Moral Utility Theory: Understanding the motivation to behave (un)ethically

Moral Utility Theory provides an integrative framework for understanding the motivational basis of ethical decision making by modeling it as a process of subjective expected utility (SEU) maximization. The SEUs of ethical and unethical behavioral options are proposed to be assessed intuitively during goal pursuit, with unethical conduct emerging when the expected benefits of moral transgressions outweigh the expected costs. A key insight of the model is that any factors that increase the value of a goal—including incentives, framings, and mindsets—can motivate misbehavior by increasing the SEU of unethical conduct. Although Moral Utility Theory emphasizes the automatic and habitual nature of most SEU appraisals, it also describes a mechanism for initiating the deliberative moral reasoning process: the experience of moral uncertainty. Moral uncertainty is proposed to occur when the SEUs of ethical and unethical behaviors are similar in magnitude, thereby activating the behavioral inhibition system and motivating the allocation of attentional resources toward the decision process. This framework bridges the gap between affective and cognitive perspectives on ethical decision making by identifying automatic evaluations as a central driver of moral decisions while also specifying when and how moral reasoning processes are initiated. By combining dual-process models of morality with well-validated principles from the science of motivation, Moral Utility Theory provides theoretical parsimony and formal modeling potential to the study of ethical decision making. The framework also suggests practical strategies—from employee selection and training to goal setting and compensation systems—for encouraging ethical behavior in organizations.     

Electronic Data Interchange: Research Review and Future Directions*

For nearly two decades, electronic data interchange (EDI) has been widely viewed as a technology pivotal to supply chain management that has also provided benefits to firms on multiple levels. Despite a substantial body of literature, there are a number of conflicting and inconclusive research results in this field. In this study, we synthesize the diverse body of research in EDI by organizing the literature into an initial theoretical framework. Based on a meta‐analysis of results from the empirical literature, we seek to clarify conflicting results from the literature in order to develop a more unified theoretical framework of contextual variables associated with EDI adoption factors and outcomes. From a managerial standpoint, our literature‐based framework offers a set of guidelines for making successful EDI adoption and implementation decisions.     

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.     

Expanding the Reach of Participatory Risk Management: Testing an Online Decision‐Aiding Framework for Informing Internally Consistent Choices

This article presents research aimed at developing and testing an online, multistakeholder decision‐aiding framework for informing multiattribute risk management choices associated with energy development and climate change. The framework was designed to provide necessary background information and facilitate internally consistent choices, or choices that are in line with users’ prioritized objectives. In order to test different components of the decision‐aiding framework, a six‐part, 2 × 2 × 2 factorial experiment was conducted, yielding eight treatment scenarios. The three factors included: (1) whether or not users could construct their own alternatives; (2) the level of detail regarding the composition of alternatives users would evaluate; and (3) the way in which a final choice between users’ own constructed (or highest‐ranked) portfolio and an internally consistent portfolio was presented. Participants’ self‐reports revealed the framework was easy to use and providing an opportunity to develop one's own risk‐management alternatives (Factor 1) led to the highest knowledge gains. Empirical measures showed the internal consistency of users’ decisions across all treatments to be lower than expected and confirmed that providing information about alternatives’ composition (Factor 2) resulted in the least internally consistent choices. At the same time, those users who did not develop their own alternatives and were not shown detailed information about the composition of alternatives believed their choices to be the most internally consistent. These results raise concerns about how the amount of information provided and the ability to construct alternatives may inversely affect users’ real and perceived internal consistency.     

A Decisional Framework of Offshoring: Integrating Insights from 25 Years of Research to Provide Direction for Future*

Mirroring the growing trend for firms to support their operations by locating activities abroad, research on the practice of offshoring has increased considerably in recent years. However, despite the mounting research, understanding of the key factors influencing decision‐making for offshoring remains surprisingly limited due to fragmentation. In this study, we synthesize and integrate insights from different research domains in order to develop a comprehensive decisional framework for key offshoring decisions. The integrative decisional framework is based on a systematic review of offshoring research published in the most influential management and business journals in the past 25 years. In addition to providing a snapshot of the state of research on decision‐making for offshoring, this study aims to stimulate future research by identifying promising research opportunities. In particular, we propose that future research should use alternative theories to incorporate overlooked aspects of decision‐making, integrate different theories to account for the interdependencies between decisions, and adopt a portfolio perspective that considers each decision as part of an overall offshoring strategy.     

Insights into Flood‐Coping Appraisals of Protection Motivation Theory: Empirical Evidence from Germany and France

Protection motivation theory (PMT) has become a popular theory to explain the risk‐reducing behavior of residents against natural hazards. PMT captures the two main cognitive processes that individuals undergo when faced with a threat, namely, threat appraisal and coping appraisal. The latter describes the evaluation of possible response measures that may reduce or avert the perceived threat. Although the coping appraisal component of PMT was found to be a better predictor of protective intentions and behavior, little is known about the factors that influence individuals’ coping appraisals of natural hazards. More insight into flood‐coping appraisals of PMT, therefore, are needed to better understand the decision‐making process of individuals and to develop effective risk communication strategies. This study presents the results of two surveys among more than 1,600 flood‐prone households in Germany and France. Five hypotheses were tested using multivariate statistics regarding factors related to flood‐coping appraisals, which were derived from the PMT framework, related literature, and the literature on social vulnerability. We found that socioeconomic characteristics alone are not sufficient to explain flood‐coping appraisals. Particularly, observational learning from the social environment, such as friends and neighbors, is positively related to flood‐coping appraisals. This suggests that social norms and networks play an important role in flood‐preparedness decisions. Providing risk and coping information can also have a positive effect. Given the strong positive influence of the social environment on flood‐coping appraisals, future research should investigate how risk communication can be enhanced by making use of the observed social norms and network effects.     

The Effects of Information Overload on Software Project Risk Assessment*

Managers are responsible for providing effective information technology governance of the software development process. Ineffective governance leads to serious resource misallocations and negative consequences concerning Sarbanes‐Oxley compliance. In order for managers to make informed decisions about software development projects, they often need more information than is available through normal information channels, that is, they need an in‐depth review of the at‐risk project. Such in‐depth reviews, however, are costly. Hence, accurate identification of at‐risk projects for in‐depth review is critical to management's ability to govern. This research considers how two factors, information load and time pressure, affect the quality of the project‐selection process. We examine quality by observing the decision strategies involved and then relating these strategies to subsequent decision making. An experiment was conducted with experienced information systems auditors using a combination of policy‐capturing and computerized process‐tracing techniques. The participants in our study cope with information overload by accelerating their decision‐making process and adopting noncompensatory decision processes. Contrary to prior research, our process‐tracing analysis suggests that participants rarely filter information, thus implying that decision makers are unable to process all the information. Coping by resorting to noncompensatory strategies did not decrease decision quality unless combined with accelerated information processing. Participants also increase their weight on the software project risk factors that they repeatedly access and that they view for longer periods of time. The theoretical contributions and practical implications regarding what actions managers can take to reduce the negative impact of information overload are discussed.     

Rationality in Strategic Information Technology Decisions: The Impact of Shared Domain Knowledge and IT Unit Structure*

Rationality is a fundamental concept to several models of IT planning and implementation. Though the importance of following rational processes in making strategic IT decisions is well acknowledged, there is not much understanding on why discrepancies occur in the IT decision‐making process and what factors affect rationality. Drawing upon structural and resource‐based perspectives of strategy, this study examines the influence of shared domain knowledge and IT unit structure on rationality in strategic IT decisions. Data were gathered from 223 senior IT executives using a survey to examine the relationships among the research constructs. The results suggest a positive impact of shared domain knowledge and formalization of IT unit structure on rationality in strategic IT decisions. Further, a highly centralized IT unit structure was found to negatively influence shared domain knowledge. On the other hand, formalization of IT structure positively influenced shared domain knowledge. The implications of the findings for research and practice are presented.     

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.     

Decision Making in Cross‐Functional Teams: The Role of Decision Power*

Through a series of game‐theoretical models, this study systematically examines decision making in cross‐functional teams. It provides a framework for the design of an organization‐specific decision‐making process and for the alignment of a team's microdecision with the “optimal” decision that maximizes the firm's payoff. This study finds that even without changing the team leader, firms could change and even dictate the team's microdecision outcome via adjusting the team member's seniority, empowering team members with veto power or involving a supervisor as a threat to overrule the team decision. This finding implies that to reposition products in the marketplace, structuring cross‐functional teams’ microdecision‐making processes is essential.     

A New Approach to Hazardous Materials Transportation Risk Analysis: Decision Modeling to Identify Critical Variables

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity , and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.     

The Essential Elements of a Risk Governance Framework for Current and Future Nanotechnologies

Societies worldwide are investing considerable resources into the safe development and use of nanomaterials. Although each of these protective efforts is crucial for governing the risks of nanomaterials, they are insufficient in isolation. What is missing is a more integrative governance approach that goes beyond legislation. Development of this approach must be evidence based and involve key stakeholders to ensure acceptance by end users. The challenge is to develop a framework that coordinates the variety of actors involved in nanotechnology and civil society to facilitate consideration of the complex issues that occur in this rapidly evolving research and development area. Here, we propose three sets of essential elements required to generate an effective risk governance framework for nanomaterials. (1) Advanced tools to facilitate risk‐based decision making, including an assessment of the needs of users regarding risk assessment, mitigation, and transfer. (2) An integrated model of predicted human behavior and decision making concerning nanomaterial risks. (3) Legal and other (nano‐specific and general) regulatory requirements to ensure compliance and to stimulate proactive approaches to safety. The implementation of such an approach should facilitate and motivate good practice for the various stakeholders to allow the safe and sustainable future development of nanotechnology.     

A Learning Real Options Framework with Application to Process Design and Capacity Planning

This paper studies the impact of learning on a multi‐staged investment scenario. In contrast to other models in the real options literature in which learning is viewed as a passive consequence of the delay period, this paper quantifies information acquisition by merging statistical decision theory with the real options framework. In this context, real option attributes are discussed from a Bayesian perspective, thresholds are identified for improved decision‐making, and information's impact on downstream decision‐making is discussed. Using real data provided by a firm in the aerospace maintenance, repair, and overhaul industry, the methodology is used to guide a multi‐phased irreversible investment decision involving process design and capacity planning.     

Examining the Antecedents and Consequences of CIO Strategic Decision‐Making Authority: An Empirical Study*

Despite the strategic importance of information technology (IT) to contemporary firms, chief information officers (CIO) often still have varying degrees of strategic decision‐making authority. In this study, we apply the theory of managerial discretion to define CIO strategic decision‐making authority and argue that the CIO's level of strategic decision‐making authority directly influences IT's contribution to organization performance. We also draw on the power and politics perspective in the strategic decision‐making literature to identify the direct antecedents to the CIO's strategic decision‐making authority. A theoretical model is presented and empirically tested using survey data collected from a cross‐industry sample of 174 matched pairs of CIOs and top business executives through structural equation modeling. The results suggest that organizational climate, organizational support for IT, the CIO's structural power, the CIO's level of strategic effectiveness, and a strong partnership between the CIO and top management team directly influence the CIO's level of strategic decision‐making authority within the organization. The results also suggest that the CIO's strategic decision‐making authority in the organization directly influences the contribution of IT to firm performance and that effective CIOs have a greater influence on IT's contribution when provided with strategic decision‐making authority.     

A Modeling Framework for Supply Chain Simulation: Opportunities for Improved Decision Making*

Owing to its inherent modeling flexibility, simulation is often regarded as the proper means for supporting decision making on supply chain design. The ultimate success of supply chain simulation, however, is determined by a combination of the analyst's skills, the chain members' involvement, and the modeling capabilities of the simulation tool. This combination should provide the basis for a realistic simulation model, which is both transparent and complete. The need for transparency is especially strong for supply chains as they involve (semi)autonomous parties each having their own objectives. Mutual trust and model effectiveness are strongly influenced by the degree of completeness of each party's insight into the key decision variables. Ideally, visual interactive simulation models present an important communicative means for realizing the required overview and insight. Unfortunately, most models strongly focus on physical transactions, leaving key decision variables implicit for some or all of the parties involved. This especially applies to control structures, that is, the managers or systems responsible for control, their activities and their mutual attuning of these activities. Control elements are, for example, dispersed over the model, are not visualized, or form part of the time‐indexed scheduling of events. In this article, we propose an alternative approach that explicitly addresses the modeling of control structures. First, we will conduct a literature survey with the aim of listing simulation model qualities essential for supporting successful decision making on supply chain design. Next, we use this insight to define an object‐oriented modeling framework that facilitates supply chain simulation in a more realistic manner. This framework is meant to contribute to improved decision making in terms of recognizing and understanding opportunities for improved supply chain design. Finally, the use of the framework is illustrated by a case example concerning a supply chain for chilled salads.     

Process Innovation Costs in Supply Networks: A Synthesis

This paper provides a synthesis of the literature on the costs incurred by organizations that develop, adopt and use inter‐organizational process innovations in supply networks. A review of the literature in this area suggests that innovation costs influence the pattern of adoption. There is, however, a lack of consensus about what these innovation costs entail. Based on a review of innovation literature in the area of information systems, this paper develops an integrative framework of inter‐organizational process innovation costs. The framework identifies six broad categories of costs (both tangible and intangible) that map onto different stages of organizational innovation: development and initiation costs associated with the generation of an innovation; switching costs and the cost of capital associated with the acceptance stage; and implementation and relational costs associated with implementation. The framework serves not only to organize the existing literature but also to provide the impetus for future research into the role that different categories of costs play in shaping inter‐organizational process innovation in supply networks.     

Institutional transitions,global mindset,and EMNE internationalization

Recently revised theoretical explanations of the internationalization process have been offered to specifically account for the propensity of Emerging Market Multinationals (EMNEs) to engage in accelerated internationalization. However, this literature stream has yet to consider how the fundamental institutional transitions occurring in emerging markets promote the individual and organizational level global mindset that helps account for this accelerated, proactive international expansion. Our dynamic multi-level conceptual framework examines the influences of both the home country institutions and intra-organizational mindsets on the development of EMNE outward FDI decision making. This framework contributes to extant literature by integrating conceptualizations of national culture with the informal and formal institutions offered by institutional theory, while examining how fundamental shifts in these influence the intra-organizational context. Furthermore, our conceptual framework adopts a multi-level perspective of global mindset as an antecedent of firm decision making and adds to the global mindset literature by arguing that institutional transition is a macro level antecedent of global mindset.     

Path to “Stardom” in Globally Distributed Hybrid Teams: An Examination of a Knowledge‐Centered Perspective using Social Network Analysis

Although distributed teams have been researched extensively in information systems and decision science disciplines, a review of the literature suggests that the dominant focus has been on understanding the factors affecting performance at the team level. There has however been an increasing recognition that specific individuals within such teams are often critical to the team's performance. Consequently, existing knowledge about such teams may be enhanced by examining the factors that affect the performance of individual team members. This study attempts to address this need by identifying individuals who emerge as “stars” in globally distributed teams involved in knowledge work such as information systems development (ISD). Specifically, the study takes a knowledge‐centered view in explaining which factors lead to “stardom” in such teams. Further, it adopts a social network approach consistent with the core principles of structural/relational analysis in developing and empirically validating the research model. Data from U.S.–Scandinavia self‐managed “hybrid” teams engaged in systems development were used to deductively test the proposed model. The overall study has several implications for group decision making: (i) the study focuses on stars within distributed teams, who play an important role in shaping group decision making, and emerge as a result of a negotiated/consensual decision making within egalitarian teams; (ii) an examination of emergent stars from the team members’ point of view reflects the collective acceptance and support dimension decision‐making contexts identified in prior literature; (iii) finally, the study suggests that the social network analysis technique using relational data can be a tool for a democratic decision‐making technique within groups.     

Contract,Mechanism Design,and Technological Detail

This paper develops a theoretical framework for studying contract and enforcement in settings with nondurable trading opportunities and complete but unverifiable information. The framework explicitly accounts for the parties' individual trade actions. The sets of implementable state‐contingent payoffs, under various assumptions about renegotiation opportunities, are characterized and compared. The results indicate the benefit of modeling trade actions as individual, rather than as public, and they highlight the usefulness of a structured game‐theoretic framework for applied research.