring talk of senior managers in meetings, which is arguably the most important but yet under‐explored venue for strategizing.     

Farmers’ Risk‐Based Decision Making Under Pervasive Uncertainty: Cognitive Thresholds and Hazy Hedging

Researchers in judgment and decision making have long debunked the idea that we are economically rational optimizers. However, problematic assumptions of rationality remain common in studies of agricultural economics and climate change adaptation, especially those that involve quantitative models. Recent movement toward more complex agent‐based modeling provides an opportunity to reconsider the empirical basis for farmer decision making. Here, we reconceptualize farmer decision making from the ground up, using an in situ mental models approach to analyze weather and climate risk management. We assess how large‐scale commercial grain farmers in South Africa (n = 90) coordinate decisions about weather, climate variability, and climate change with those around other environmental, agronomic, economic, political, and personal risks that they manage every day. Contrary to common simplifying assumptions, we show that these farmers tend to satisfice rather than optimize as they face intractable and multifaceted uncertainty; they make imperfect use of limited information; they are differently averse to different risks; they make decisions on multiple time horizons; they are cautious in responding to changing conditions; and their diverse risk perceptions contribute to important differences in individual behaviors. We find that they use two important nonoptimizing strategies, which we call cognitive thresholds and hazy hedging, to make practical decisions under pervasive uncertainty. These strategies, evident in farmers' simultaneous use of conservation agriculture and livestock to manage weather risks, are the messy in situ performance of naturalistic decision‐making techniques. These results may inform continued research on such behavioral tendencies in narrower lab‐ and modeling‐based studies.     

Context‐Specific,Scenario‐Based Risk Scales

Reacting to an emergency requires quick decisions under stressful and dynamic conditions. To react effectively, responders need to know the right actions to take given the risks posed by the emergency. While existing research on risk scales focuses primarily on decision making in static environments with known risks, these scales may be inappropriate for conditions where the decision maker's time and mental resources are limited and may be infeasible if the actual risk probabilities are unknown. In this article, we propose a method to develop context‐specific, scenario‐based risk scales designed for emergency response training. Emergency scenarios are used as scale points, reducing our dependence on known probabilities; these are drawn from the targeted emergency context, reducing the mental resources required to interpret the scale. The scale is developed by asking trainers/trainees to rank order a range of risk scenarios and then aggregating these orderings using a Kemeny ranking. We propose measures to assess this aggregated scale's internal consistency, reliability, and validity, and we discuss how to use the scale effectively. We demonstrate our process by developing a risk scale for subsurface coal mine emergencies and test the reliability of the scale by repeating the process, with some methodological variations, several months later.     

Methodology‐as‐Technique and the Meaning of Rigour in Globalized Management Research

This paper analyses the genre of ‘methodology‐as‐technique’, which we suggest provides the underpinning logic for a particular conception of scientific rigour that is increasingly regarded as normal in globalized management research. Based on a qualitative interview study of management researchers in the peripheral context of India, we associate the methodology‐as‐technique genre with social scientific methods of organizing, conducting and disseminating knowledge founded on Western neo‐imperialism and colonialism. Our analysis draws attention to the consequences of the genre of methodology‐as‐technique which relate to a narrowing and displacement of research goals, erasure of context, and devaluation and marginalization of alternatives. By providing insight into how methodology‐as‐technique comes to dominate in peripheral locations such as India, we suggest that these normative constraints also present an opportunity for denaturalization, by making what is increasingly seen as normal appear alien or strange. We conclude by arguing that countering restrictive definitions of rigour in management research relies on development of a more expansive and inclusive conception of the global that fosters indigenous ways of knowing and promotes decolonizing methodologies.     

Innovation in Small,Project‐Based Construction Firms*

Relevant literature is synthesized to provide a holistic picture of our current knowledge of innovation in small, project‐based firms, highlighting significant gaps in the broad areas of ‘focus and outcome’, ‘organizational capabilities’, ‘context’ and ‘process’. Research findings from fieldwork focused on the construction industry are offered to address these gaps. In particular, a consensus model is given of the organizational factors dynamically at play. It is shown that typically the innovations of small, project‐based firms are closely tied to their operational activities and are pushed forward by owners who utilize very scarce resources to make progress in the interstices of normal business. This leads to an emphasis on taking up established technologies through ‘learning on the job’. Growth per se is not an important target. The motivation to act is generally to get past a survival mode of operating and to achieve stability by satisfying clients. These characteristics contrast with large organizations, especially in terms of the role of the owner, the close focus on niche markets and the lack of slack resources to innovate in parallel with normal business. It is hoped that these results will be of interest to other sectors where small, project‐based firms operate.     

Using Real‐Time Decision Tools to Improve Distributed Decision‐Making Capabilities in High‐Magnitude Crisis Situations*

Multi‐organizational collaborative decision making in high‐magnitude crisis situations requires real‐time information sharing and dynamic modeling for effective response. Information technology (IT) based decision support tools can play a key role in facilitating such effective response. We explore one promising class of decision support tools based on machine learning, known as support vector machines (SVM), which have the capability to dynamically model and analyze decision processes. To examine this capability, we use a case study with a design science approach to evaluate improved decision‐making effectiveness of an SVM algorithm in an agent‐based simulation experimental environment. Testing and evaluation of real‐time decision support tools in simulated environments provides an opportunity to assess their value under various dynamic conditions. Decision making in high‐magnitude crisis situations involves multiple different patterns of behavior, requiring the development, application, and evaluation of different models. Therefore, we employ a multistage linear support vector machine (MLSVM) algorithm that permits partitioning decision maker response into behavioral subsets, which can then individually model and examine their diverse patterns of response behavior. The results of our case study indicate that our MLSVM is clearly superior to both single stage SVMs and traditional approaches such as linear and quadratic discriminant analysis for understanding and predicting behavior. We conclude that machine learning algorithms show promise for quickly assessing response strategy behavior and for providing the capability to share information with decision makers in multi‐organizational collaborative environments, thus supporting more effective decision making in such contexts.     

The Influence of Context on the Strategic Decision‐Making Process: A Review of the Literature

This paper critically reviews the strategic decision‐making process literature, with a specific focus on the effects of context. Context refers to the top management team, strategic decision‐specific characteristics, the external environment and firm characteristics. This literature review also develops an illustrative framework that incorporates these four different categories of contextual variables that influence the strategic decision‐making process. As a result of the variety and pervasiveness of contextual variables featured within the literature, a comprehensive and up‐to‐date review is essential for organizing and synthesizing the extant literature to explicate an agenda for future research. The purpose of this literature review is threefold: first, to critically review the strategic decision‐making process literature to highlight the underlying themes, issues, tensions and debates in the field; second, to identify the opportunities for future theory development; and third, to state the methodological implications arising from this review.     

Developing a Human‐centred and Science‐based Approach to Design: The Knowledge Management Platform Project

The gap between theory and practice is a persistent problem in management and organization research. In this respect, several scholars have suggested that ‘design’ is an ideal‐typical form of mode 2 knowledge production. Design research develops knowledge in the service of action and problem solving in organizational settings. In this paper, we connect two perspectives on design that can be considered to be largely complementary but have hardly been combined and integrated in practice: science‐based design drawing on design propositions grounded in research and human‐centred design emphasizing an active and systematic participation by users and other stakeholders. An integrated approach that builds on both perspectives is developed and subsequently applied to designing and developing a portal for mapping competencies in an information technology cluster. This project involves creating problem awareness and articulating design propositions as well as developing scenarios of use, experimenting with prototypes, and organizational transformation. As such, this methodology addresses the dual challenge of rigour and relevance by producing both scientific and practical knowledge.     

The Role of Project and Organizational Context in Managing High‐tech R&D Projects

High‐tech organizations often struggle to manage different types of R&D projects. Evidence from research and practice suggests that managers frequently categorize and manage projects based on the extent of change triggered in product, process, technology, and market dimensions. However, this can create challenges in high‐tech organizations. This study investigates how high‐tech organizations manage R&D projects based on their learning goals. First, we argue for the benefits of categorizing R&D projects based on the degree of exploration and exploitation learning goals. A qualitative case study from four high‐tech business units involving 10 R&D projects helps understand the different types of projects based on their learning goals. The case study shows that R&D projects in high‐tech organizations typically fall into three categories based on their learning goals: Radical innovation projects, Incremental innovation projects, and Hybrid projects. Second, we iterate between literature and evidence from our qualitative data to theorize how project context and organizational context affect project performance depending on the type of project. The data for the empirical analysis come from a multilevel survey of 110 R&D projects across 34 high‐tech business units. Results show the importance of designing project and organizational context differently for the three types of R&D projects. Collectively, this study offers a new perspective on how to manage high‐tech R&D projects.     

How Anxiety Leads to Suboptimal Decisions Under Risky Choice Situations

The current research proposes that situationally activated anxiety—whether incidental or integral—impairs decision making. In particular, we theorize that anxiety drives decisionmakers to more heavily emphasize subjective anecdotal information in their decision making, at the expense of more factual statistical information—a deleterious heuristic called the anecdotal bias. Four studies provide consistent support for this assertion. Studies 1A and 1B feature field experiments that demonstrate the role of incidental anxiety in enhancing the anecdotal bias in a choice context. Study 2 builds on these findings, manipulating individuals’ incidental anxiety and showing how this affects the anecdotal bias in the context of message evaluations. Study 2 also provides direct evidence that only high‐arousal negative emotions such as anxiety/worry enhance the anecdotal bias, not just any negative emotion (e.g., sadness). While the first three studies examine how incidental anxiety impacts choice, the last study demonstrates the effect of integral anxiety on decision making, manipulating anxiety by intensifying participants’ perceived risk. Our results show that—consistent with findings from our first three studies—the anecdotal bias is enhanced when anxiety is heightened by individuals’ perception of risk.     

Coordinating Service‐Sensitive Demand and Capacity by Adaptive Decision Making: An Application of Case‐Based Decision Theory*

The subject of this article is the simultaneous choice of product price and manufacturing capacity if demand is stochastic and service‐level sensitive. In this setting, capacity as well as price have an impact on demand because several aspects of service level depend on capacity. For example, delivery time will be reduced if capacity is increased given a constant demand rate. We illustrate the relationship between service level, capacity, and demand reaction by a stylized application problem from the after‐sales services industry. The reaction of customers to variations in service level and price is represented by a kinked price‐demand‐rate function. We first derive the optimal price‐capacity combination for the resulting decision problem under full information. Subsequently, we focus on a decision maker (DM) who lacks complete knowledge of the demand function. Hence the DM is unable to anticipate the service level and consequently cannot identify the optimal solution. However, the DM will acquire additional information during the sales process and use it in subsequent revisions of the price‐capacity decision. Thus, this decision making is adaptive and based on experience. In contrast to the literature, which assumes certain repetitive procedures somewhat ad hoc, we develop an adaptive decision process based on case‐based decision theory (CBDT) for the price‐capacity problem. Finally, we show that a CBDT DM in our setting eventually finds the optimal solution, if the DM sets the price based on absorption costs and adequately adjusts the capacity with respect to the observed demand.     

Media Effects on Group Collaboration: An Empirical Examination in an Ethical Decision‐Making Context

Even though it is widely acknowledged that collaboration underlies much of the decision‐making efforts in contemporary organizations, and that organizational groups are increasingly making decisions that have ethical implications, few studies have examined group ethical decision‐making processes and outcomes. In addition, while there is increasing evidence that groups often collaborate/communicate using different mediating technologies, few studies have examined the effect of the characteristics of the media in group ethical decision‐making contexts. Finally, there is a clear paucity of studies that have investigated group decision making pertaining to information technology (IT)‐related ethical dilemmas, an area of rising importance for information systems (IS) and decision science researchers. This article seeks to address the gaps described above through an experimental study where groups collaborating either in a face‐to‐face context or in a computer‐mediated context (using NetMeeting or Wiki) were required to make a decision with respect to a scenario with an IT‐related ethical dilemma. Results indicate that media characteristics (e.g., anonymity, immediacy of feedback, parallelism) do not have an effect on whether groups make ethical (or unethical) decisions. However, several media characteristics were found to play a significant role on downstream variables, such as the quality of a follow‐up task (i.e., creation of a decision justification document), and overall process satisfaction of the group members.     

Negotiating Imitation: Examining the Interactions of Consultants and Clients to Understand Institutionalization as Translation

Organizational scholars increasingly view institutionalization as a process through which actors adapt or translate seemingly successful practices in a field to create variations that are specific to their own organization. Yet little is known about how outsiders who seek to diffuse ‘best practice’ affect translation. We examined interactions between management consultants and their clients in two different consulting projects, which focused on embedding the practice of ‘lean’ in one and the practice of a quality improvement framework in the other. Our findings provide insights into the processes of translation through which promoters and adopters iterate at different stages to reach a compromise, illuminating how the evolution of an imported practice signals the outcome of a negotiation. Furthermore, we demonstrate that management practices are not translated in isolation but enveloped by peripheral practices that are adopted by association. We highlight how the peripheral practice of benchmarking, in both cases, was rarely contested or negotiated and thus proved more resistant to translation. Our analysis allows us to unpack the agency inherent within translation‐as‐negotiation and integrate research on diffusion and translation.     

‘Bureaucracy‐lite’ and Continuities in Managerial Work

This paper questions three frequently asserted, interrelated claims about developments in management: that centralized, regulated bureaucratic organizations characterized by hierarchy and rules are inevitably giving way to decentralized and empowered post‐bureaucratic organizations characterized by internal networks and an internal market; that, as a consequence, the traditional managerial role of command and control is being superseded by one of facilitation and coordination; and that, in turn, managerial work as routine administration of work processes is being supplanted by the ‘new managerial work’ of non‐routine leadership and entrepreneurship. It is argued that these claims often rest on caricatures of bureaucracy and network organization and are neither new nor well supported by evidence. Against these claims, the paper adduces case‐study evidence which shows that, despite claims about ‘decentralization’ and ‘empowerment’, organizational change may entail not a radical shift to network organization, but more limited change to a different form of bureaucracy in which hierarchy and rules have been retained but in an attenuated and sharper form –‘bureaucracy‐lite’. Consequently, managerial roles continue to be defined in terms of individual responsibility and vertical accountability for an organizational sub‐unit, and managerial work continues to be preoccupied with monitoring and maintaining work processes, routine direction and control of staff and processing information in order to deal with the ambiguities inherent in the dimensions of managerial ‘responsibility’.     

An Entropy‐Based Methodology for Valuation of Demand Uncertainty Reduction

We propose a distribution‐free entropy‐based methodology to calculate the expected value of an uncertainty reduction effort and present our results within the context of reducing demand uncertainty. In contrast to existing techniques, the methodology does not require a priori assumptions regarding the underlying demand distribution, does not require sampled observations to be the mechanism by which uncertainty is reduced, and provides an expectation of information value as opposed to an upper bound. In our methodology, a decision maker uses his existing knowledge combined with the maximum entropy principle to model both his present and potential future states of uncertainty as probability densities over all possible demand distributions. Modeling uncertainty in this way provides for a theoretically justified and intuitively satisfying method of valuing an uncertainty reduction effort without knowing the information to be revealed. We demonstrate the methodology's use in three different settings: (i) a newsvendor valuing knowledge of expected demand, (ii) a short life cycle product supply manager considering the adoption of a quick response strategy, and (iii) a revenue manager making a pricing decision with limited knowledge of the market potential for his product.     

Invisible Whispering: Restructuring Collaborative Decision Making with Instant Messaging

Organizational decision making is dominated by teams. When an important decision is required, a team is often formed to make it or to advise the individual decision maker, because a team has more resources, knowledge, and political insight than any one individual working alone. As teams have become geographically distributed, collaboration technology has come to play an important role in such collective decision making efforts. Instant messaging (IM) is an increasingly prevalent workplace collaboration technology that enables near‐synchronous text exchanges on a variety of devices. We examined the use of IM during face‐to‐face, telephone, and computer‐mediated team meetings, a practice we call “invisible whispering.” We introduce Goffman's characterization of social interaction as dramatic performance, differentiable into “front stage” and “backstage” exchanges, to analyze how invisible whispering alters the socio‐spatial and temporal boundaries of team decision making. Using IM, workers were able to influence front stage decision making through backstage conversations, often participating in multiple backstage conversations simultaneously. This type of interaction would be either physically impossible or socially constrained without the use of IM. We examine how invisible whispering changes the processes of collaborative decision making and how these new processes may affect the efficiency and effectiveness of collaborative decision making, as well as participation, satisfaction, relationships among team members, and individual attention.