HEC Montréal

Abstract Two very different models of product innovation are postulated and tested. The conservative model assumes that innovation is performed reluctantly, mainly in response to serious challenges. It therefore predicts that innovation will correlate positively with environmental, information processing, structural and decision making variables that represent, or help to recognize and cope with these challenges. In contrast, the entrepreneurial model supposes that innovation is always aggressively pursued and will be very high unless decision makers are warned to slow down. Thus negative correlations are predicted between innovation and the variables that can provide such warning. Correlational and curvilinear regression analyses revealed that each model was supported by conservative and entrepreneurial sub‐samples, respectively, in a diverse sample of 52 Canadian firms.

The SOC-8 guidelines are intended to be flexible to meet the diverse health care needs of TGD people globally. While adaptable, they offer standards for promoting optimal health care and guidance for the treatment of people experiencing gender incongruence. As in all previous versions of the SOC, the criteria set forth in this document for gender-affirming medical interventions are clinical guidelines; individual health care professionals and programs may modify these in consultation with the TGD person.

Process studies focus attention on how and why things emerge, develop, grow, or terminate over time. We identify various ontological assumptions underlying process research, explore its methods and challenges, and draw out some of its substantive contributions revealed in this Special Research Forum on Process Studies of Change in Organization and Management. Process studies take time seriously, illuminate the role of tensions and contradictions in driving patterns of change, and show how interactions across levels contribute to change. They may also reveal the dynamic activity underlying the maintenance and reproduction of stability.

Abstract Whereas much is known about the relationships between strategy and structure, and between environment and structure, too little is known about a third link—the relationship between strategy‐making and environment. An empirical study was conducted upon two distinct samples of firms. We hypothesized that increases in environmental dynamism, hostility and heterogeneity should be related to specific changes in the amount of analysis and innovation which characterizes strategy‐making activity. Most of these relationships tended to be much stronger in successful than in unsuccessful samples of firms.

Stochastic programming can effectively describe many decision-making problems in uncertain environments. Unfortunately, such programs are often computationally demanding to solve. In addition, their solution can be misleading when there is ambiguity in the choice of a distribution for the random parameters. In this paper, we propose a model that describes uncertainty in both the distribution form (discrete, Gaussian, exponential, etc.) and moments (mean and covariance matrix). We demonstrate that for a wide range of cost functions the associated distributionally robust (or min-max) stochastic program can be solved efficiently. Furthermore, by deriving a new confidence region for the mean and the covariance matrix of a random vector, we provide probabilistic arguments for using our model in problems that rely heavily on historical data. These arguments are confirmed in a practical example of portfolio selection, where our framework leads to better-performing policies on the “true” distribution underlying the daily returns of financial assets.

We propose an improved version of the neighbor-joining (NJ) algorithm of Saitou and Nei. This new algorithm, BIONJ, follows the same agglomerative scheme as NJ, which consists of iteratively picking a pair of taxa, creating a new mode which represents the cluster of these taxa, and reducing the distance matrix by replacing both taxa by this node. Moreover, BIONJ uses a simple first-order model of the variances and covariances of evolutionary distance estimates. This model is well adapted when these estimates are obtained from aligned sequences. At each step it permits the selection, from the class of admissible reductions, of the reduction which minimizes the variance of the new distance matrix. In this way, we obtain better estimates to choose the pair of taxa to be agglomerated during the next steps. Moreover, in comparison with NJ's estimates, these estimates become better and better as the algorithm proceeds. BIONJ retains the good properties of NJ--especially its low run time. Computer simulations have been performed with 12-taxon model trees to determine BIONJ's efficiency. When the substitution rates are low (maximum pairwise divergence approximately 0.1 substitutions per site) or when they are constant among lineages, BIONJ is only slightly better than NJ. When the substitution rates are higher and vary among lineages,BIONJ clearly has better topological accuracy. In the latter case, for the model trees and the conditions of evolution tested, the topological error reduction is on the average around 20%. With highly-varying-rate trees and with high substitution rates (maximum pairwise divergence approximately 1.0 substitutions per site), the error reduction may even rise above 50%, while the probability of finding the correct tree may be augmented by as much as 15%.

Executive Overview The conventional wisdom concerning environmental protection is that it comes at an additional cost imposed on firms, which may erode their global competitiveness. However, during the last decade, this paradigm has been challenged by a number of analysts (e.g., Porter & van der Linde, 1995), who have argued basically that improving a company' environmental performance can lead to better economic or financial performance, and not necessarily to an increase in cost. The aim of this paper is to review empirical evidence of improvement in both environmental and economic or financial performance. We systematically analyze the mechanism involved in each of the following channels of potential revenue increase or cost reduction owing to better environmental practices: (a) better access to certain markets; (b) differentiating products; (c) selling pollution-control technology; (d) risk management and relations with external stakeholders; (e) cost of material, energy, and services; (f) cost of capital; and (g) cost of labor. In each case, we try to identify the circumstances most likely to lead to a “win-win” situation, i.e., better environmental and financial performance. We also provide a diagnostic of the type of firms most likely to reap such benefits.

Theorists and researchers interested in employee commitment and motivation have not made optimal use of each other's work. Commitment researchers seldom address the motivational processes through which commitment affects behavior, and motivation researchers have not recognized important distinctions in the forms, foci, and bases of commitment. To encourage greater cross-fertilization, the authors present an integrative framework in which commitment is presented as one of several energizing forces for motivated behavior. E. A. Locke's (1997) model of the work motivation process and J. P. Meyer and L. Herscovitch's (2001) model of workplace commitments serve as the foundation for the development of this new framework. To facilitate the merger, a new concept, goal regulation, is derived from self-determination theory (E. L. Deci & R. M. Ryan, 1985) and regulatory focus theory (E. I. Higgins, 1997). By including goal regulation, it is acknowledged that motivated behavior can be accompanied by different mindsets that have particularly important implications for the explanation and prediction of discretionary work behavior.

Some twenty years ago, Harvard Business School economist and strategy professor Michael Porter challenged conventional wisdom about the impact of environmental regulation on business by declaring that well-designed regulation could actually enhance competitiveness. The traditional view of environmental regulation held by virtually all economists until that time was that requiring firms to reduce an externality like pollution necessarily restricted their options and thus by definition reduced their profits. After all, if profitable opportunities existed to reduce pollution, profit-maximizing firms would already be taking advantage of them. Over the past twenty years, much has been written about what has since become known simply as the Porter Hypothesis. Yet even today, we continue to find conflicting evidence concerning the Porter Hypothesis, alternative theories that might explain it, and oftentimes a misunderstanding of what the Porter Hypothesis does and does not say. This article examines the key theoretical foundations and empirical evidence concerning the Porter Hypothesis, discusses its implications for the design of environmental regulations, and outlines directions for future research on the relationship between environmental regulation, innovation, and competitiveness.

Even though user participation in information system development has long been considered to be a critical factor in achieving system success, research has failed to clearly demonstrate its benefits. This paper proposes user involvement as an intervening variable between user participation and system use. Embedding the constructs of participation and involvement into the theoretical framework of Fishbein and Ajzen, a model is developed and tested in a field study of information system projects. Several key findings emerge from the study. User participation and user involvement represent two distinct constructs, with participation leading to involvement, and involvement mediating the relationship between participation and system use. The critical dimension of user participation is overall responsibility. The role of user participation and involvement is different, depending upon whether system use is mandatory or voluntary.

Diffusion models have emerged as a powerful new family of deep generative models with record-breaking performance in many applications, including image synthesis, video generation, and molecule design. In this survey, we provide an overview of the rapidly expanding body of work on diffusion models, categorizing the research into three key areas: efficient sampling, improved likelihood estimation, and handling data with special structures. We also discuss the potential for combining diffusion models with other generative models for enhanced results. We further review the wide-ranging applications of diffusion models in fields spanning from computer vision, natural language processing, temporal data modeling, to interdisciplinary applications in other scientific disciplines. This survey aims to provide a contextualized, in-depth look at the state of diffusion models, identifying the key areas of focus and pointing to potential areas for further exploration. Github: https://github.com/YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy

The Technology Acceptance model (TAM) is one of the most influential theories in Information Systems. However, despite the model's significant contributions, the intense focus on TAM has diverted researchers’ attention away from other important research issues and has created an illusion of progress in knowledge accumulation. Furthermore, the independent attempts by several researchers to expand TAM in order to adapt it to the constantly changing IT environments has lead to a state of theoretical chaos and confusion in which it is not clear which version of the many iterations of TAM is the commonly accepted one. The present commentary discusses these concerns, speculates on the possible contributions to the current state of affairs, and makes several suggestions to alleviate the problems associated with TAM and to advance IT adoption research to the next stage.

The proposed theory extends research on cognitive and sociopolitical legitimacy, reputation, and status by advancing an evaluator's perspective on these concepts as forms of social judgment, each addressing a different evaluator's question about the organization. I describe how evaluators make their social judgments under conditions of bounded rationality and how cognitive and social factors influence this process. The proposed process model of social judgment formation highlights the complex and nondeterministic nature of this process.

To better explain resistance to information technology implementation, we used a multilevel, longitudinal approach. We first assessed extant models of resistance to IT. Using semantic analysis, we identified five basic components of resistance: behaviors, object, subject, threats, and initial conditions. We further examined extant models to (1) carry out a preliminary specification of the nature of the relationships between these components and (2) refine our understanding of the multilevel nature of the phenomenon. Using analytic induction, we examined data from three case studies of clinical information systems implementations in hospital settings, focusing on physicians’ resistance behaviors. The resulting mixed-determinants model suggests that group resistance behaviors vary during implementation. When a system is introduced, users in a group will first assess it in terms of the interplay between its features and individual and/or organizational-level initial conditions. They then make projections about the consequences of its use. If expected consequences are threatening, resistance behaviors will result. During implementation, should some trigger occur to either modify or activate an initial condition involving the balance of power between the group and other user groups, it will also modify the object of resistance, from system to system significance. If the relevant initial conditions pertain to the power of the resisting group vis-à-vis the system advocates, the object of resistance will also be modified, from system significance to system advocates. Resistance behaviors will follow if threats are perceived from the interaction between the object of resistance and initial conditions. We also found that the bottom-up process by which group resistance behaviors emerge from individual behaviors is not the same in early versus late implementation. In early implementation, the emergence process is one of compilation, described as a combination of independent, individual behaviors. In later stages of implementation, if group level initial conditions have become active, the emergence process is one of composition, described as the convergence of individual behaviors.

After decades of being viewed as obsolete and problem ridden, recent research has begun to show that major, publicly traded family-controlled businesses (FCBs) actually out-perform other types of businesses. This article examines the nature of such family businesses in an attempt to explain why some seem to do so well and others so poorly. It begins with four fundamental governance choices that distinguish among different kinds of family businesses: level and mode of family ownership, family leadership, the broader involvement of multiple family members, and the planned or actual participation of later generations. Using precepts from agency and stewardship theory, it relates these dimensions to the nature of the resource-allocation decisions made by the business and capability development, which in turn have implications for financial performance. Propositions are drawn about the drivers that make some family businesses great competitors—while leaving others at a disadvantage.

The vehicle routing problem with time windows (VRPTW) is a generalization of the vehicle routing problem where the service of a customer can begin within the time window defined by the earliest and the latest times when the customer will permit the start of service. In this paper, we present the development of a new optimization algorithm for its solution. The LP relaxation of the set partitioning formulation of the VRPTW is solved by column generation. Feasible columns are added as needed by solving a shortest path problem with time windows and capacity constraints using dynamic programming. The LP solution obtained generally provides an excellent lower bound that is used in a branch-and-bound algorithm to solve the integer set partitioning formulation. Our results indicate that this algorithm proved to be successful on a variety of practical sized benchmark VRPTW test problems. The algorithm was capable of optimally solving 100-customer problems. This problem size is six times larger than any reported to date by other published research.

Abstract There already exists a substantial body of work dealing with the relationships between strategy and structure. But most of the studies oversimplify things by focusing mainly on diversification and divisionalization. Recent literature has derived more complex and integrated views of strategy and structure, much of it isolating common types, ‘gestalts’, or configurations. This paper suggests a new approach for examining the relationships between strategy and structure and proposes some functional linkages between several complex strategic and structural configurations.

ABSTRACT: The intermeshing of disciplines from the natural sciences, social sciences, engineering and management has become essential to addressing today's environmental challenges. Yet, this can be a daunting task because experts from different disciplines may conceptualize the problems in very different ways and use vocabularies that may not be well understood by one another. This paper explores three alternative environmental concepts used in transdisciplinary research, and outlines some of the epistemological and practical problems that each one poses. It pays particular attention to the increasingly popular concept of “circular economy”, and contrasts it with the more commonly-used concepts of “environmental sciences” and “sustainable development”. In clarifying the nature, meaning and inter-relationship of these alternative concepts, the paper helps trans-disciplinary researchers to understand the opportunities and challenges associated with each one.

Validity and generalization continue to be challenging aspects in designing and conducting case study evaluations, especially when the number of cases being studied is highly limited (even limited to a single case). To address the challenge, this article highlights current knowledge regarding the use of: (1) rival explanations, triangulation, and logic models in strengthening validity, and (2) analytic generalization and the role of theory in seeking to generalize from case studies. To ground the discussion, the article cites specific practices and examples from the existing literature as well as from the six preceding articles assembled in this special issue. Throughout, the article emphasizes that current knowledge may still be regarded as being at its early stage of development, still leaving room for more learning. The article concludes by pointing to three topics worthy of future methodological inquiry, including: (1) examining the connection between the way that initial evaluation questions are posed and the selection of the appropriate evaluation method in an ensuing evaluation, (2) the importance of operationally defining the ‘complexity’ of an intervention, and (3) raising awareness about case study evaluation methods more generally.

Dantzig-Wolfe decomposition and column generation, devised for linear programs, is a success story in large-scale integer programming. We outline and relate the approaches, and survey mainly recent contributions, not yet found in textbooks. We emphasize the growing understanding of the dual point of view, which has brought considerable progress to the column generation theory and practice. It stimulated careful initializations, sophisticated solution techniques for the restricted master problem and subproblem, as well as better overall performance. Thus, the dual perspective is an ever recurring concept in our “selected topics.”