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Without innovation a business does not have a rational source of competitive advantage in construction (CAC), necessary for appropriating added value. Various management research papers have identified factors that may create innovation conditions. Other researchers have shown how industries have innovated through time. This paper draws upon both sources to show a temporal development for the strategic introduction of innovation within the construction industry. This paper develops the temporal typology as a model for identifying and developing potential sources of innovation. The model (which consists of an ordered set of four epochs) provides a typology of innovation based on different routes through the epochs that together describe the different innovation (business cycle) contexts which can be utilised to identify which sources of innovation may be most appropriate in order to create a further (and higher) source of added value. This paper illustrates the representativeness of the model to “real‐life” businesses.

The evolution of capitalism has gone through four major epochs, from the first tangible exchanges of goods and resources, to the generation of wealth by entrepreneurs held personally accountable for their actions, to cost-cutting measures for increasing efficiencies and maximizing wealth for the few, and finally to a socially irresponsible form. The fourth epoch dispatched the last remaining shards of capitalist responsibility to anyone but investors, as the basis of wealth appropriation shifted to manipulating the speculative future worth of intangible or fictitious capital. This evolution through four epochs has sadly been a process of diminishing value creation (Boje et al., 2017).

We are trapped in an era of socially irresponsible capitalism with little respect for humankind. But, it was not always this way. The earliest references to entrepreneurial behavior emerged in the east during the Han Dynasty and in the west in the eighteenth century. Somewhat like the fourth epoch of the twenty-first century, these global beginnings of early capitalism were also directed by opportunistic desires to pursue wealth generation by taking advantage of people’s needs and wants. Although capitalists have consistently been the prime directors of resources and the distributors of wealth, in the early epochs of capitalism they were different. The early epoch entrepreneurs bore personal risks of business failure, consequences that might impact them for a lifetime.

The antenarrative generative mechanisms, or spirals, help us understand the interconnectivities of “real” and “actual” domains of reality (Bhaskar, 1975; Boje, 2016). Socially irresponsible capitalism is pulling global societies into a downward spiral toward an addiction of speculative destruction and dehumanization, transforming “real” into “actual” realities. We need a force to pull us back up toward a revitalized form of socially responsible capitalism. This force is called the socio-economic approach to management (SEAM), and in the responsible entrepreneurial spirit of earlier epochs, the path to recovery can be accomplished by accountably working with one organization or entity at a time.

This chapter first investigates the historical double-spiral-helix footsteps of socially irresponsible capitalism in the making. Then through a SEAM project example, we discuss how the micro-societal perspective of an organization places it at a deeper level of reality, deeper within the double-spiral-helix meta-reality of macro-societal capitalism. Finally, we demonstrate how the socioeconomic approach can help diagnose the deeper realities with an organization, beyond the evident narratives, to reveal the third spiral of deficiencies. This third spiral disenables the organization’s ability to activate the micro forces of socially responsible capitalism.

Sharding of blockchains consists of partitioning a blockchain network into several sub-networks called “shards,” each shard processing and storing disjoint sets of transactions in parallel. Sharding has recently been applied to public blockchains to improve scalability through parallelism. The throughput of sharded blockchain is optimized when the workload among the shards is approximately the same. The purpose of this paper is to investigate the problem of balancing workload of account-based blockchains such as Ethereum.

Two known consensus-based distributed load-balancing algorithms have been adapted to sharded blockchains. These algorithms migrate accounts across shards to balance transaction processing times. Two methods to predict transaction processing times are proposed.

The authors identify some challenging aspects for solving the load-balancing problem in sharded blockchains. Experiments conducted with Ethereum transactions show that the two load-balancing algorithms are challenged by accounts often created to process a single transaction to optimize anonymity, while existing accounts sparsely generate transactions.

Tests in this work have been conducted on transactions originating from a blockchain platform rather than using artificially generated data distributions. They show the specificity of the load-balancing problem for sharded blockchains, which were hidden in artificial data sets.

The purpose of the paper is to present a constructionist framework for reflection upon time in organizational change processes. The framework directs attention towards (1) institutionalized ideas on organizational change processes anchored in different theoretical epochs, (2) institutionalized norms and virtues that govern the development of specific time regimes in organizations and (3) subjective opportunistic expectations of the future.

The paper is essayistic in character.

The paper explores how constructions of time might be biased by managerial leaders' opportunistic enactment of specific institutionalized ideas anchored in different theoretical epochs in order to comply with culturally embedded and mediated managerial virtues such as being fast and vigorous.

The paper opens up for a differentiated understanding of time in organizational change processes, and it pinpoints the assumptions that guide both theoretical discussions on time, as well as empirical studies.

The framework proffers the reflective practitioner the opportunity to develop informed expectations on time in relation to organizational change processes.

A nuanced and differentiated understanding of how time is construed in organizational change processes might reduce the social costs of underestimating the time organizational changes take – or exaggerating the belief in managerial leaders as sovereigns of time.

The paper contributes with a critical understanding of how time is construed in organizational change processes.

The purpose of this paper is to evaluate the health‐states of unit under test (UUT) in aerospace systems by means of unreliable test outcomes, and the evaluation results can provide a guide for engineers to carry out proper maintenance prior to total failure.

In this paper, the authors formulate the health‐state evaluation (HSE) problem with unreliable test outcomes based on Bayes rule, and develop the Lagrangian relaxation and adaptive genetic algorithm (LRAGA) to solve it. The solution scheme can be viewed as a two‐level coordinated solution framework for the HSE problem. At the top level, the Lagrange multipliers are updated by using AGA. At the bottom level, each of the sub‐problems is solved by using AGA.

The experimental results show that the HSE model appears promising and the LRAGA can obtain the higher quality solution and converge to it at a faster rate than conventional methods (i.e. Lagrangian relaxation (LR), genetic algorithm (GA), simulated annealing (SA) and Lagrangian relaxation and genetic algorithm (LRGA).

The proposed method for the HSE problem of large‐scale systems which include thousands of faults and tests needs to be verified further.

The HSE results for aerospace systems can help engineers to carry out a schedule for prompt maintenance prior to UUTs' failure, to avoid the consequences of total failure. It is important to improve aerospace systems' safety, reliability, maintainability, affordability, and reduce life cycle cost.

This paper constructs the HSE model with unreliable test outcomes based on the Bayes rule and proposes a method based on LRAGA to solve the HSE problem.

Authenticity has emerged as a prevailing purchase criterion that seems to include both real and stylised versions of the truth. The purpose of this paper is to address the negotiation of authenticity by examining the means by which costume designers draw on cues such as historical correctness and imagination to authenticate re-enactments of historical epochs in cinematic artwork.

To understand and analyse how different epochs were re-enacted required interviewing costume designers who have brought reimagined epochs into being. The questions were aimed towards acknowledging the socio-cultural circulation of images that practitioners draw from in order to project authenticity. This study was conducted during a seven-week internship at a costume store called Independent Costume in Stockholm as part of a doctoral course in cultural production.

Authenticity could be found in citations that neither had nor resembled something with an indexical link to the original referent as long as the audience could make a connection to the historical epoch sought to re-enact. As such, it would seem that imagination and historical correctness interplay in impressions of authenticity. Findings suggest that performances of authentication are influenced by socially instituted discursive practices (i.e. jargons) and collective imagination.

This paper contributes to the literature on social and performative aspects of authentication as well as its implications for brands in the arts and culture sector.

Displacement measurement in large-scale structures (such as excavation walls) is one of the most important applications of close-range photogrammetry, in which achieving high precision requires extracting and accurately matching local features from convergent images. The purpose of this study is to introduce a new multi-image pointing (MIP) algorithm is introduced based on the characteristics of the geometric model generated from the initial matching. This self-adaptive algorithm is used to correct and improve the accuracy of the extracted positions from local features in the convergent images.

In this paper, the new MIP algorithm based on the geometric characteristics of the model generated from the initial matching was introduced, which in a self-adaptive way corrected the extracted image coordinates. The unique characteristics of this proposed algorithm were that the position correction was accomplished with the help of continuous interaction between the 3D model coordinates and the image coordinates and that it had the least dependency on the geometric and radiometric nature of the images. After the initial feature extraction and implementation of the MIP algorithm, the image coordinates were ready for use in the displacement measurement process. The combined photogrammetry displacement adjustment (CPDA) algorithm was used for displacement measurement between two epochs. Micro-geodesy, target-based photogrammetry and the proposed MIP methods were used in a displacement measurement project for an excavation wall in the Velenjak area in Tehran, Iran, to evaluate the proposed algorithm performance. According to the results, the measurement accuracy of the point geo-coordinates of 8 mm and the displacement accuracy of 13 mm could be achieved using the MIP algorithm. In addition to the micro-geodesy method, the accuracy of the results was matched by the cracks created behind the project’s wall. Given the maximum allowable displacement limit of 4 cm in this project, the use of the MIP algorithm produced the required accuracy to determine the critical displacement in the project.

Evaluation of the results demonstrated that the accuracy of 8 mm in determining the position of the points on the feature and the accuracy of 13 mm in the displacement measurement of the excavation walls could be achieved using precise positioning of local features on images using the MIP algorithm.The proposed algorithm can be used in all applications that need to achieve high accuracy in determining the 3D coordinates of local features in close-range photogrammetry.

Some advantages of the proposed MIP photogrammetry algorithm, including the ease of obtaining observations and using local features on the structure in the images rather than installing the artificial targets, make it possible to effectively replace micro-geodesy and instrumentation methods. In addition, the proposed MIP method is superior to the target-based photogrammetric method because it does not need artificial target installation and protection. Moreover, in each photogrammetric application that needs to determine the exact point coordinates on the feature, the proposed algorithm can be very effective in providing the possibility to achieve the required accuracy according to the desired objectives.

The purpose of this paper is to present a degenerated simplex search method to optimize neural network error function. By repeatedly reflecting and expanding a simplex, the centroid property of the simplex changes the location of the simplex vertices. The proposed algorithm selects the location of the centroid of a simplex as the possible minimum point of an artificial neural network (ANN) error function. The algorithm continually changes the shape of the simplex to move multiple directions in error function space. Each movement of the simplex in search space generates local minimum. Simulating the simplex geometry, the algorithm generates random vertices to train ANN error function. It is easy to solve problems in lower dimension. The algorithm is reliable and locates minimum function value at the early stage of training. It is appropriate for classification, forecasting and optimization problems.

Adding more neurons in ANN structure, the terrain of the error function becomes complex and the Hessian matrix of the error function tends to be positive semi‐definite. As a result, derivative based training method faces convergence difficulty. If the error function contains several local minimum or if the error surface is almost flat, then the algorithm faces convergence difficulty. The proposed algorithm is an alternate method in such case. This paper presents a non‐degenerate simplex training algorithm. It improves convergence by maintaining irregular shape of the simplex geometry during degenerated stage. A randomized simplex geometry is introduced to maintain irregular contour of a degenerated simplex during training.

Simulation results show that the new search is efficient and improves the function convergence. Classification and statistical time series problems in higher dimensions are solved. Experimental results show that the new algorithm (degenerated simplex algorithm, DSA) works better than the random simplex algorithm (RSM) and back propagation training method (BPM). Experimental results confirm algorithm's robust performance.

The algorithm is expected to face convergence complexity for optimization problems in higher dimensions. Good quality suboptimal solution is available at the early stage of training and the locally optimized function value is not far off the global optimal solution, determined by the algorithm.

Traditional simplex faces convergence difficulty to train ANN error function since during training simplex can't maintain irregular shape to avoid degeneracy. Simplex size becomes extremely small. Hence convergence difficulty is common. Steps are taken to redefine simplex so that the algorithm avoids the local minimum. The proposed ANN training method is derivative free. There is no demand for first order or second order derivative information hence making it simple to train ANN error function.

The algorithm optimizes ANN error function, when the Hessian matrix of error function is ill conditioned. Since no derivative information is necessary, the algorithm is appealing for instances where it is hard to find derivative information. It is robust and is considered a benchmark algorithm for unknown optimization problems.

This paper aims to develop and analyse a new multiple-hypothesis receiver autonomous integrity monitoring (RAIM) algorithm. The proposed algorithm can handle simultaneous multiple failures as well as a single failure.

The proposed algorithm uses measurement residuals and satellite observation matrices of several consecutive epochs for failure detection and exclusion. It detects failures by monitoring the error vector itself instead of monitoring the projection of the error vector. The algorithm reduces the minimum detectable bias via the relative receiver autonomous integrity monitoring (RRAIM) scheme.

The algorithm is able to detect any instance of multiple failures, including failures that are not detected by the conventional RAIM algorithm. It is able to detect multiple failures with magnitudes of several tens of meters, although the algorithm has to solve an ill-conditioning problem. The detection capability of the proposed algorithm is not dependent on satellite geometry.

The algorithm assumes that the error vectors in three consecutive epochs have biases of similar magnitude. As a result, although the algorithm detects occurrences of drifting error, it cannot identify which measurement(s) has the critical error.

The paper includes implications for the development of the RAIM algorithm for aviation users. Especially, it can be a candidate for future standard architecture in multiple constellations, multiple frequency satellite-based augmentation system (SBAS) users.

The paper proposes a new multiple-hypothesis RAIM algorithm with an RRAIM concept. A detailed explanation of the algorithms, including rigorous mathematical expressions, is presented. The paper also includes an analysis of differences in detection capability between conventional algorithm and the proposed algorithm depending on satellite geometry.

According to an extensive and growing literature, we are in the twilight of bureaucracy. The labels applied to the supposed new organizational form include: post‐bureaucratic; post‐modern; post‐hierarchical; and the virtual organisation. The purpose of this paper is to consider the various claims for “epochal” change by evaluating the supporting and contrary evidence.

The paper draws on evidence on the reform of the UK Civil Service over the last few decades to show the intensification of bureaucracy.

The paper takes issue with the “epochalist” visions of sudden transformation which have underpinned much of the comment on post‐bureaucracy, arguing that the concept of post‐bureaucracy is analytically blind to the diversity and complexity of contemporary organizational change.

Locating the debate on post‐bureaucracy in the broader political economy of Neo‐Conservatism reveals an authoritarian dimension which has been absent from most commentaries.