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The study aims to drive conceptual clarity around resistance to information technology projects, integrating multiple facets of the phenomenon from earlier studies.

The study conducts a meta-synthesis of qualitative studies on resistance to technology projects; it analyzes those studies at a case-specific level, compares and contrasts emergent concepts against each other, and “translates” those to the rest of the studies. The study uses the seven-step meta-ethnography method by Noblit and Hare to reciprocally translate emergent concepts to construct the conceptual model.

Through meta-synthesis, the study derives a new conceptual model for resistance to information technology projects, exemplifying how the identified antecedents create user resistance and how the phenomenon progresses within organizations.

This study enriches the observations and conclusions of past individual studies while explicating various facets of the mechanisms that generate and progress technology resistance within organizations. It offers fresh insights into the equivocal nature of the phenomenon and the distinctive ways it progresses from individual to group level.

Many ambitious and costly digital transformation efforts do not succeed due to user resistance. Understanding the mechanisms that create user resistance can help organizations manage technology projects better, thereby reducing the technology assimilation gap and protecting returns on related investments.

There have been extensive studies on technology acceptance (enablers) within organizations, while those relating to technology inhibitors are somewhat limited. However, the symmetry of understanding between enablers and inhibitors is vital for organizations to assimilate promising technologies and transform their business models. This model uses a new lens of sensemaking theory to explain how the antecedents trigger perceived threats and resistance behavior; it highlights the nuances around the development of resistance within individuals and its progression to groups. The resultant model offers better generalizability in organizational contexts.

Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.

To determine the optimal dimensions for a stacked micro‐channel using the genetic algorithms (GAs) under different flow constraints.

GA is used as an optimization tool for optimizing the thermal resistance of a stacked micro‐channel under different flow constraints obtained by using the one dimensional (1D) and two dimensional (2D) finite element methods (FEM) and by thermal resistance network model as well (proposed by earlier researcher). The 2D FEM is used to study the effect of two dimensional heat conduction in the micro‐channel material. Some parametric studies are carried out to determine the resulting performance of the stacked micro‐channel. Different number of layers of the stacked micro‐channel is also investigated to study its effect on the minimum thermal resistance.

The results obtained from the 1D FEM analysis compare well with those obtained from the thermal resistance network model. However, the 2D FEM analysis results in lower thermal resistance and, therefore, the importance of considering the conduction in two dimensions in the micro‐channel is highlighted.

The analysis is valid for constant properties fluid and for steady‐state conditions. The top‐most surfaces as well as the side surfaces of the micro‐channel are considered adiabatic.

The method is very useful for practical design of micro‐channel heat‐sinks.

FEM analyses of stacked micro‐channel can be easily implemented in the optimization procedure for obtaining the dimensions of the stacked micro‐channel heat‐sinks for minimum thermal resistance.

Seeks to help managers to recognize different types of resistance and how to react to them. Categorizes types of resistance (resistance quadrants) and presents questions to help identify the personality of the resistor. Resistance to change can be intentional or unintentional, covert or overt. Describes causes of resistance and presents diagnostic questions. Managers with self‐awareness and a sense of humour are most successful in overcoming resistance to change.

This paper examines organizational change, focusing on the distinction of changes according to their scope and presenting a typology of evolutionary and strategic changes. It also offers an in‐depth study of resistance to change. Through empirical research, the paper analyzes the importance of the sources of resistance to change defined theoretically, and considers both types of changes. The article shows which sources of resistance differ most, according to the scope of change, offering hints about where organizations should pay special attention when initiating a change process.

Traditionally, resistance has been cast as adversarial ‐ the enemy of change that must be defeated if change is to be successful. While it is apparent that classical management theory viewed resistance in such a manner, recent literature contains much evidence that suggests resistance may indeed be useful and is not to be simply discounted. Present day suggestions and prescriptions for managing resistance have evidently disregarded this research and left little room for utility in resistance. This paper argues that the difficulty of organisational change is often exacerbated by the mismanagement of resistance derived from a simple set of assumptions that misunderstand resistance’s essential nature. It is suggested that management may greatly benefit from techniques that carefully manage resistance to change by looking for ways of utilising it rather than overcoming it.

This article discusses power and resistance in commercial environments. It finds that a company's ability to realize its goals (fulfill its strategy) is a function of its ability to deal with resistance; to recognize it first of all, and then to find ways to overcome it, which inevitably involve the use of power in some form.

The paper examines strategies used by pharmaceutical companies for getting drugs prescribed, programs by credit card companies to defeat resistance to card proliferation, and strategies by software companies to overcome resistance in OEMs to product acceptance.

The author concludes that the success of the products/companies studied is explained by their capacity for overcoming resistance, that it cannot be attributed to a compelling vision statement, or a five‐year plan, a competitive analysis, or any of the other strategy approaches used by the majority of companies.

All companies, presumably, have goals, and all companies operate in power‐dependent environments, and all companies, whether they recognize it or not, face resistance beyond the existence of competitors. The key is to be able to see resistance, and to understand how it is manifesting itself against a specific goal.

The thesis of the paper is important to practitioners because it gets them thinking about resistance beyond the existence of competitors. It reveals other, more powerful sources of opposition, and gives them a new platform for strategy based on finding power over resistance.

Termination resistances can affect the behaviour of thin‐film resistors. Depending on the dimensions of a resistor both the TCR and the long‐term stability will be affected, while the termination resistance forms part of the practical resistance value. This paper deals with the results of an investigation concerning the influence of termination resistances with respect to the behaviour of thin‐film resistors. Three thin‐fiim technologies were investigated. Values for the resistance, TCR and ageing drifts of both the bulk material and the terminations will be discussed. Some remarks on the structure of a termination will be mentioned.

The purpose of this paper is to optimize the configuration sizes of micro‐channel cooling heat sink using the thermal resistance network model. The optimized micro‐channel heat sink is simulated by computational fluid dynamics method, and the total thermal resistance is calculated to compare with that of thermal resistance network model.

Taking the thermal resistance and the pressure drop as goal functions, a multi‐objective optimization model was proposed for the micro‐channel cooling heat sink based on the thermal resistance net work model. The Sequential Quadratic Programming procedure was used to do the optimization design of the structure size of the micro‐channel. The optimized micro‐channel heat sink was numerically simulated by computational fluid dynamics (CFD) software.

For the heat sink to cool a chip with the sizes of L × W = 2.5 mm × 2.5 mm and the power of 8 W, the optimized width and height of the micro‐channel are 154 μm and 1,000 μm, respectively, and its corresponding total thermal resistance is 8.255 K/W. According to the simulation results, the total thermal resistance of whole micro‐channel heat sink R_total is 7.596 K/W, which agrees well with the analysis result of thermal resistance network model.

The convection heat transfer coefficient is calculated approximatively here for convenience, and that may induce some errors. Originality/value –The maximum difference in temperature of the optimized micro‐channel cooling heat sink is 59.064 K, which may satisfy the requirement for removal of high heat flux in new‐generation chips.

The aim of this work was to validate the Wilson and Laing theoretical mathematical model for estimating the intrinsic “dry” thermal resistance of upper‐bedding, and compare the two‐dimensional models commonly used to estimate the “dry” thermal resistance of bedding in use, with the actual intrinsic “dry” thermal resistance measured using an infant thermal manikin. The Wilson and Laing model was the only model used adequately to estimate the intrinsic “dry” thermal used resistance of materials arranged over the infant thermal manikin. Estimation of intrinsic “dry” thermal resistance of bedding during use is not adequate using two‐dimensional models. Further investigation into the relationship between thermal resistance, conditions of use, and SIDS using the Wilson and Laing model is recommended.